MSS erence pumNBS SPECIAL PUBLICATION 533

U.S. DEPARTMENT OF COMMERCE / National Bureau of Standards. Characterization

of Particles

i33
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Characterization of Particles

Proceedings of the Particle Analysis Session

NATIONAL BUREAU

OF STAJTOARDS LIBRARY of the 13th Annual Conference of the Microbeam Analysis Society held at Ann Arbor, Michigan, June 22, 1978

APR 2 5 1980 QC/oo

. U£l

no- 6s 3

Kurt F. J. Heinrich, Editor

Center for Analytical Chemistry

National Measurement Laboratory

National Bureau of Standards

Washington, D.C. 20234

U.S. DEPARTMENT OF COMMERCE, Philip M. Klutznick, Secretary

Luther H. Hodges, Jr., Deputy Secretary Jordan J. Baruch, Assistant Secretary for Productivity, Technology, and Innovation NATIONAL BUREAU OF STANDARDS, Ernest Ambler, Director

Issued April 1980
Library of Congress Catalog Card Number: 80-600033

National Bureau of Standards Special Publication 533

Nat. Bur. Stand. (U.S.), Spec. Publ. 533, 222 pages (Apr. 1980) CODEN: XNBSAV

U.S. GOVERNMENT PRINTING OFFICE WASHINGTON: 1980

For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, D.C. 20402

Price $6.50 (Add 25 percent for other than U.S. mailing).
FOREWORD

The Center for Analytical Chemistry of the National Bureau of Standards, National Measurement Laboratory, is concerned with the development of new techniques of analysis as well as the improvement of existing methods

of chemical analysis. Since one of its goals is to further the dissemination of knowledge, the NBS Center

for Analytical Chemistry has published a series of Special Publications covering areas of analytical

chemistry such as Quantitative Electron Probe Microanalysis (NBS Special Publication 298) , Secondary

Ion Mass Spectrometry (NBS Special Publication 427), and The Use of Monte Carlo Calculations in Electron Probe Microanalysis and Scanning Electron Microscopy (NBS Special Publication 460) . These publications are available from the Superintendent of Documents, Government Printing Office, Washington, DC 20402. The subject of this volume, the characterization of particles, is of great importance to many scientific and technological fields, including metallurgy, energy

generation, pollution prevention, recycling of materials,

and biology. This publication should serve to document

the current state of particle characterization, and should therefore be a valuable reference to workers in the area.

J. D. Hoffman, Director

National Measurement Laboratory
PREFACE

The characterization of microscopic particles

includes the determination of size and shapes as well as elementary and molecular chemical analysis. In the Gas

and Particulate Science Division of the Center for Analytical Chemistry, NBS, and in other Divisions of the National Measurement Laboratory, several advanced

instrumental techniques were applied to these ends. The editor of this publication was invited to organize and chair at the Conference of the Microbeam Analysis Society

(Ann Arbor, June 22, 1978) a special session on the characterization of microscopic particles. Parts of the materials contained in papers 3-12 were orally presented

at this session. The materials here presented have been brought up to date and three papers not orally presented in Ann Arbor were added to this publication in order to obtain a fuller coverage of the subject. Since a written publication

covering this subject was not previously available, it can be expected that this NBS Special Publ ication wi 1 1 be found useful by a wide range of technologists interested

in particulate matter.
ABSTRACT

This document contains a series of invited papers on the subject of Particle Characterization. Part of the material presented here was presented orally at the Thirteenth Annual Conference of the Microbeam Analysis Society,

at Ann Arbor, Michigan, on June 22, 1978. The publication

describes microscopic and analytical techniques for the characterization of single microscopic particles. Applications of these techniques to problems of general interest

are also included.

Key words: Biological fluids; electron microscopy; electron microprobe; ion probe; light microscopy; microanalysis;

microdroplets; particles; particulate matter.
TABLE OF CONTENTS

FOREWORD. PREFACE . ABSTRACT. CHARACTERIZATION OF PARTICLES

K. F. J. Heinrich

OPTICAL MICROSCOPY OF PARTICLES

E. B. Steel VARIATION IN X-RAY INTENSITY RATIOS USED TO IDENTIFY ASBESTOS FIBERS

John C. Russ QUANTITATIVE ANALYSIS OF SMALL PARTICLES USING WAVELENGTH AND ENERGY DISPERSIVE

SYSTEMS IN AN ELECTRON BEAM INSTRUMENT 21 John Gavrilovic

PROCEDURE FOR THE QUANTITATIVE ANALYSIS OF SINGLE PARTICLES WITH THE ELECTRON PROBE . . 2? J. A. Small, K. F. J. Heinrich, D. E. Newbury, R. L. Myklebust, and C. E. Fiori MONTE CARLO ELECTRON TRAJECTORY SIMULATION - AN AID FOR PARTICLE ANALYSIS 3< Dale E. Newbury, Robert L. Myklebust, Kurt F. J. Heinrich, and John A. Small QUANTITATIVE CHARACTERIZATION OF PARTICULATES BY SCANNING AND HIGH VOLTAGE

ELECTRON MICROSCOPY

R. J. Lee and R. M. Fisher CHARACTERIZATION OF COAL GASIFICATION PARTICULATES BY SEM, EDS, AES, XPS, AND

ITS RELEVANCE TO INHALATION TOXICOLOGY 8^', D. L. Davidson and E. M. Gause ACCURACY OF ELECTRON MICROPROBE ANALYSIS OF BIOLOGICAL FLUIDS: CHOICE OF STANDARD

SOLUTIONS, AND RANGE OF LINEARITY OF THE CALIBRATION CURVES Nicole Roinel, Lucienne Meny, and Jean Henoc APPLICATION OF AUGER-ELECTRON SPECTROSCOPY AND X-RAY PHOTOELECTRON SPECTROSCOPY

TO THE CHARACTERIZATION OF POLLUTANT PARTICLES • 131

C. J. Powell SECONDARY ION MASS SPECTROMETRY FOR THE ANALYSIS OF SINGLE PARTICLES 13?, Dale E. Newbury

SCOPE AND LIMITATIONS OF SINGLE PARTICLE ANALYSIS BY RAMAN MICROPROBE SPECTROSCOPY. . . 15: Edgar S. Etz and John J. Blaha LASER MICROPROBE MASS ANALYSIS (LAMMA) IN PARTICLE ANALYSIS 19<

R. Kaufmann and P. Wieser

In order to adequately describe materials and experimental procedures,

it was occasionally necessary to identify commercial products by manufacturer's name or label. In no instance does such identification

imply endorsement by the National Bureau of Standards nor does it imply that the particular products or equipment is necessarily the best available for that purpose.
I tional Bureau of Standards Special Publication 533. This Publication Originated from a

lecial Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

iciety, Ann Arbor, MI, June 22, 1978. (Issued April 1980)

: < i CHARACTERIZATION OF PARTICLES

K. F. J. Heinrich*

Gas and Particulate Science Division

National Bureau of Standards Washington, D. C. 20234 Introduction

In particles of microscopic dimensions, many properties vary from those of macroscopic

)1 ids and liquids. This is mainly due to the much larger ratio of surface to volume and

i the correspondingly large surface effects. Microscopic particulates thus resemble a fferent state of aggregation. Particulate materials play important roles in all aspects of life: soils, sands,

igments, solid insecticides, as well as living cells and cellular organelles, bacteria,

id viruses, to only cite a few, are all constituted of microscopic particles. In addition,

arious human activities cause the production and/or dissemination of particles of potenially unfavorable economic or health effects. Examples include particulate air pollutants

-jch as fly ash and asbestos fibers, fallout particles, wear particles in oils, and

articulate pollutants of waters.

The macroscopic characterization of such particulates by diverse means (including the •etermination of particle size distribution and chemical analysis) is a subject of enormous

readth which we will not consider here. In many instances, however, it is necessary to naracterize individual single particles and to distinguish them from particles having difarent origin, properties, and/or significance. In special sessions of the Thirteenth

.nnual Conference of the Microbeam Analysis Society [l] 1 (Ann Arbor, Mich., June 19-23,

978), eleven papers dealing with studies of particles were presented. Selected communicaions covering the material presented in these papers, and extensively revised since the

AS Conference, are the subject of the present publication. Observable Characteristics of Prime Interest

Among the characteristics of particles which may be of interest to the investigator,

|re size, shape, optical properties, composition, structure, and heterogeneity.

The relevance of particle size to aerodynamic properties, respirabil ity, and, in jertain types of particles, toxicity, is widely discussed in literature. Shape has

imilar implications, particularly in the aspects of toxicity of fibrous minerals [2]. his and other microscopic aspects are easily observable in microscopes of appropriate

jpatial resolution. Hence, microscopy in its various forms plays a prominent role in article identification.

A second area of great interest is compositional analysis, either on an elemental

Papers 3-10), isotopic (Paper 10), or molecular (Paper 11) level. Finally, the structure

f crystalline lattices can be characterized by the optical microscope or by electron

liffraction.

*New address: Office of International Relations, National Bureau of Standards,

Washington, D.C. 20234. ^Figures in brackets indicate literature references at the end of this paper.

1
It is important to realize that the size range of particles considered to be micro- scopic extends from a few pm to 1 mm. But diverse techniques have different size ranges

of applicability, and must therefore be chosen accordingly (figure 1). The difficulties

of microscopic and spectroscopic identification, as well as the cost of analysis and of the required equipment, increase sharply with decreasing particle size. Therefore, most of the published work deals with particles of diameter above 1 pm, although there is enormous interest in the particles which are smaller than 1 pm.

1

'

IO' 10 I0" 8 I0"6

IO*" 4 IO" 2 10° m

Figure 1. Typical ranges of dimensions of excited regions with several techniques: AEM - analytical electron transmission microscopy; AUGER - electron probe Auger micro- analysis - EELS - electron energy low spectroscopy; EPMA - electron probe micro- analysis; MRS - Micro-Raman spectroscopy; SEM - scanning electron microscopy;

SIMS - secondary ion mass spectroscopy (ion probe microanalysis), XRF - x-ray fluorescence. The horizontal scale represents the diameter of the analyzed

region in the plane of the specimen surface and the vertical scale represents

depth.

2
The inclusion of paper 9, of Roinel et al., deserves some comment, since it deals with

le analysis of small drops of biological fluids. Although these drops are typically

)-100 urn in diameter, the dehydration of the fluid produces small (>1 urn diameter)

articles of solid residue, and the calibration problems discussed in this paper are

elated to the dimensions of these particles. Some aspects of relevance to this topic are

so included in the paper by Newbury et al.

1] Proceedings, 13th Annual Conference, Microbeam Analysis Society of America, Ann Arbor,

Mich., June 19-23, 1978, obtainable from K. F. J. Heinrich, Bldg. 222, Rm. A-119,

Nat. Bureau of Standards, Washington, D. C. 20234.

2] Proceedings of Workshop on Asbestos: Definitions and Measurement Methods, NBS, Gaithersburg, Md. , July 18-20, 1977, C. C. Gravatt, P. D. LaFleur, K. F. J. Heinrich,

eds. , NBS Special Publication 506 , U. S. Dept. of Commerce.

In order to adequately describe materials and experimental procedures, it was occasionlly necessary to identify commercial products by manufacturer's name or label. In no nstance does such identification imply endorsement by the National Bureau of Standards nor

oes it imply that the particular product or equipment is necessarily the best available

or that purpose. The opinions of authors outside of NBS do not reflect that of NBS.

3

ational Bureau of Standards Special Publication 533. This Publication Originated from a oecial Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

ociety, Ann Arbor, MI, June 22, 1978. (Issued April 1980) OPTICAL MICROSCOPY OF PARTICLES

E. B. Steel* Bureau of Mines Avondale Metallurgy Research Center

Avondale, Maryland 20782 Abstract

The optical microscope is one of the oldest and most effective

methods for studying the morphology of particulates and for determining

particle identity. A wide range of particle sizes and types are within

the light microscope's useful limits. Particles as small as approxi- mately 0.25 urn can be resolved and optical data can be collected on most particles larger than a few micrometers in diameter. Particle size, orientation, contrast, the depth of field, the similarity of optical properties among different types of particulates, and the microscopists' experience can all play an important role in applying the light microscope to the analysis of particulates. Introduction

The light microscope is an exceptionally versatile tool used in a wide variety of article applications. Whether one's field of interest is with nanoplankton, asbestos, or

ome other area, the microscope is often the first and most efficient means of studying

articulates. The purpose of this paper is to look at the capabilities and limitations of

he light microscope as it is applied to the study of particulates. The actual techniques

entioned are covered in detail in the references provided.

There are two basic types of information that may be obtained by optical microscopy

''hen studying particulates. These are the morphology and the optical properties of the

articles. A variety of data can be collected using the particle morphology, including

ample size distributions [I] 1

, crystal growth and fracture information, and particle idenification. The optical properties are generally measured to identify particles or observe

he orientation of particles, especially in nonbiologic and crystalline s.amples. Discussion

The microscope has many characteristics which are well suited to the study of particuates. Microscopy is generally a nondestructive technique which allows the same particles

•bserved on the microscope to be analyzed by some other technique, such as the laser Raman

ir electron microprobes. Sample preparation is usually relatively simple and quick,

nvolving mounting the particles on a glass slide in a refractive index oil or immersion

ledium. The microscope has a large field of view and is capable of quickly scanning a large

iample area. The approximate size of the field of view observed with the various objectives

s given in Table 1. This scanning capability gives the microscope very good sensitivity

-hat is mainly a function of the amount of time spent looking for a particle. A wide variety

ft particle sizes, from several millimeters to less than a micrometer, can be observed with mly minor changes in the instrument. A number of identification techniques can be adapted

'Current adress: Center for Analytical Chemistry, National Bureau of Standards,

Washington, D.C. 20234

'Figures in brackets indicate literature references at the end of this paper.

5
Table 1. Characteristics for some common light microscope objectives.

Magnification

Numeri cal Aperture

Depth of Field

(urn) Diameter3 of Field

(mm)

Resol vi ngk Power

(um)

3X 0.08 50 9 5 10 0.25 8 2 1.3

50 0.85 1 0.5 0.4

100 1 . 3 0.4 0.4 0.25 Approximate value with 10X oculars. 'Approximate value in green light.

to meet the special problems presented by the sample [2-4]. A permanent record and illustra- tion can be made through the use of photomicrography [5,6]. The generally high contrast of specimens viewed on the microscope makes it a good technique for automated particle sizing and counting. Microscopy can be used quantitatively to find the relative abundance of spe- cific types of particles in a sample by combining the optical information with a counting

technique, such as point counts or area counts. In addition, the qualitative chemistry can

be determined using the methods of chemical microscopy, and phase stability can be defined

for some particles using a hot stage [7,8]. The limitations of the optical microscope are due to the nature of visible light and are often dependent on the size and the specific optical and physical properties of the particles found in a sample.

In order to observe and measure the size and optical parameters of particles, there must

be adequate resolution, contrast, and depth of field for the size and type of particle in the sample. Most microscopes are capable of using a number of optical lenses which yield useful magnifications of approximately 15X to 1500X. Each objective lens has a numerical aperture

(N.A.) which will determine its resolving power at a given wavelength of light [9]. Table 1 gives the resolution in green light for some common objectives. It can be seen that the best resolution in green light is about 0.25 urn. While an observer may be able to see objects somewhat smaller than 0.25 um across, they will not be resolved and accurate meas- urement of these or smaller particles is not possible with the light microscope. In general, if the particles are smaller than about 0.5 urn, electron microscopy is the better

tool for particle sizing. The observation and measurement of particles also requires that they be in a definite

region of focus. The maximum depth of this region is controlled by the numerical aperature

of the objective lens and is called the depth of field. Table 1 shows that the depth of focus decreases with increasing magnification or N.A. An example of some of the problems associated with shallow depth of field are seen in figures 1 and 2. Figure 1 shows the same field of view taken at three different depths. Particles appear and disappear as the microscope is focussed up and down. This makes it possible to miss particles of interest when performing scans of areas, unless it is carefully observed over the full depth of the sample mount. Figure 3 shows a photomicrograph of a coccolith in which the full depth of the individual particle cannot be focussed, so that the edges of the coccolith are in focus

at one point and the interior of the particle at another point. If this type of focus is critical, then the scanning electron microscope, with its superior depth of focus, could be used to observe the particle.
a

' gure 1. Photomicrographs of the same area of a dissolved filter on which asbestos fibers were collected. The light microscope is one of the few instruments capable of observing through the full depth of a cleared or transparent filter. However, as one focusses down through the filter from part (a) to part (c), fibers appear and disappear, making it possible to miss fibers or other particles in the sample. Also, the depth of field is often insufficient to see even the individual fiber

bundles, making their measurement and observation difficult. Photomicrographs

were taken using phase contrast 40X/0.65 NA objective.

7
> 1

* 10 pm

a b c

Figure 2. Photomicrographs of a coccolith, a fossil marine plankton, as seen under bright- field illumination (a), phase contrast (b), and crossed polarized light (c) conditions. Photomicrographs were taken using a 90X/1.4 NA polarized light objective for (a) and (c), and a 100X/1.3 NA phase contrast objective for (b).

100 ym

Figure 3. Photomicrograph (a) exhibits the effect of relief on observation in the light microscope. The refractive index of the mounting medium matches that for the, particles labelled m, which are therefore almost invisible in brightfield illumination. Particles h and 1 have refractive indices that are higher and lower than

the mounting medium and therefore have reasonably good relief. Photomicrograph,

(b) shows the same field of view as that shown in (a). The field in (b) is! viewed through crossed polarizers and the particles marked m are now easily] visible, while the isotropic particle 1 is not visible in this mode of observation.]

8
In addition to resolution and depth of focus, enough contrast must be present between

; particle and the mounting medium to make observation of the particle practical. In

leral , the higher the magnification the lower the contrast. Also, the greater the difrence in the refractive index between the mounting medium and the particle, the greater

! contrast. This latter contrast mechanism is referred to as relief. Figure 3 shows a nmon case where the relief is quite low, that is, when determining the refractive index

a particle. This is done by immersing the particle in an oil with the same or very

lilar refractive index as the particle. In such cases some other contrast mechanism is

?ded to increase the contrast and allow the grain to be observed. These mechanisms

:lude phase contrast, interference contrast, fluorescence, dark field illumination, and

Dssed polarized light [10]. Each of these methods can show different details in the

^phology or optical properties of the sample. Some of these contrast mechanisms are wn in figures 2 and 3. Once the particle is observed, it may be possible to identify it. Many particles may recognized by morphology alone, such as the coccolith shown in. figure 3. This type of

sntifi cation is directly related to the observer's experience and is therefore as much

: as it is science. When identifying particles by their morphology, it is often helpful compare the unknown to a known sample or a photomicrograph of a known sample. (Such as

ose found in McCrone's Particle Atlas [11].) Another way to identify particulates is to

asure their optical properties using the polarizing light microscope. The optical

jperties that are measurable in transmitted light are listed in Table 2. Table 2. Optical and physical properties observable using

the polarizing transmitted light microscope. Refractive Index or Indices Transmitted Color

Relative Light Absorption

Optic Axial Angle Extinction Angle Dispersion

Inclusions (orientation or type) Morphology (cleavage or fracture)

Sign of Elongation Twinning

Bi refringence Optic Sign Optical Indicatrix

Using all the properties listed in Table 2 it is almost always possible to unambigusly identify particulates. However, it is often not possible to measure all of these

tical parameters on every grain in a sample. The particle's size or orientation may not

low some of the properties to be measured and if optically similar grains are present in

e sample, then an unambiguous identification may not be possible.

The most important optical parameter is the refractive index or indices of the

rticle. The number of refractive indices for a particle depends on its crystal symtry. Amorphous substances, such as glass, and crystals with isometric symmetry have one fractive index and are called isotropic substances. Other crystalline material will have

o or three refractive indices, again depending on their crystal symmetry. These nonotropic particles must be oriented in specific directions in order to accurately measure

eir refractive indices. It is common for the grains in a sample to have preferred

9
orientations due to cleavage or crystal faces or to have random orientations that do not allow the specific light vibrations necessary for accurate indices measurements to be observed. In these cases approximate values close to the high and low refractive indices

for the particles are measured. Often this less accurate index determination is still sufficient to identify the type of particle, or at least distinguish it from the other types

of particles in the sample. In other cases this lack of accuracy may cause the index measurement to overlap with the data from other types of particles making unambiguous identification difficult. There are ways to get around the orientation problems, such as simply tapping the coverslip so that the particle orientation changes, or using a universal stage so that the grain orientation can be systematically manipulated [12]. Another factor affecting the measurement of the optical properties and therefore the identification of many grains is the size of the particles. When the particle diameter is below approximately 5 - 10 urn it becomes difficult to measure many of the optical parameters. Birefringence becomes weak or negligible, the orientation of the grain becomes difficult to determine, as do the refractive indices. Below about 1 pm in diameter, the optical parameters are impractical to measure and particle identification is probably not possible. The preceding discussion applies mainly to particles that are transparent to light. For opaque particles, the reflected light microscope must be used to measure the optical properties. These properties include such things as the reflectivity, color, and anisotropy of the particle [13,14]. The reflected light data are not as definitive as the transmitted light data an identification is largely dependent on the operator's experience.

To make these measurements, the particles must be prepared as flat polished specimens, which

is often not practical for particulate samples. However, because of the sample preparation

method, these optical data are especially easy to correlate with electron microprobe data. Conclusions

The optical microscope is an efficient and nondestructive tool which can be applied to many particulate analysis problems. The microscope has a relatively low initial cost and very little upkeep cost with almost no "down" time. Combining this with its relatively

rapid sample preparation and analysis time makes microscopy a very efficient technique.

It can be used as an independent technique within the limits discussed above or due to its nondestructive nature it can be used as a complimentary technique with other types of particle analysis. References

[1] Cadle, R. D. , Particle Size: Theory and Industrial Applications, Reinhold Co., New

York, NY (1965).

[2] Bloss, F. D. , An Introduction to the Methods of Optical Crystallography, Holt, Rinehart, and Winston, Inc. , New York, NY (1961).

[3] Kerr, P. F. , Optical Mineralogy, McGraw-Hill, Inc., New York, NY (1977).

[4] Crossman, G. C. , Anal. Chem. , 20, 976 (1948).

[5] Eastman Kodak Company, Photomicrography, Rochester, NY (1974).

[6] Allen, R. M. , Photomicrography, Van Nostrand Co., Inc., New York, NY (1943).

[7] Chamot, E. M. and Mason, C. W. , Handbook of Chemical Microscopy, John Wiley & Sons,

Inc. , New York, NY (1940).

[8] Julian, Y. and McCrone, W. C. , "Accurate use of hot stages," Microscope, 19, 225-234

(1971).

10
9] Longhurst, R. S. , Geometrical and Physical Optics, Longmans, Green and Co., Ltd London (1964).

0] Needham, G. H. , The Practical Use of the Microscope, Charles C. Thomas, Publishe

Springfield, 111. (1958).

1] McCrone, W. C. and Del ly , J. G. , The Particle Atlas, Ann Arbor Science Publishe

Ann Arbor, Michigan (1973).

12] Emmons, R. C. , "The Universal Stage," Mem. Geol. Soc. Amer. , No. 8 (1943).

i3] Cameron, E. N. , Ore Microscopy, John Wiley & Sons, Inc. , New York, NY (1961).

14] Freund, H. , Applied Ore Microscopy, Macmillan Co. , New York, NY (1966).

!

11
J
.ional Bureau of Standards Special Publication 533. This Publication Originated from a

icial Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

:iety, Ann Arbor, MI, June 22, 1978. (Issued April 1980)

VARIATION IN X-RAY INTENSITY RATIOS USED TO IDENTIFY ASBESTOS FIBERS

John C. Russ 1 EDAX Laboratories

P. 0. Box 135 Prairie View, IL 60069 Identification of asbestos fibers and other small particulate matter observed in TEM

STEM is often based in whole or in part on the ratios of elemental intensities [1-3] 2. underlying principle in this method is the linear relationship between concentration

;io and intensity ratio, which has been proposed by many authors, some of whom measure

5 proportionality factors [4] and others calculate them from quasi-theoretical relationps [5]. To be able to routinely apply this method to confidently identify particles, it is :essary to evaluate the magnitude of variation that may be encountered, and the extent to

ich it may allow for confusion. We have analyzed a series of asbestos minerals and others

ich potentially could be mistaken for them. Table 1 lists the concentrations of the major

ements which would normally be chosen for analysis, and figure 1 shows the concentration

;ios Mg/Si and Fe/Si , indicating that the materials are indeed all distinct. Table 1. iulk concentration (w/o) of major elements (by XRF). Mineral Percent Mg Percent Si Percent Fe Amosite 2.4 - 4.0 22.4 - 23.1 28.4 - 34.2 Anthophyllite 12.7 - 17.2 21.5 - 27.1 4.3 - 8.4 Chrysotile 24.0 - 25.9 18.3 - 19.6 1.4 - 2.4 Crocidol ite 0.6 - 1.60 22.7 - 23.8 27.9 - 29.5 Talc 18.3 - 19.2 28.1 - 29.6 0.3 - 1.0 Tremol ite 14.4 - 14.8 26.5 - 29.6 •1.0 - 3.3

It is important to note that the samples available did not encompass the complete

ige of elemental composition for a given asbestos mineral. (e.g., Crocidolite from

livia contains much more magnesium than amosite from South Africa, although Table 1 shows

gher magnesium levels in amosite than in crocidolite [6].) The additional variation

Issible should be borne in mind, as it will increase the uncertainty to be described.

The uncertainty of mineral identification must also be understood to include confusion

tween asbestos-like and other minerals which happen to contain the same ratios of major

ements, in this case Mg, Si, and Fe. Even though the actual concentrations, crystal

ructure, degree of hydration, and so forth may be quite different, it is only elemental

tios that are used in this method to make the determination. It should also be pointed

t that this general approach is often used for the identification of other small parcles besides the asbestos-like ones being described here. The same types of problems and

tential confusion are present in those situations as well.

resent address: North Carolina State University, Engineering Research Serviced Division,

158 Burlington Engineering Laboratories, Box 5995, Raleigh, North Carolina 27650.

igures in brackets indicate the literature references at the end of this paper.
Figure 1 (a-f). Representative spectra from various mineral particles.

14
Figure 2 shows representative electron-excited spectra of particles at 80 kV in the

STEM. From such spectra, measured for 400 seconds to obtain good counting statistics, we determined the factors k ^. defined by the relationship: Cone _ Inten

x ^

x_ Conc

Si

- xSi Inten<.. G

chrysotile

Mg/Si talc

0

anthophyllite

.5- n

crocidolite

.5 1.0 Fe/Si Figure 2. Plot of concentration ratios for minerals (see Table 1). Since the k^. factor is not truly a constant, but depends to some extent on particle

size, orientation, and matrix composition, we measured a series of particles ranging from

approximately 0.1 to 5 urn, and for the larger particles measured spectra both with the beam

centered on the fiber or particle and with the beam scanning to cover the entire area (or

for some of the longer fibers, a representative section). The total peak area above a fitted background curve was integrated and the mean bulk composition used to calculate

kxSi

factors > which ranged as shown in Table 2.

Mi neral MgSi FeSi Amosite

Anthophyl lite Chrysotile

Crocidol ite Talc

Tremol i te

not determined

1.30 - 1.58

1.29 - 1.42 not determined

1.31 - 1.71

1.31 - 1.65

15

1.12 - 1.57

1.09 - 1.61 not determined

1.22 - 1.59 not determined

not determined
In general, the higher values of k^^. and lower values of kp

e

<-.j represent the larger

particles. The overall mean values for the factors were k^^. = 1.41 and kp

e

<-.j = 1.48. These values include fundamental constants such as fluorescent yield, the influence of microscope parameters such as the accelerating voltage influence on ionization crosssection, and x-ray detector parameters such as beryllium window thickness, and so will vary

from one experimenter and apparatus to another. Since practical identification of mineral particles in the microscope normally involves many particles, it is necessary to restrict the analyzing time per particle. As an appar- ently practical compromise, we chose to count until the silicon peak reached 1000 full scale (at which point its integrated area was 5500-6000 counts). This required times varying

from less than 20 seconds for the larger particles to more than 100 seconds for the smaller

ones. For a series of ten such measurements, all on a single particle of each type (each approximately 0.5 urn in particle or fiber diameter), we then integrated the Mg, Si, and Fe peaks and divided to obtain ratios. Table 3 shows the range of variation due to the statistics of counting, and figure 3 shows a representative spectrum. Table 3. Range of intensity ratios for ten measurements on same particle.

Mineral Mc /Si Fe/Si Amosite 0.023 - 0 181 0.917 - 1 008 Anthophyl 1 ite 0.410 - 0. 489 0.132 - 0 202 Chrysoti le 0.946 - 1. 036 0.021 - 0 104 Crocidol ite 0.010 - 0. 129 0.822 - 0 916

Talc 0.402 - 0. 511 0.006 - 0 051 Tremol ite 0.307 - 0. 413 0.018 - 0 111

Figure 3. Repetitive short time measurement

on fiber of amosite, showing poor peak statistics.

Figure 4 shows these intensity ratio ranges graphically, and figure 5 shows the same ranges enlarged by the error due to assuming the kxS

- factor is constant. It is clear that while many of the minerals can be readily distinguished, not all can. For amosite and crocidolite, some additional means of identification such as the presence of other elements,

or electron diffraction must be added to the simple comparison of intensity ratios of the major elements. Identification of more (preferably all) of the elements present in a mineral can in principle end in positive identification of the mineral. For example, the

16
sodium in crocidolite and manganese in amosite are distinctive. However, in this case the peak of copper (from the sample grid) obscures the presence of any sodium peak, and in any

ase both peaks are smaller than the principal elements already used, so that longer

analysis times would be needed to obtain statistically useful numbers. It is not practical

to use a longer time to reduce the statistical spread, as the overlap would persist.

1.5

| chrysotile

J | 1 anthophyllite

I tremolite

Figure 4. Plot of intensity

ratios for minerals

(see Table 3).

.5 1.0 Fe/Si

"So 5

chrysotile

I trer

anthophyllite

Figure 5. Plot of total range

of intensity ratios, including variation

in kxSi

- due to par- ticle size, geometry

and matrix.

Fe/Si

17
Most of the error introduced by neglecting the effect of particle size on the KxSi factor can be eliminated by correcting for absorption, as shown by Goldstein [7]. The factors measured on standards can be converted to the "infinitely thin" case by dividing

them by . e -[(u/p)

s

.- (p/p)

x jpt/2

where (p/p) is determined for the matrix as 1 (p/p)^ from each individual element's mass absorption coefficient, p is the density, t is the approximate size of the particle, and

C

i are the concentrations of the elements present. Then they should be constant independent

of size. When unknowns are measured, the factor can be adjusted by the same method, except

that while the size can be determined adequately from the TEM image, the concentrations are

not known. This is awkward, since it means some iterative calculation is needed. Furthermore, only the concentration ratios are being determined, not the absolute concentrations.

Also, the density can only be guessed at. For these asbestos materials, normalizing the elemental ratios of Mg, Si, and Fe to arbitrarily total to 50 percent gives adequate

results. However, in other quite different materials this could lead to significant errors. Individual correction of the kx

<.. factors for particle size, and conversion to concentration, is only useful for spectra having good counting statistics, and so is too time consuming for routine application to large numbers of analyses. Nevertheless, the use of fully corrected results (i.e. the conversion of spectral data to oxide chemistry with total propagated errors due to statistics) is the only reliable way to obtain meaningful concentrations. This is even more true if different investigators' results are to be compared, since the k^ factors are dependent on the accelerating voltage used. The calculation can also include atomic ratios of the cations present, which may be useful for phase identification as wel 1

An additional caution is that since analysis of samples of this type requires collecting data from large numbers of particles or fibers, the problem of total counting calculation time becoming large to obtain more accurate results can be prohibitive. On the other

hand, one should not assume that the errors described in the simple use of intensity ratio matching will tend to average out when large numbers of fibers are analyzed. This does

not happen, as the errors are generally likely to be strongly biased, and not random. Confused identification is most likely to result when there are mixtures of mineral types present, a frequent occurrence in samples of real interest. The use of x-ray analysis, particularly with interpretation based on simple elemental

ratios, is certainly not adequate for identification of asbestos minerals with the high confidence needed in view of the health and legal concerns regarding these minerals. If the x-ray results are combined with morphology (e.g., fibrous appearance) and, when they

can be obtained, electron diffraction patterns, then fairly conclusive identification can

be made [8]. Unfortunately, this combination requires a skilled and knowledgeable microscopist/analyst, and furthermore is too time-consuming for application to large numbers of particles. Hence, there will probably continue to be some use of the simple

ratio method, which may be permissible if the potential errors and resulting confusions in identification are first studied for the particular case of interest. In general, the experimenter should be very careful in applying this fast and simple method. It is essential to first consider all probable overlaps of identification with other minerals which might be present.

The author is particularly grateful to Dr. F. D. Pooley for advice and comments.

18
References

1] Beaman, D. R. and File, D. M. , Quantitative determination of asbestos fiber concentrations, Anal- Chem. , 48, 101-110 (1976).

"2] Pooley, F. D. , The use of an analytical electron microscope in the analysis of mineral

dusts, PhiJ. Trans . R. Soc. Lond. A. , 286, 625-638 (1977).

^3] Pooley, F. D. , The identification of asbestos dust with an electron microscope microprobe analyzer, Norelco Reporter , Special Issue , 5-9 (1976).

[4] Cliff, G. and Lorimer, G. W. , Quantitative analysis of thin foils using EMMA 4 - the ratio technique, Proc. Fifth Europ, Congr. on Electron Microsc. Manchester, p. 140-141,

London; Inst, of Physics.

[5] Russ, J. C. , The direct element ratio model for quantitative analysis of thin sections, Microprobe Analysis as Applied to Cells and Tissues, Hall, T. , Echlin, P., and Kaufmann, R. , 269-276, (1974).

[6] Pooley, F. D. , private communication.

[7] Goldstein, J. I., Lorimer, V. W. , and Cliff, G. , Quantitative x-ray analysis of thin

films in the electron microscope, MAS Proceedings, 11th Annual Conf . , Aug. 1976,

p. 25A-C.

[8] Chatfield, E. J. , Identification and measurement of asbestos fibers by electron microscopy, Asbestos, February and March 1978.

19

National Bureau of Standards Special Publication 533. This Publication Originated from a Special Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

Society, Ann Arbor, MI, June 22, 1978. (Issued April 1980)

QUANTITATIVE ANALYSIS OF SMALL PARTICLES USING WAVELENGTH AND ENERGY DISPERSIVE SYSTEMS IN AN ELECTRON BEAM INSTRUMENT

John Gavrilovic Walter C. McCrone Associates, Inc. Chicago, Illinois 60616 Microparticles in sizes down to 1-2 um can be quantitatively analyzed in electron beam

instruments using the standard ZAF correction procedure for solid (bulk) and infinitely

large samples. The accuracy of such quantitative analyses is limited primarily by the particle size and subsequent loss of x-ray intensities which, in turn, increase experimental

errors. Such errors cannot be effectively compensated by small particle corrections since

they are mostly random and are caused by instrument instability and counting errors. Ratios

of x-ray intensities for particles below 1 um and particularly below 0.3 um are severely

affected by particle size. The relative change in measured x-ray intensities on very small particles as compared to bulk samples is caused primarily by the decrease in x-ray absorption due to the shorter path within the sample and is significantly higher than the experimental errors incurred during the analysis. Special correction procedures that have been

developed or are currently being developed can be applied to improve the accuracy of the

analysis of such particles [l^.S] 1

. The total intensity of x-rays from small particles (below 6-10 um) falls rapidly with

particle size, as can be seen in figures 1 and 2. Particles larger than 6-12 um have total

x-ray intensities equal to that of a bulk sample. The major cause of the significant drop

in x-ray intensity for particles larger than 10 um, observed by some researchers, is the

result of local changes both in the incident angle of the electron beam and in x-ray takeoff angle, both of which depend on particle shape [4]. The optimum method for analysis of

small particles therefore appears to be to collect x-rays from the small particle while it

is being rastered by the electron beam. Such a raster normally also covers a certain portion of the substrate in order to incorporate the whole projected area of the small particle. To compensate for loss of x-ray intensity during rastering of the substrate one can

use the following correction factor:

where I Q is the corrected intensity from the element, I-j the measured intensity, S r the

total rastered area, and S p the projected area of the small particle. With this method the stability of the measurement is significantly increased and analysis of particles down to approximately 1 um becomes routine. Even particles smaller than 1 um down to 0.1 um can be analyzed semiquantitati vely with a relative accuracy of 20-40 percent without further correction except for the ratio of rastered to projected area.

•'Figures in brackets indicate the literature references at the end of this paper.

21
1.0 20 3.0 4.0 5.0 6.0 PARTICLE SIZE (pm) Figure 1. Size distribution versus total intensity of major elements for K-489 glass particles.

1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 II.

PARTICLE SIZE (fitn) Figure 2. Size distribution versus total intensity of major elements for K-230 glass particles.

22
Both wavelength and energy dispersive systems can be used for quantitative analysis of

;mall particles without corrections provided suitable bulk standards of similar composition

ire available. Low concentration elements (less than 1%) in small particles should be

inalyzed with wavelength dispersive systems because of the excessively high background

nherent in the energy dispersive systems. Figures 3, 4, 5, and 6 show experimental results obtained during analysis of microiarticles of sizes 0.1 urn and larger mounted on a polished beryllium substrate. These

licroparticles were obtained by grinding two types of glass standards produced by the

lational Bureau of Standards for microbeam analysis. As you can see from these diagrams,

.he calculated composition for small particles, down to approximately 2 urn is the same as

: or bulk samples of glass without any corrections. Below approximately 1.5 urn the ratio of

ilements in the small particles drastically changes due to the increase in the ratio of low mergy to high energy x-rays. This is a result of reduction in self-absorption in the

•mailer sample. Such changes are frequently masked by large relative errors common in small

larticle analysis [5]. The wavelength dispersive system gives a lower background and higher

•ensitivity for trace elements, but the associated experimental errors are generally larger

.ecause of the more severe x-ray geometry requirements.

StondordiSi 21.9%

Pb 1.2%

Bo 39.3%

_ Ba

Figure 3. Percent by weight of major

elements versus size as deter- mined by EDS for K-489 glass

particles.

2.0 3.0 4.0 5.0 PARTICLE SIZE (pm)

StondOrdiSi 219%

Pb 1.2%

Bo 39.3%

Figure 4. Percent by weight of major

elements versus size as deter- mined by WDS for K-489 glass

particles.

PARTICLE SIZE (u

23
Standard : Si 14.0% Pb4l.8%

Ba 8.8%

* 4 * Ph i't^^r Si

g <S*-9 < A il^A J, i, 4.0 5.0 6.0 7.0 PARTICLE SIZE (pm)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 PARTICLE SIZE (ym)

Figure 5. Percent by weight of major elements versus size as determined by EDS

for K-230 glass particles (bottom curves - expanded scale).

24
Standard: Si 14.0% Pb4l.8%

Ba 9.0%

* ***** * *"* *

* ^uM A * 4.0 5.0 6.0 7.0 PARTICLE SIZE (pm)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 PARTICLE SIZE (urn)

Figure 6. Percent by weight of major elements versus size as determined by WDS

for K-230 glass particles (bottom curves - expanded scale.

25
A similar set of curves, Figures 7 and 8, show an even more remarkable similarity in composition of the analyzed microparticles and a bulk glass standard K-249, down to 0.2 urn size. Below that size, experimental errors due to low count rates virtually mask the par- ticle size effect.

Standard! Si 14.0%

Pb 39.5%

Bo 9.0%

1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 00

Particle size (pm)

Figure 7. Percent by weight of major elements versus size as determined by EDS

for K-249 glass particles.

Glass K-249 WDS Standard: Si 14.0%

Pb 39.5%

Ba 9.0%

1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 °o

Particle size ( pm ) Figure 8. Percent by weight of major elements versus size as determined by WDS

for K-249 glass particles.

26
Table 1 illustrates the results of an EDS analysis of 30 small particles ranging in size from 0.1 to 11 urn, including the bulk (polished) glass standard K-230. These results

were obtained on an ARL electron microprobe, EMX-SM type, at 10 nA specimen current on beryllium and 20 kV accelerating voltage with an electron beam diameter of 0.1 um. The

probe is equipped with four wavelength-dispersive spectrometers and a high resolution 0RTEC

energy dispersive detector along with a Sargent-Welch vertical turbomolecular pump which

supplies 1 x 10 6 torr contamination-free vacuum. With the steady increase in the precision and accuracy of electron beam analysis of

small particles, special correction methods will be used more frequently. The development

of a relatively simple, reliable, computerized correction procedure will then be of great

help to all small particle analysts. References

[1] Armstrong, J. T. , and Buseck, P. R. , The Minimization of Size and Geometric Effects in the Quantitative Analysis of Microparticles with Electron Beam Instruments, Proceedings

of the Tenth Annual Conference of Microbeam Analysi s Society . [2] Armstrong, J. T. , and Buseck, P. R. , Quantitative Chemical Analysis of Individual Microparticles Using the Electron Microprobe, Anal . Chem. , 47, 2178-2192 (1975).

[3] Small, J. A., Heinrich, K. F. J., et al . , Progress in Quantitation of Single Particle

Analysis with the Electron Probe, Proceedings of Fifteenth Annual Conference of Micro - beam Analysi s Society , Ann Arbor, MI (1978).

[4] Bayard, M. , Microprobe Analysis, Andersen, C. A. ed. , Wiley-Interscience , New York, NY, (1973) pp. 323-348.

[5] Gavrilovic, J., Common Errors in Subnanogram Particle X-ray Analysis, Microscope , 22, 221-227 (1974).

27

National Bureau of Standards Special Publication 533. This Publication Originated from a Special Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

Society, Ann Arbor, MI, June 22, 1978. (Issued April 1980)

PROCEDURE FOR THE QUANTITATIVE ANALYSIS OF SINGLE PARTICLES WITH THE ELECTRON PROBE

J. A. Small, K. F. J. Heinrich, D. E. Newbury, R. L. Myklebust, and C. E. Fiori Center for Analytical Chemistry

National Bureau of Standards Washington, D. C. 20234 Introduction

In recent years, one of the major areas of interest in the field of electron probe

analysis has been the elemental characterization of individual particles. In order to develop a quantitative analysis procedure for particles, there are two major effects

peculiar to particulate analysis which must be taken into account.

The first effect arises from the finite size (mass) of a particle. This mass effect

is important when the excitation volume of the primary electron beam is larger than the

volume of the particle to be analyzed. In this situation, the mass of material participating in x-ray generation is less in the particle than it is in a thick specimen since the

beam electrons may escape through the sides and bottom of the particle.

This effect also results in a reduction of x-ray intensities from the particles relative to the intensities from bulk materials; the deviation from bulk behavior increases in magnitude with decreasing particle size. The mass effect can be demonstrated by comparing

the x-ray emissions from a particle to the emissions from a bulk target of the same composition. The effect is most evident when the comparison is done for a hard energy x-ray line

which has minimal absorption. Such a case is shown in figure 1 by the decrease in the

Ba La intensity from the particles relative to the bulk material for particles smaller than

3 um in diameter.

Id 08

! 1 1 1 1 1 1

Ba La / GLASS K 309 * * MICROSPHERES . Figure

17.4 kV 30°TOA

• EXPERIMENTAL POINTS — THEORETICAL PREDICTIONS - MONTE CARLO 7/19/76

I I I I I I I I

Ba La x-ray intensity for glass spheres ratioed to bulk inten- sity and plotted as a function

of sphere d' intensity,

and TOA=take-off-angle.

DIAMETER OF MICROSPHERE (p)

The second major effect is the result of absorption and is important when the average

x-ray absorption path length for a particle is different from the average path length for a bulk material. The largest deviations from bulk occur when there is high absorption as is typically observed for low energy x-ray lines. Such a situation is common in many samples

containing elements such as aluminum and silicon. The difference in average path length

29
can result in widely different values of x-ray intensities between particle and bulk. For the situation shown in figure 2, the path length A-B in the particle is less than the path

length A-C in the bulk. The reduced average path length results in a greater x-ray emis- J sion from the particle compared to bulk, despite the opposing action of the particle mass

effect. The absorption effect is demonstrated in figure 3 where the silicon intensity | ratio between particle and bulk is above unity for spheres greater than 2.0 urn in diameter.

Figure 2. Diagram of particle absorption effect.

1 1

I

1 1

1 1 Si K

GLASS K 309 MICROSPHERES

17.4 kV 30° TOA

• EXPERIMENTAL POINTS — MONTE CARLO PREDICTIONS -

Figure 3. 23456789 10 DIAMETER OF MICROSPHERE (/im)

Si K x-ray intensity for glass spheres ratioed to bulk inten- sity and plotted as a function

of sphere diameter. I^sphere

intensity, I b=bulk intensity

and TOA=take-off-angle.

Various analytical techniques have been developed for the analysis of particles. These procedures range in complexity from the simple scaling of the peak intensities obtained by conventional analysis programs such as the procedure used by Gavrilovic [l] 1 to the extensive treatment based on shape determination proposed by Armstrong [2]. The main problems with these existing techniques are that the complex procedures require a large computer and extensive analyst training, while the simple scaling procedure is limited

to a small number of particle compositions for which the particle effects are minimized.

1 Figures in brackets indicate the literature references at the end of this paper.

30
At the 1978 Scanning Electron Microscopy meeting, a new approach to quantitative

inalysis of particles based on peak-to-background intensity measurements was proposed

ndependently by Small et al . for the determination of concentrations, and by Statham and

'awley for the determination of concentration ratios [3,4]. This new approach is based on

.he use of the ratio between the characteristic x-ray intensities and the continuous x-ray

ntensities of the same energies (peak-to-background ratios) to eliminate the major particle

•ffects. It is a modification of the method proposed by Hall to correct for the excitation

Kolume in thin films [5]. In this paper, the current status of the analytical procedure eing developed at NBS for particle analysis will be described. In addition, the results

ibtained from the analysis of glass and mineral particles with this procedure will be

:ompared to the results obtained from conventional microprobe analysis procedures. Experimental Techniques

In order to test the particle analysis scheme, it was necessary to obtain particles of

.nown composition. For this purpose, glass particles were made by crushing bulk glass from

.he set of NBS Research Material Glasses [6]. Mineral particles of talc and FeS 2 were also btained for the study. All particles were suspended in ethanol and mounted on a 20 nm arbon film which was supported by a beryllium microscope grid. The samples were coated by acuum evaporation with approximately 10 nm of carbon before analysis.

The experimental measurements were made with an electron microprobe analyzer equipped

ith a lithium-drifted silicon x-ray detector. The beam energy used for the measurements

as 20 keV, the take-off angle was 40 degrees, and the beam current was lx!0~9 A. The

articles were analyzed by scanning the electron beam over an area larger than the crossectional area of the particle in order to minimize beam positioning effects. The analytcal conditions were the same for the mineral particles, but the beam energy was 10 keV for

ale and 15 keV for FeS 2

. Calculation of the Peak-to-Background Ratios

The peak-to-background ratios, R, are calculated from equation (1) in which 1^ equals

he experimental intensity within a region of interest of photon energies for a characterstic line, equals the calculated background intensity, obtained by the data reduction

rocedure, FRAME C [7], for the same region of interest:

R - — ^ (1)

J Bkg

he continuum from the carbon film is ignored and the particle spectrum is assumed to have continuum which originates from only the analyzed particle. This assumption is reasonble since the intensity from the carbon film is small in most cases as shown by the plots

n figure 4, which are the superimposed spectra from an 8 pm particle and the carbon film.

31
els. = 512

L.T =300 sec.

kV. = 20 _g beam current = 1x10 amp

Figure 4. Spectra of 8 um particle and carbon film.

Calculation of Particle Continuum

The continuum for a given particle is fit by a computer with equation (2) which is Lifshin's modification of Kramers' equation [8,9]. It was originally derived for bulk

specimens and is being used to calculate a first approximation for the particle continuum.

A and B are empirical coefficients, f(x) is the absorption term for a bulk specimen, and

is the detector efficiency. Two experimental regions of interest are used to determine

the coefficients A and B. The equation is then used to calculate the continuum as a func- tion of energy. Figure 5 shows an actual spectrum of a particle 10 um in diameter superimposed on the calculated background determined by equation 2. One of the continuum regions selected for

the fit was taken between the Si K and Ca Ka peaks, and the other at an energy slightly

greater than the Fe KB peak. The fit is in good agreement with the experimental continuum

over the entire energy range.

Figure 5. Spectrum showing a 10 pm particle and the background fit.

32
Analytical Procedure and Results Unlike the procedure being developed by Statham in which the results are expressed as concentration ratios, the method under development at NBS expresses results as elemental

concentrations. Equation (3) is the foundation for the particle procedure and resulted from the experimental observation that the emitted peak-to-background ratios from particles are, to a first

approximation, equivalent to the peak-to-background ratios from a bulk sample of the same composition [3]. Although the physical mechanisms of generation of characteristic and

bremsstrahl ung x-rays are different, to a first approximation the two radiations for a given

energy are formed over nearly the same region of the sample. Therefore, the ratio of the

peak intensity to the background intensity of the same energy can be used to normalize out

the effects of absorption and mass.

< P/B Wicle=<P/B W (3) Rearranging equation (3), the peak intensities for the particle can be used to calculate the

values appropriate to the intensity from a hypothetical bulk material of the same composition, P*, equation (4).

P * = P -

P Particle' B Bulk " Bu1k m

^article TM

The values of the intensities, P*'s, can then be used to form x-ray intensity ratios ^''standard' which would then be used as input for a conventional analysis procedure such

as FRAME C. In practice, for a typical particle of unknown composition, bulk material with

the same composition will not be available to measure the values of B^y-j^. These values,

however, can be approximately calculated from the continuum of a standard and from the first

estimate of composition obtained from the hyperbolic iteration loop in the conventional

FRAME C program. These values of B^-j^ can then be used in equation (4) to obtain the

first estimates of P*'s. A set of intensity ratios for a bulk sample of the same composition as the particle is then calculated from equation (5) and used as input for the ZAF

routine. The set of concentrations from each iteration is used to calculate new values of

B (Bulk) and the se °. uence 1S repeated until convergence (in practice 5 iterations). A block

diagram for the particle procedure is shown in figure 6. particle standard

33
Assume

set of Cj's ZAF gives

j = iteration no.

kj(calc), kj(exp), Cj hyperbolic eqn.

Cj+1 Compute Z. Bkg.

part. eqn.

.-j(exp) test

k

J+1 (exp) kj+f (calc)

Figure 6. Flow chart showing the interface of the particle corrections with a ZAF analysis scheme.

Equation (6), which derives the intensity B standard, B Green [10].

(Bulk) from that of the continuum on a (Std)' uses the atomic number dependence of Kramers' law as modified by

f

x (Bulk) . ^BullP

x(Std)

(6)

The subscript "Bulk" refers to the values which are calculated from the current

estimate of the composition as determined by the analysis procedure, and the subscript

"Std" refers to values for the standard. _The Z's are the average atomic numbers, the

f 's are the absorption terms, and the F(Z)'s are the values of Green's correction to Kramers' constant. The values for F(Z) were determined by a computer fit to the experimental curve in Green's thesis [11]. Results from the analysis with Kramers' law of NBS glass K-309 particles are shown in Table 1. Both particles were irregularly shaped and are shown in figures 7a and 7b. Glass

K-411 (see Table 2) was used as the standard for Si, Ca, and Fe, and bulk glass K-309 was used as the standard for Al and Ba. The results from the particle program are substantially

closer to the nominal values than the results from FRAME C. The relative errors for the particle results are all under 10 percent except for Si, which is 11 percent. In comparison,

the results from FRAME C have relative errors on the order of 65 percent.
Table 1. Analysis of K-309 Particles Element True

Composition

Particle Frame

7a 7b Regular Frame

7a 7b (wt.%) (wt.%) (wt. 1) Al 7.9 7.0 8.4 1.4 3.4 Si 18.7 17.8 20.8 3.5 7.9 9.9 10.1 2.0 3.9 Ba 13.

12.4 12.8 2.6 5.0 Fe 10.5 9.3 10.4 2.1 4.3 K-411 Glass Z-13 was the standard for Si, Ca, Fe. K-309 Glass, Z-19 was the standard for Al, Ba. Beam energy was 20 keV. ^rue composition determined by electron probe analysis

Figure 7 a and b. Micrographs of K-309 glass particles 1 and

Table 2. Composition of Glass K-411 Element Wt. percent

5 SiFeMg

Ca

0

25.39 11.20

11.06 43.51 determined by wet chemical analysis.

35
The second method used to calculate the values of from a standard is given by equation (7), which was derived empirically at NBS. This equation takes into account an experimentally observed nonlinear relationship between generated continuum intensity and atomic number. The numerical form was determined by fitting a curve to the plot of the generated continuum for several pure elements vs. the atomic numbers.

B (std)

x t(°- 006E + 0-0642) Zg ulR-0.012E - 0.088] Bulk

(0.006E + 0.0642)Z

n(st(J)

- 0.012E - 0.088

E is the energy in keV for which corresponding intensity is to be calculated, and n is a fitting parameter which is dependent on the beam energy. The values of n which have been observed are 1.0 for 10 keV, 0.64 for 20 keV, and 0.44 for 25 keV. The functional dependence

of n on beam energy is currently being studied. The results of the analysis with this equation for talc particles are shown in Table

3. The calculated values for Al and Mg compare favorably between the methods based on Kramers' equation and the NBS equation. The analyses by both methods are well within a 10 percent relative error, while the values from FRAME C are about 63 percent too low. Table 3 Analysis of talc part icles 3

.

Eq. (6) Eq. (7) Average

7_ Stoic.

b Frame C Kramers NBS Dimension

#1 12 19.3 8.7 19.0 19.1 3 pm

14 29.8 13.4 31.2 30.1 #2 12 19.3 5.6 18.7 19.

2 pm

14 29.8 8.5 30.7 29.8

#3 12 19.3 16.6 17.9 17.5 6 pm

14 29.8 25.4 29.0 27.2

Re a hi energy was 10 keV

K-41 Table 2 was used as the standard for Mg and Si.

a" Results expressed as weight percent. ^Stoichiometric concentration.

A more dramatic effect can be seen in the analyses of FeS 2 particles the results of which are reported in Table 4. These results show a decrease in the relative error for the analysis of Fe from 19 percent for the method based on Kramers' law to approximately 5 percent for the method based on the NBS equation. The relative error on the sulfur analyses

is somewhat greater for particle #2 when the NBS equation is used, but the value is still within six percent.

36
Table 4. Analysis of FeS2 particles 3

. Average

z btoi c. Frame C Kramers NBS Dimension

#1 16 53.4 31 3 53 2 53 5 5 |jm 26 46. 6 30.8 55.7 49^7

#1 16 53.4 46.0 53.2 56.2 5 urn 26 46.6 39.7 55.7 48.3

Beam energy was 15 keV. ZnS and Fe were used as standards.

a Results expressed as weight percent. Stoichiometric concentration.

At the present time, equation (7) is being tested in order to evaluate its applicability to different detector and electron probe geometries. Equation (7) is also being

lodified to improve the accuracy of predicting the continuous x-ray emission of a multilement system from a pure element standard. Additional Areas of Investigation

In addition to the two major particle effects, there are several second-order correcions to the particle analysis scheme which need to be studied in more detail. The first

f these is manifested by an increase in the relative intensities of x-rays in bulk samples

ue to characteristic and continuum fluorescence. The f 1 uorescence- i nduced characteristic

-ray production in bulk samples occurs over a range of distances greater than 10 um from

he beam-sample interaction volume [3]. As a result, in micrometer-sized particles much of

he fluorescence-induced x-ray intensity will be missing. This effect is most significant

or heavy elements in a light matrix. For example, secondary fluorescence could cause aviations on the order of 5-10 percent for Fe in K-309 particles relative to bulk targets

s calculated by C0R2 [12]. The second is a breakdown in the method used to fit the background on small particles,

urrently the continuum for the particles is predicted by the modification of Kramers' quation mentioned earlier. This equation was derived for bulk specimens but is in good

greement with the continuum for particles down to 10 um in size. For particles less than

0 um, the predicted continuum is higher than the true value by about five percent. Efforts

re underway to derive a more exact method for the prediction of the continuum emitted by

mall particles. Work is also being done with a Monte Carlo program in an effort to identify those conitions under which the correspondence of the peak-to-background ratio between particles

: nd bulk material of the same composition, equation (3), breaks down. Calculations which

re presented in the paper by Newbury et al. elsewhere in this publication [13], show that

here is a significant deviation in the peak-to-background ratios from particles as compared

o bulk: (1) the anisotropy of the generation of the continuous x-radiation, and (2) diferences in the energy dependence of the cross-section for characteristic and continuous

-radiation coupled with differences in the energy distribution of electrons backscattered

rom bulk and particle targets.

37
Conclusions

The proposed method for the quantitative analysis of particles is designed to obtain

elemental concentrations rather than concentration ratios. The method involves minor

alterations to a conventional microanalysis routine such as FRAME C, and can therefore be

run in real-time (on-line) with a small computer. In addition, the method is, to a first approximation, independent of particle shape and requires no additional input other than

that required for a conventional analysis. The results from the analyses on synthetic and natural mineral particles are in good agreement with the known compositions and are substantially better than the results from conventional methods. In the near future additional corrections will be incorporated to account for the various second order effects. References

[1] Gavrilovic, J., "Quantitative Analysis of Small Particles Using Wavelength and Energy Dispersive Systems in an Electron Beam Instrument," Proceedings of the 13th Annual Conference of the Microbeam Analysis Soc. , Ann Arbor, MI. , June 1978, paper #60.

[2] Armstrong, J. T. and Buseck, P. R. , "Quantitative Chemical Analysis of Individual Microparticles Using the Electron Microprobe: Theoretical", Anal. Chem. , 47, 2178- 2192 (1975).

[3] Small, J. A. et al., "The Production and Characterization of Glass Fibers and Spheres

for Microanalysis," SEM/1978/1, SRM Inc., AMF O'Hare, II. 60666, pp. 445-454.

[4] Statham, P. and Pawley, J. , "A New Method for Particle X-ray Micro-analysis Based on Peak Background Measurements," SEM/1978/1, SEM Inc., AMF O'Hare, II. 60666, pp. 469-

478.

[5] Hall, T. , "Some Aspects of the Microprobe Analysis of Biological Specimens," in Quantitative Electron Probe Microanalysis, K. F. J. Heinrich, ed. , U. S. Government

Printing Office, Washington, D.C., 1968, pp. 269-299.

[6] Fiori, C. E. et al., "An Overview of the Glass Standards Program for Microanalysis at the National Bureau of Standards," Proceedings of the 11th Annual Conference of the Microbeam Analysis Society, Miami Beach, FT., 1976, paper #27.

[7] Myklebust, R. L. and Fiori, C. E. , "FRAME C: A Compact Procedure for Quantitative Energy-Dispersive* Electron Probe X-ray Analysis," Proceedings of the 12th Annual Conference of the Microbeam Analysis Society, Boston, MA. , 1977, paper #96.

[8] Kramers, H. A., "On the Theory of X-ray Absorption and of the Continuous X-ray

Spectrum," Phil. Mag., 48, 836 (1923).

[9] Lifshin, E. , Proc. 9th Annual Conference of Microbeam Analysis Society, Ottawa,

Canada, 1974, paper #53. [10] Green, M. , Ph.D. Thesis, University of Cambridge, Chapter 4, 1962, pp. 60-75.

[11] Yakowitz, H. (Personal communication).

[12] Henoc, J., Heinrich, K. F. J., and Myklebust, R. L. , A Rigorous Correction Procedure

for Quantitative Electron Probe Microanalysis (C0R2), NBS Technical Note 769, U. S. Government Printing Office, Washington, D. C. , 1973. [13] Newbury, D. E. , Myklebust, R. L. , Heinrich, K. F. J., and Small, J. A., "Monte Carlo Electron Trajectory Simulation - an Aid for Particle Analysis, this paper.

38
National Bureau of Standards Special Publication 533. This Publication Originated from a Special Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

Society, Ann Arbor, MI, June 22, 1978. (Issued April 1980)

MONTE CARLO ELECTRON TRAJECTORY SIMULATION - AN AID FOR PARTICLE ANALYSIS

Dale E. Newbury, Robert L. Myklebust, Kurt F. J. Heinrich, and John A. Small

In many problems of interest in scanning electron microscopy and electron probe microanalysis, it is necessary to calculate the distribution of beam electrons within the sample,

as well as the magnitude and distribution of the secondary signals (characteristic and continuum x-rays, secondary electrons, cathodol umi nescence , etc.) generated during interaction.

The technique of Monte Carlo electron trajectory simulation has been widely applied to these

problems [l] 1

. In a Monte Carlo electron trajectory calculation, the processes of elastic

and inelastic scattering which take place during electron interaction are simulated through

the use of mathematical models. The path of an individual electron is calculated through

•the solid in a stepwise manner as the electron undergoes scattering. The distance between

scattering events, the scattering angles, and the rate of energy loss along the path are calculated from realistic physical models. Random numbers are used to distribute the

Lbhoices for the parameters of these models over their respective ranges so as to accurately

..represent the relative probabilities for each process. Because of the large number of possible choices for these parameters and the combinations thereof along a trajectory, the :alculation of a single trajectory does not adequately describe the beam-specimen interaction, figure 1(a). To provide statistically valid results, a large number of trajectories

-nust be calculated. For trajectory plots which give a qua! itative impression of the interaction volume, about one hundred individual trajectories must be calculated, figure 1(b),

vhereas for quantitative results, one thousand to ten thousand trajectories are needed.

The fundamental step of any Monte Carlo simulation which must be repeatedly calculated

jilong the entire trajectory is illustrated in figure 2. With the electron at a point P N

, laving come from a previous point P N

_-|, a scattering event is presumed to take place which

:hanges the direction of the electron to bring it to a new point, P^+ -| - This scattering

I' i?vent is characterized by an angle of scattering, (J), which deviates the electron from its

original path ( p n--|^ p n)> an azimuthal scattering angle, 4>, which defines the plane within

. iVhich scattering occurs, and a distance between scattering events, the step length, S. j'hese parameters are used with an appropriate set of geometrical equations [2,3] to produce

j new set of coordinates (XN+] , Y N+1 , Z N+1

) and the process is repeated. Within this

general framework, the various types of Monte Carlo simulations can be divided into three

:lasses: (a) single scattering, (b) multiple scattering, and (c) hybrid.

1 . Single Scattering

In a single scattering simulation, an appropriate scattering cross section is employed

vhich gives the probability for discrete scattering events. Since most of the angular

deviations greater than 0.5° occur as a result of elastic scattering, an elastic scattering

?;ross section such as the total (relativistic) [4] Rutherford scattering cross section is employed: Figures in brackets indicate the literature references at the end of this paper.

National Bureau of Standards Center for Analytical Chemistry Washington, D. C. 20234 Introduction - Overview of Monte Carlo Simulation Techniques

Types of Monte Carlo Simulations

39
Figure la. Monte Carlo electron trajectory simulation. Target: iron; beam energy:

20 keV; beam diameter: 10 nm; 5 trajectories.

N-1

where ac is the total cross section ( rx— ), Z is the atomic number, E is the electron"^?)

beam energy (keV), m

Q

is the electron rest mass, c is the speed of light, (m

Q

c * 511 keV) and a is a screening factor [5]: a = 3.4xl0"

3 Z°- 67/E (2)

42
which describes the effect of orbital charges on the electrostatic field of the nucleus.

From the total cross section, a mean free path between scattering events, A, can be calculated:

(3) where A is the atomic weight (g/mole), N fl is Avogadro's number (atoms/mole), and p is the

3 density (g/cm ). Since the value of A represents a mean free path, the particular value of

the step length to be used in any step is taken from a statistical distribution about this

mean [4]:

S = -A log | R | (4) The scattering angles are determined from the differential form of the cross section:

2 Wi= 5-21X10" 21 ^ < ' + — 2 )2 A 2

< 5 > " I 1

E + 2m

Q c^ (sin2 |

+ a)

1

Given a probability distribution function, f(x), where for example f(x) can be the scattering cross section a(8), a function can be generated which relates a particular value of x to

a particular random number R, where 0<R<1 [2]:

/ f(x)dx/ / f(x)dx (6)

In the case of the scattering angles, the ratio of the differential cross section to the

total cross section can be integrated over all scattering angles to generate an appropriate

function for selection of the scattering angles by random numbers: £lM d, (7a) °E

rfhich leads to: cos <(> = 1 - [2 R/(l + a - R)] (7b) *here R is a random number 0 < R < 1. The azimuthal scattering angle, t|i, has an equal

•probability at all values, and it can therefore be found from a simple equation:

4< = 2nR (8)

Thus, with the electron at a point P^, having come from a point P^_-| , a set of scattering

parameters (S,4>, and can be calculated. These values are employed with the appropriate

geometrical expressions to obtain the new point, [2,3]. Energy loss during travel through the specimen is usually approximated by use of the

iethe formula for continuous energy loss:

4... - . - (9)

43
where e is the electronic charge and J is the mean ionization potential [5]. The energy

loss AE along the path segment AS, is: AE = AS • dE/dS (10) The single scattering form of the Monte Carlo simulation gives the most detailed

information on the electron trajectory, since the step length of the calculation is almost

identical to the mean free path. In addition, some workers have included a treatment of inelastic scattering as a discrete process of energy loss rather than using the continuous

energy loss approximation [6]. While the single scattering approach is the most rigorous,

it is also the most expensive to calculate, requiring up to several thousand repetitions of the basic element p_er trajectory . 2. Multiple Scattering

To reduce the time necessary for a calculation, several workers have used a multiple

scattering approach. In this method, the effects of ten to twenty single scattering events

are approximated by a "multiple scattering" step which, on average, produces the same net displacement and angular deviation as the sum of single scattering displacements within the

step. The step length in a multiple scattering calculation is approximately ten times

longer than that used in a single scattering calculation, which reduces the time for the calculation by about an order of magnitude. While the multiple scattering model has been

found to give good results for flat bulk targets [3], it does not work well for thin films

or small particles where the dimension of the target approaches the step length of the calculation. For such situations, the coarse description of the trajectory by the multiple

scattering simulation is inadequate, and a single scattering procedure becomes necessary.

3. Hybrid Model

To overcome the limitations of the multiple scattering model while retaining most of the calculational speed, a hybrid model was developed which combines elements of both the single scattering and the multiple scattering models [7]. The initial portion of the tra- jectory from the incident energy, EQ

, to an energy of 0.95 E Q is calculated with the single scattering simulation, after which the balance of the trajectory is calculated with the multiple scattering model. The trajectory is thus simulated with small steps and a more realistic model near the surface, and with large steps deeper in the target where high accuracy is less important. This hybrid Monte Carlo model has been found to give more accurate results than the pure multiple scattering model while retaining most of its calculational speed. Monte Carlo Calculations of Particles

In particles with dimensions which are smaller than the interaction volume in a bulk

target of the same composition, loss of electrons can occur from al 1

, surfaces. Transmission

through the particle can take place as well as scattering through the sides and through the surface through which the beam entered. These escaping electrons are collectively called

"backscattered" electrons in analogy to the bulk specimen situation. A description of this electron escape in terms of analytical equations would be difficult. The Monte Carlo elec- tron trajectory simulation, however, is especially well suited to the calculation of electron

tron beam - specimen interactions in particles. The calculated coordinates of each scat- tering point along the electron trajectory can be compared with the function describing the surface of the particle to determine when the electron escapes. Examples of electron tra- jectories within particles are shown in figure 3 where increasing the beam energy incident

on spheres of aluminum leads to penetration of electrons through the entire particle. Applications to X-Ray Microanalysis of Particles

As illustrations of the utility of Monte Carlo electron trajectory calculations for particulate analysis, three applications will be described in detail:

44
45
A. X-ray Emergence Angle Effects

The x-ray emergence angle is defined as the angle above the surface at which the x-rays emerge in the direction of the detector (i.e., in the conventional arrangement of a flat specimen the complement of the angle between the beam axis and the detector axis), figure 4(a). The value of the emergence angle determines the length of path which the x-rays must traverse to escape the specimen and along which absorption takes place. In an electron probe microanalyzer , the emergence angle for both the crystal spectrometers and energy dispersive spectrometer is typically in the range 30-60° for a flat specimen set

normal to the beam. [Such an instrument is thus capable of analyzing a specimen whose

surface is positioned normal to the beam.] In a scanning electron microscope, the energy dispersive spectrometer is frequently attached with the detector axis at a right angle to the beam, which produces for a specimen of surface normal to the beam an x-ray emergence

angle of 0°, Such a detector configuration cannot be applied to the analysis of a flat bulk specimen set normal to the beam. X-ray microanalysis of flat specimens is accomplished in such instruments by tilting the specimen toward the detector to create a sufficiently large emergence angle (figure 4(b)). While this is a satisfactory situation for a flat bulk

sample, tilting does not necessarily produce an adequate emergence angle for a particle

(figure 4(c)). For a spherical particle with the beam directed towards the particle center,

the emergence angle remains effectively 0°, even when the substrate carrying the particle is highly tilted. The degree to which this situation influences the measured x-ray intensity

depends on the size of the interaction volume relative to the particle size. For very small particles, the extra x-ray path length caused by the 0° emergence angle is not significant

(figure 5(a)). When the interaction volume becomes smaller than the particle size, figure

5(b), the added x-ray absorption path length can profoundly influence the measured x-ray

intensity, particularly for radiation of long wavelength. Monte Carlo simulations have been used to calculate the x-ray intensity which is emitted

as a function of particle size for the situations illustrated in figures 4(c) and (d) with

the beam incident at the center of the particle [8]. The intensities have been normalized with respect to the intensity calculated for a bulk substrate under the same conditions.

The calculated response for a low energy x-ray line, silicon Ka (1.74 keV), in an iron matrix is shown in figure 6 for a cylindrical particle. For a 0° emergence angle, a range

of particle size is observed for which the normalized intensity is greater than unity; i.e., the particle emits more x-rays than the bulk sample. For larger particle sizes, the inten- sity rapidly drops off as the effect of the added absorption path length becomes significant.

This behavior leads to an intensity function in which particles of two widely different

diameters emit the same x-ray intensity. To the contrary, for a high emergence angle the x- ray intensity does not fall off at large particle diameter, but it becomes identical with

that observed from a bulk material.

The importance of the proper choice for the x-ray detector orientation in particle

analysis is demonstrated by figure 6. The dependence of the x-ray intensity on the sample geometry should be monotonic with respect to particle size since the intensity is also a complicated function of specimen composition, the determination of which is the analyst's

goal. The sharp drop-off in intensity with increasing particle diameter observed for the 0° angle case would make quantitative analysis unnecessarily difficult and therefore this configuration must be avoided.

B. Particles and Films on Substrates

To produce a specimen which is suitable for the analysis of individual particles, the particles are often dispersed on a massive substrate of a low atomic number material such as beryllium or carbon. Similarly, in order to analyze a material in the form of a thin film

or to create thin film standards, the material must be supported. A massive, low atomic number material can be used for this purpose. Monte Carlo calculations can be useful in understanding the signals observed from particles or films on substrates. The trajectories

of electrons and the signals which they generate can be calculated for the particle and film as well as the substrate. Thus, the case in which an electron penetrates through a particle or film, enters the substrate, and is subsequently scattered out of the substrate

to re-enter the particle or film can be be adequately treated.

46
\ \\ \

Figure 4. X-ray emergence angle in:

a. Solid specimen in electron probe microanalyzer.

b. Solid specimen in scanning electron microscope (detector at a right angle

to beam axis)

c. Particle observed with SEM x-ray geometry.

d. Particle observed with electron probe x-ray geometry.

47
X-ray Detector Particle size less

than 1 pm

(a)

48
49
As an example of such an application, the characteristic x-ray signals emitted from

thin sodium chloride layers on a beryllium substrate have been calculated by Monte Carlo

techniques. Experimental results on similar specimens are reported by Roinel et al. [17] elsewhere in these proceedings. The target was assumed to consist of a matrix of sodium

chloride doped with low levels of magnesium, potassium, and phosphorus, and the specimen

surface was normal to the beam. Films of various thicknesses were considered and the x-ray

intensities per unit thickness were normalized with respect to those calculated for the minimum thickness considered (0.025 mg/cm2

). The observed working curves, figure 7, reveal an initial increase in the relative efficiency of x-ray production as the thickness

increases, followed by a decrease at greater thicknesses. The calculated results are similar for films on a beryllium substrate and without a substrate, except that the increase

in efficiency is more exaggerated for the films without a substrate. The experimental

results in the paper of Roinel et al. [17] do not show the initial increase in efficiency.

On a theoretical basis, the increase in efficiency with layer thickness can be under- stood to occur as a result of elastic scattering. Thus, the electron path through a film of twice the thickness increases by more than a factor of two since elastic scattering causes

the electrons to deviate from their initial path normal to the foil. The additional path

length leads to greater x-ray production and hence, more efficient production per unit

thickness. The eventual decrease which is observed occurs because of absorption effects and

loss of electron energy. An increase in efficiency is observed as a function of x-ray

energy; this can be explained in terms of overvoltage effects.

The deviation of the Monte Carlo calculations from the results of the experiments of

Roinel et al. [17] indicates that the film model is in disagreement with the experimental

situation. Scanning electron micrographs of the microdroplet targets made by Roinel et al

reveal that the specimen is formed of small (M urn diameter) crystallites rather than

being a uniform thin film. If the main effect of mass increase of the specimen is an in- crease of the number of particles of approximately constant diameter, a wide range of linearity of the calibration curve, with gradual decrease of relative efficiency, can be predicted. Such a behavior was, in fact, observed experimentally by the above authors [17]. Monte Carlo calculations are thus useful in understanding the behavior of x-ray signals emitted from complex targets.

C. Calculations of Ratios of Characteristic-to-Continuous X-ray Intensities

It was reported simultaneously by this group [9] and by Statham and Pawley [10] that experimental measurements of the ratio of characteristic x-rays to continuous x-rays of similar energy (peak-to-background ratio) are nearly identical in particles and bulk material

of the same composition over a wide range of particle size. This experimental observation

has been used to develop a scheme for particle analysis based on the ZAF (atomic number- absorption-fluorescence) matrix correction method. The particle analysis scheme has been reported previously in outline form [9,11] and is described in detail elsewhere in this volume [12]. In order to aid the development and refinement of this method, the Monte Carlo technique has been applied to the problem of calculating the peak-to-background ratios for x-rays emitted from particles.

To carry out these calculations, an appropriate cross section is needed for the production of both the continuous x-rays and the characteristic x-rays. Selection and testing of cross sections for Monte Carlo simulations to calculate absolute x-ray yields have not been previously reported, and therefore these topics will be considered briefly.

(1) Continuum generation cross sections Kirkpatrick and Wiedmann [13] have derived algebraic expressions for the production of x-ray continuum intensity as a function of continuum energy and beam energy. Statham [14]

has modified slightly the expressions of Kirkpatrick and Wiedmann over certain ranges and incorporated the resulting cross section in a Monte Carlo simulation. In the present work, we have used the original Kirkpatrick and Wiedmann [13] expressions to calculate the intensity of the continuous x-radiation emitted from bulk and particle targets. Since the generation of continuous radiation is related to the direction of electron travel, the

50
51
anisotropic form of the continuum cross section has been used. For comparison purposes, the

cross section obtained when the emission is assumed to be isotropic has also been calculated.

The correspondence of the calculated continuous spectrum derived from the anisotropic

cross section with that measured for a bulk target is found to be quite good. Our calculated and experimentally determined continuum spectra for titanium are shown in figure 8. The calculated spectrum has been corrected for absorption in the sample and for absorption

in the beryllium window and silicon dead layer of the energy dispersive spectrometer. Similar correspondence between calculation and experiment has been found for bulk targets of copper and gold. These studies suggest that the technique for calculation of the continuum

spectrum is satisfactory for the present studies.

2. Characteristic X-ray Emission Cross Section

In contrast with the situation for the continuous x-rays, the calculation of the inten- sity of characteristic x-rays generated in the sample is somewhat less satisfactory. A number of expressions for the cross section are available in the literature [15]. These

have the form

. -

C

l Z

nl C

2

< C

3

U > . H ? Cr

EcC4 (U+C5

) where Cj. = 6.51x10 20 cm2 keV2 (where C x is ne4

, with e the electronic charge), is the number of electrons in the shell with critical ionization energy E c (keV), U is the over- voltage (U = E/E

c

, where E is the energy of the electron), and C 2 , C 3 , C 4 , C 5 , and C 6 are constants with different values depending on the choice of cross section model. By setting

some of these constants equal to unity, all of the models can be realized. Lifshin et al

[16] recently reported experimental values of the total characteristic intensity generated

in bulk, pure element targets as a function of overvoltage. We have calculated the total characteristic intensity predicted by the Monte Carlo simulation for similar sample and beam conditions with several different choices of expression for the ionization cross section. The values are compared in Table 1. In general, for the cross sections tested, no com- pletely satisfactory fit to the experimental data is obtained. Table 1. Characteristic x-ray generation (photons/electron)

E = 20 keV. Monte Carlo Calculations

Cross Section (xlO ) (xlO ) Fabre 0.80 2.38 Bethe (Mott and Massey) 1.54 2.84 Green and Cosslett 0.981 Experimental Measurements

Lifshin 1.53 3.36 Green - 2.4

52

For the particle calculations, ratios of characteristic intensities are employed, and therefore the effects of the choice of constants which regulate the absolute intensity of

the calculated characteristic x-rays tend to cancel within the accuracy required for the present case. Similarly, the choice of the stopping power has little effect in the case of calculating ratios. Several different models for cross sections for characteristic x-ray

production have been examined in the following work, and the results for the ratios have been found to be essentially independent of the exact model.

3. Comparison of Peak-to-Background Ratios in Particle and Bulk Material

To test the experimental observation that the peak-to-background is similar in particles and bulk material, a hypothetical target of the same composition as NBS Glass K-309 was

considered. This composition has the advantage of providing characteristic x-ray energies

spanning the range 1.5 - 6.4 keV and resembles natural silicate particles. Peak-to-background (P/B) calculations were made for the bulk material and for spherical particles of various diameters. All Monte Carlo calculations were made with a beam with a constant

current density of the same size as the particle. This condition corresponds closely to the situation achieved experimentally with raster scanning of particles [9]. The results for a particle of 6 urn diameter, reported as a ratio of (P/B)p

art ^ c

-j e to C P/B

)^ u ^ ^ , are given in Table 2. For this 6 urn diameter particle, the (P/B) values at 20 keV are found to be quite similar to that of the bulk, with a value slightly higher by 2-6 percent for the particle.

The ratios of peak intensities emitted by the particle and bulk, also listed in Table 2, show much larger deviations, with low energy lines actually being emitted with greater

intensity from the particle than from the bulk.

Table 2. Comparison of 6 ym particle to bulk (K309) ^B )particle

P partic1e "(^bulk P bulk

A1 1.03 1.12

Si 1.00 1.06

Ca 1.02 0.86

Ba 1.06 0.86

Fe 1.05 0.87

E - 20 keV

oemergence angle = 40° Note: Calculated with Monte Carlo simulation with beam

at the center of the particle.
(a) Effect of Particle Size on (P/B) Ratios When the ratio of (P/B) ratios is calculated as a function of particle size (Table 3),

i systematic deviation is observed. The (P/B) ratio of the particle increases relative to

.hat of the bulk material as the particle size decreases. This increase in the (P/B) ratio

«f the particle occurs over the entire energy range which was studied.

Table 3. Calculated values of Peak/B 9( spnere ) / Peak/Bg^

for K309 glass at 20 kV (emergence angle = 40°) Diameter (urn) Element

Line Energy

keV 6 3 2 10.5

Al 1.48 1.03 1.10 1.21 1.39 1.51

Si 1.74 1.00 1.05 1.14 1.29 1.38

Ca 3.69 1.02 1.10 1.22 1.43 1.54

Ba 4.46 1.06 1 . 14 1.30 1.55 1.67

Fe 6.40 1.05 i.n 1.31 1 .54 1.67

Electron range at 20 kV is approximately 3.1 urn.

(b) Effect of Shape Calculations of the (P/B) ratio have been made for both spheres and cylinders of nfinite length, of two different diameters, as compared to bulk material (Table 4). The

P/B) values for the cylinders do not show as large a deviation from bulk values as do the

Dheres. This behavior occurs because the cylinder axis is effectively infinite as in a ulk specimen.

55
Table 4. Comparison of spheres (SPH) and cylinders (CYL) of glass K309 at 20 kV (emergence angle = 40°)

Peak/Bgpartide

Peak/B9

B ulkDiameter (pm)

Element

Line Energy

keV SPH CYL SPH CYL

Al 1.48 1.03 1 01 1.39 1.21

Si 1.74 1.00 0.98 1.29 1.14

Ca 3.69 1.02 1.00 1.43 1.24

Ba 4.46 1.06 1.02 1.55 1.31

Fe 6.40 1.05 1.01 1.54 1.33

(c) Effect of Beam Energy

The systematic deviation in the (P/B) ratio of the particle is a function of the energy

of the incident beam, and hence the range of the electron in the target. Calculations for three different particle sizes at incident beam energies of 10 and 20 keV are given in Table 5. A reduction in the beam energy by a factor of two reduces the deviation from bulk behavior by at least a factor of two.

Effect of beam energy on peak-to-background ratios

(K309 glass, emergence angle = 40°)

Peak/Bg, Peak/Bg,Sphere

'Bulk Diameter (pm)

1 Element

Line Energy

keV 20 kV lOkV 20kV lOkV 20 kV lOkV M 1.48 1.10 1.01 1.39 1.06 1.51 1.21

Si 1 . 74 1.05 1.01 1.29 1.05 1.38 1.18

Ca 3.69 1.10 1.01 1.43 1.08 1.54 1.27

3 a 4.46 1. 14 1.01 1.55 1.11 1.67 1.33

Fe 6.40 1.11 1.01 1.54 1.08 1.67 1.31

56
Origin of Deviation

The deviation in the (P/B) ratio of the particle from (P/B) ratio of the bulk apparitly occurs for the following two reasons:

1. Anisotropy of Generation of Continuous X-rays

The generation of x-ray continuum along a segment of electron trajectory is anisotropic

icause it is related to the direction of flight of the electron and is peaked in a forward

rection. In a bulk target, the effects of elastic scattering lead to a randomization of

<e directions of flight of the beam electrons, so that although the generation of continuum

anisotropic along an individual electron trajectory, the generation averaged over the

itire interaction volume appears nearly isotropic to an external detector. -In a small

.rticle or thin film, the effects of elastic scattering are reduced when the dimensions

come significantly less than the bulk interaction volume. The trajectory segments are re parallel, so that the anisotropic effects are not cancelled by randomization. Moreer, this anisotropy also explains the behavior of (P/B) .. , /(P/B). ,, as a function parti c I e uu l k beam energy. At high beam energy, the cross section for elastic scattering is reduced,

e mean free path and total range increase, and the trajectory segments in a small rticle become more parallel (figure 3). The anisotropic generation effects are thus less bject to randomization by elastic scattering at high energy as compared to low energy. This hypothesis can be tested by comparing the calculated behavior of ( p / B ) part j c i J

I ^bulk as a f ur,ct

',on °f Particle size and considering both anisotropic and isotropic

I ntinuum generation. In figure 9, this comparison has been calculated for three different

ements (Ca, Fe, and Al) in K-309 glass spheres referenced to bul k material . In all cases,

can be seen that about half the deviation of ( p / B ) part

c 1 e fr0m ^ P//B ^bulk 1S re1ated to

e anisotropy of the continuum generation.

2. Difference in Cross Sections for Characteristic and Continuum Rays

The remaininga portion v of the deviation from bulk (P/B) , occurs as a result of the values mplicated relation between the cross sections for characteristic and continuum cross

ctions and the energy spectrum of electrons emitted from the particle. The cross sections

r characteristic and continuum x-radiation as a function of electron energy are shown in gure 10. As the electron energy is reduced and approaches the x-ray energy of interest,

e cross section for characteristic x-ray production decreases while the cross section for

ntinuum x-ray production increases. Beam electrons which have lost sufficient energy to

ach the range of a few keV above the x-ray energy of interest make contributions prinipally to the continuum and not to the characteristic x-radiation. These lower energy

ectrons therefore tend to reduce the peak-to-background ratio. In a particle, the effect

electron penetration is to allow the escape of high energy electrons before chey have the portunity to lose large amounts of energy. The energy spectrum of electrons backscattered

om a particle as calculated with our Monte Carlo simulation is seen to be more sharply

aked at a higher fraction of the initial energy than that from the bulk specimen (figure

). Thus, in a particle, most electrons do not reach the lower energies necessary to ificiently create continuous x-rays of the energy of interest. The (P/B) ratio for the

rticle is therefore expected to be higher than that for the bulk since less continuum is eated relative to the characteristic emission. This effect increases as the particle size

comes smaller.

The deviation of (P/B) .. , from (P/B). therefore originates from two effects, particle y bulk a

e anisotropy of continuum emission and the difference in the relative behavior of the

oss sections for continuous and characteristic x-ray generation. Both of these effects

e a function of the particle size as a fraction of the interaction volume in the bulk

terial. The deviation of (P/B)

1 from (P/B)

b ^ should thus have the form

57
K309 SPHERES 20 kV AO

0 TOA

a=anistropic continuum

Diameter (Mm)

Figure 9. Monte Carlo calculations of the peak/background ratio emitted from a spherica particle (normalized by (P/B) for a bulk target) as a function of particl diameter. Both the isotropic and the anisotropic continuum cases are consid

ered. Target: K-309 glass; beam energy: 20 keV; x-ray emergence angle 40°. 58
Continuum Cross Section

uojpes ssojq onsuepDJDqo
60
C/fOhnit ,diameter particle N

. f ( r ), diameter < range. (P/B) ,

1 v

* range, 'particle

a first approximation, the behavior is similar for all x-ray energies of interest, and

erefore one factor can be used to adjust the rticle value measured from the actual

>ectrum for the deviation: p rfp/B^ l< i = r^p/B^ i ; particle J ,anisotropy. L ^ ^particle J (measured) x F ^energy

can be observed by examining the form of the curves in figure 9, the correction F is osely approximated by the function:

«re X = D/Rg, D is the particle diameter, and Rg is the Bethe range in the bulk material. r the example of the K-309 glass in figure 9, the values of the constants are A = 0.75,

= 2, and C = 1. The generality of this equation as a modification to the particle

alysis scheme is currently being tested. Summary

The technique of Monte Carlo electron trajectory simulation forms a valuable aid to rticle analysis. The cost of computation makes the direct application of the Monte Carlo

mulation to a particular analysis problem justifiable in only a few cases. The principal

lue of Monte Carlo simulation is as a tool for the development of direct computational

hemes for particle analysis. The Monte Carlo simulation can provide calculated data where

perimental data are difficult to obtain. In addition, the Monte Carlo simulation can equently be employed to separate effects, such as the influence of the anisotropy of the ntinuum x-ray emission in the present studies, which would be virtually impossible to parate experimentally from other factors which effect the x-ray generation. In applying

e Monte Carlo simulation, it is important to remember that the calculated results are eatly influenced by the choice of scattering models, mean ionization potential, and other

rameters. It is therefore necessary to test the cal cul ational scheme as completely as ssible before confidence can be placed in the results of the simulation.

ri f

61
References

[1] Heinrich, K. F. J., Newbury, D. E. , and Yakowitz, H. , eds. , Use of Monte Carlo Calculations in Electron Probe Microanalysis and Scanning Electron Microscopy, NBS (U.S.),

Spec. Publ. 406 (Washington, D.C. 1976).

[2] Berger, M. J., Methods in Computational Physics, Vol. 1, Alder, B. , Fernback, S. , and Rothenberg, M. , eds. , Academic Press, New York (1961).

[3] Myklebust, R. L. , Newbury, D. E. , and Yakowitz, H. , Use of Monte Carlo Calculations in Electron Probe Microanalysis and Scanning Electron Microscopy, NBS (U.S.), Spec. Publ. 406, 105 (Washington, D. C. 1976).

[4] Reimer, L. and Krefting, E. R. , Ibid., 45. [5] Bishop, H. E. , Ibid. , 5. [6] Shimizu, R. , Kataoka, Y. , Ikuta, T. , Koshikawa, T. , and Hashimoto, H. , J. Phys. D: Appl. Phys. 9, 101 (1976).

[7] Newbury, D. E. , Myklebust, R. L. , and Heinrich, K. F. J., in Eighth International Conference on X-ray Optics and Microanalysis, Ogilivie, R. and Wittry, D. , eds., (Boston, MA 1976) 27A.

[8] Myklebust, R. L. , Newbury, D. E. , and Heinrich, K. F. J., Proc. 11th Annual Conference, Microbeam Analysis Society (Miami, FL 1976) 23A. [9] Small, J. A., Heinrich, K. F. J., Fiori, C. E. , Myklebust, R. L. , Newbury, D. E. , and Dilmore, M. F. , Scanning Electron Microscopy, Johari , 0., ed. , Vol. 1, 445 (1978).

[10] Statham, P. J. and Pawley, J. B. , Ibid, 469. [11] Small, J., Heinrich, K. F. J., Fiori, C. , Newbury, D. , and Myklebust, R. , Proc. 13th Annual Conf. Microbeam Analysis Society (Ann Arbor, MI 1978) 61. [12] Small, J., Heinrich, K. F. J., Myklebust, R. L. , and Newbury, D. , this volume.

[13] Kirkpatrick, P. and Wiedmann, L. , Phys. Rev., 67, 321 (1945).

[14] Statham, P. J., X-ray Spectr. , 5, 154 (1976).

[15] Powell, C. J., Use of Monte Carlo Calculations in Electron Probe Microanalysis and Scanning Electron Microscopy, NBS (U.S.), Spec. Publ. 406, 97 (Washington, D. C. 1976)

[16] Lifshin, E. , Ciccarelli, M. F. , and Bolon, R. B. , 12th Annual Microbeam Analysis

Society (Boston, MA 1977) 104A. [17] Roinel, N. , Champigny, M. , Meny, L. , andHenoc, J., this volume.

62
tional Bureau of Standards Special Publication 533. This Publication Originated from a ecial Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

iciety, Ann Arbor, MI, June 22, 1978. (Issued April 1980)

QUANTITATIVE CHARACTERIZATION OF PARTICULATES BY SCANNING AND HIGH VOLTAGE ELECTRON MICROSCOPY

R. J. Lee and R. M. Fisher

U. S. Steel Corporation

Research Laboratory Monroeville, PA 15146 Abstract

The development of a minicomputer-based automatic image analysis

(AIA) method for scanning electron microscopy (SEM) now makes it possible

to determine the size, shape, and composition of a large number of particles in a very short time. Thus, it is feasible to obtain statistically significant estimates of the bulk concentration and size distribution of specific classes of particles in powders, airborne

dusts, and other particulate samples. This new technique provides an important link between bulk measurements by sieving and other methods and detailed studies of the morphology, internal structure, and composition

of individual particles. Introduction

"Analytical" microscopy is used to describe studies in which one or more of the ailable signals is recorded and interpreted in detail for a small number of particles or

tatures [1.2] 1

. However, there is a large class of problems for which it is desirable to uantitati vely" characterize a large number of particles. Powders, pigments, and airborne

sts, as well as inclusions or second phases in steels, minerals, or coal, are just a few

the many examples of particulate problems encountered in quality-control or processnitoring programs. Very often the differences between samples or batches are rather

btle and can only be detected when statistical criteria are used to compare descriptive

rameters such as size, shape, and area. In this case, the measurement and analysis of

veral thousand particles may be required if the sample contains a mixture of several fferent types of particles having different size distributions.

The quantitative particulate analysis procedures to be described include three

stinct phases: (1) automated measurement of particle parameters amenable to rapid

alysis, such as size, shape, and composition, and assignment to type classes [3-6];

) verification of the homogeneity and specific identity of the particle type comprising

e class [7]; and (3) detailed analysis of the morphology, composition, crystal structure

nd occurrence of defects) of particles belonging to a specific class of interest [8].

e ultimate goals of these methods are commensurate with those of image analysis and croscopy in general - to maximize the information obtained per particle while reducing the mplexity of the procedures, and to minimize the time required for analysis. Automatic Image Analysis by Scanning Electron Microscopy

Figure 1 is a photograph showing a scanning electron microscope, Tracor Northern

ftware-based x-ray analyzer, LeMont Scientific digital beam scan controller, display

rminal, floppy disk data storage, and other computer peripherals comprising the SEM-AIA

cility. A schematic diagram of the signal and information flow in the automatic image

.igures in brackets indicate the literature references at the end of this paper.

63
Figure 1. Scanning electron microscope equipped for automatic image analysis as installed in the USS Research Laboratory. analysis mode is shown in figure 2. The minicomputer shown at the top of the figure directs

the digital beam-control system for real-time picture-point by picture-point analysis (up to 4096 by 4096 matrix) as described below. The energy-dispersive spectrometer (EDS) and software-based multichannel analyzer shown

at the bottom of the illustration are used for x-ray microanalysis and classification of features. This system makes use of the same input/output and mass-storage devices as the minicomputer that controls the electron beam, which permits simultaneous collection of size, shape, and composition information from image features. A teletype (TTY) high-speed

printer, magnetic-tape cassette, and dual floppy disk (not shown) are used as input/output

and mass-storage devices.

64
65
The time sequence of events comprising the automatic image analysis procedure is illustrated schematically in figure 3. The digital scan generator (DSG) moves the incident

electron beam in a stepwise fashion over the specimen surface. If the signal received by

the electron detector is close to background level (no image contrast), the computer selects

the next (x,y) coordinates in the scan sequence and moves the beam to the next picture

point [9]. As illustrated in figure 4, when image contrast above a preset threshold is encountered (or below if adjusted for negative contrast) an auxiliary subroutine drives the

beam in a preset pattern to determine the dimensions and shape of the feature (such as an inclusion particle).

BEAM-CONTROL

SYSTEM LOCATES

PARTICLES

BEGIN DATA TRANSFER TO NS-880

'-RAY SPECTRA STORE IMAGE

DIMENSIONS IN h~

OBJECT VECTOR

TERMINATE DATA ACQUISITION ON THE BASIS OF COUNTS.

TIME OR PARTICLE SIZE

DETERMINE MAJOR- MINOR INTENSITIES AND RATIOS

SELECT/REJECT/CLASSI FY

SIZE/SHAPE/COMPOSITION

CREATE OBJECT VECTOR FOR EACH PARTICLE

RETURN CONTROL

TO BEAM- CONTROL SYSTEM

OBJECT VECTOR

SIZE SHAPE

0-4 PARAMETERS

SIZE CLASS

1-20

Figure 3. Block diagram of Flextran programs for computer-controlled size measurement,

chemical analysis, and classification of image features.
Figure 4. Illustration of use of threshold setting to trigger and terminate

digital scan drive.

The preset pattern shown in figure 5 consists of four pairs of diagonals; each

liagnol is terminated when the signal falls below the reference voltage. The pattern is repeated twice, once to locate the feature and once to determine the lengths of the diagonals

.hrough the centroid. The maximum, minimum, and average diagonals are stored; the centroid

s retained and used in a portion of a subroutine designed to prevent double counting.

Figure 5. Illustration of preset pattern followed in AIA particle size and shape measurements.

As shown in figure 5, a low picture-point density is used in searching, thereby

jillowing a large area to be analyzed per unit time. Simultaneously, the precision of the

leasurement is maintained by using a higher point density (the on-point density) once a

: eature is located. This example is for an off-point density of 50, and an on-point

tensity of 200. Once the maximum, minimum, and average diagonals of the feature are

tetermined and stored, the minicomputer returns to the search mode, or, alternatively,

jositions the beam at the centroid of the feature and signals a second minicomputer to nitiate EDS x-ray analysis. Beam-control programs are written in an interactive Flextran and supplied by LeMont

Scientific. One was written for particle-size measurement and plotting size-distribution

lata. The second was written to measure the size and diameter of long straight features, a leasurement not satisfactorily performed with the preset-diagonal measurement.

Basically, the user specifies the magnification and the off-point and on-point

tensities used in the search and analysis portions of the program, the portion of the image

~.Q be analyzed, and the type of picture-point matrix - (n x m), where n specifies the
horizontal off-point density, and m specifies the vertical off-point density. At the end

of each frame or scan of the image the operator can ask for a new frame, interim plots ofi the data, or new analyses.

The signals used for imaging, that is, the secondary (SE), backscattered (BSE), or transmitted (TSE) electron intensities can also be used for image analysis. The SE image, with a resolution of MOO A, is useful for analyzing free particulates on a flat substrate. 9 The TSE signal, with a resolution of 75 A, is good for fine powders and air samples supported by a thin film of carbon. The BSE is especially useful for analysis of particles

in a matrix or on a substrate which has a significantly different mean atomic number, lid The micrographs in figure 6 were taken with a BSE detector especially designed for AIA for aA

resolution of 200 A and show mixed A1 2 0 3 and MnS-Al 2 0 3 inclusions in steel. In this case,. AIA is carried out in two steps: first with a low threshold setting to measure the total inclusion content and size distribution, and then, with the higher setting as illustrated

to restrict the analysis to "brighter" A1 2 0 3 component.

(a; 10,000X (b)

ELEMENTAL ANALYSIS

(C)

Figure 6. High resolution BSE micrographs, (a) MnS-Al 2 0 3 inclusions; (b) monitor oscil- loscope trace of BSE signal as the beam traversed a dual-phase inclusion. Extent of feature is defined by portion of the signal above lower threshold (LT) value; (c) block diagram of x-ray classification scheme.

68
Measurements of high atomic number (Z) particles on a low-Z substrate made with any

\:f the three signals agree very well with each other within the limits of measurement by

"and (~1 00 A at 1000X magnification). Measurements of low-Z features in a high-Z matrix,

jch as MnS particles in three percent Si steel, tend to be larger (~0.1 urn) when made with

5E than when made with SE. This appears to be the result of edge effects and the greater

?pth from which the BSE signal is extracted.

The results of tests of the reproducibility of measurements made with AIA are :ummarized in Table 1. A single MnS particle in a polished section of silicon steel was

: jasured repeatedly at four magnifications. The mean and standard deviations were computed

)r the maximum diameter, minimum diameter, and average diameter. The accuracy, as ^presented by the standard deviation, is seen to improve only slightly at higher magnifica-

! ion. This is an important result because it is more efficient to scan at low magnification

: ) increase the number of particles encountered in a single field of view. Table 1. Reproducibility of AIA measurements made on the same particle at four magnifications. Average Diameter Maximum Diameter

Number of urn urn Aspect Ratio Maximum Minimum

igni fi- Measure- Standard Standard Standard Diameter Diameter ction ments Mean Deviation Mean Deviation Mean Deviation urn urn 1000 11 0.73 0.03 0.88 0.05 0.60 0.083 0.960 0.480

2000 14 0.74 0.05 0.83 0. 11 0.80 0.136 1.050 0.540

4000 12 0.73 0.02 0.83 0.07 0.81 0.080 0.960 0.600

8000 12 0.72 0.01 0.84 0.02 0.77 0.027 0.870 0.630

Illustrative Applications

The numerous applications of SEM-AIA may be grouped into four general categories:

||) single-inclusion type in a solid matrix for which very accurate size and distribution

ita are of major interest (for example, MnS inclusions in steel); (2) mixtures of

iclusion types in a solid matrix, for which quantitative information about both the

lundance and the sizes of the various types are of primary interest (for example, mineral mstituents in coal); (3) single-component powders, for which mean size and distribution

'e sought (for example, pigments); (4) multiple-component dusts, for which phase identificaon as well as size and abundance of the various components are required (for example,

ispended particulates in air samples). An example of each of these categories is described

i brief to illustrate salient features of AIA techniques.

icl usions i_n Steel

. The size and nature of inclusions are important factors when interpreting or predicting

ie properties of steels or other metals. Although this subject has been investigated

tensively by optical and electron microscope techniques, many problems require a level of

[ xuracy beyond that which can be achieved by conventional methods. For example, informaon about changes in size of inclusions in steels during prolonged heating at elevated

mperatures is of considerable value for predicting the properties of finished steels as

11 as for basic studies of the growth mechanism. A typical computer printout of an A-SEM analysis of MnS inclusions in a three percent Si steel is shown in figure 7. The

ta can also be listed on a particle-by-particle basis if desired.
Nil or ICLfj OF THIS TYPE 1024

MKA.'I AVE DIAMETER 0.76

STAND ARD DE VI ATION OF AVE D IAMETERS

0. 10 0. 19 0-50

I. ,5 Total area percent ioo.oo variable plotted ave

mo of microns per d iv. 0.10

scale factor 4 rel. freq. plot

Figure 7. Example computer printout of an automatic image analysis

of MnS inclusions in steel. The results of analyses of a series of samples are presented in Table 2 and also plotted in figure 8. The metal lographic effects of heating time and temperature, although

significant, are not large and could not be determined by conventional electron-microscope

methods [10]. An example involving duplex Al 2 03 -MnS inclusions is shown in Table 3. It is, apparent that the effects of the special treatment could not be detected by conventional

quantitative television microscopy, although they are quite evident by AIA-SEM analysis.

Table 2. Isothermal growth of MnS precipitates in three percent silicon

steel as a function of annealing time and temperature. Average Diameter of MnS Particles, urn Temperature Time, hours

°C °F 1/2 1 4 16 24 64 240 850 1562 950 1742

1000 1832

1100 2012 0.76

0.38 0.43 0 44 0 46 0.47 0.43 0.45 0 49 0 48

0.46 0.50 0 53 0 63 0.76 0.80 0.82

fell

70
Figure 8. Illustration of AIA measurements of the growth

of MnS inclusions in Fe-3 percent Si steel.

Table 3. Weight percent A1 2 03 and MnS in 4027 steels determined

by automatic image analysis (AIA). AIA ATjOl ~MnS~ QTM Treated 45.22 41.45 0.12 - 0.14 Untreated 77.30 11.82 0.12 - 0.14

ineral Constituents i_n Coal . Most of the coal mined in the U. S. contains between 10 and 20 weight percent mineral

atter. Some of this inorganic material can be removed by comminution and washing, but the emainder is so intimately associated with the coal macerals that its complete removal is ot feasible . This residual mineral matter affects the properties of coke after carbonizaion of the coal, and the nature of ash and slag formed during combustion. Detailed studies

If the mineral species, abundance, and size distribution of the included minerals in coal

re needed to develop a basic understanding of their role in specific applications and

ermit optimum use of various coals. SEM-AIA has proven to be a valuable adjunct to other analytical techniques such as

ptical petrography, chemical analysis, and Mossbauer spectroscopy, since it provides mineral dentification and size information on a particle-by-particle basis. Some 29 categories of

ineral phases were established on the basis of the actually observed x-ray intensities of

'he 10 most common elements (Na, Mg, Al , Si, S, CI, K, Ca, Ti , Fe) found in coal ash. ifteen categories corresponded to common minerals, another nine represented mixtures of

wo or more common minerals in which mineral grains formed a compound particle, and the emainder are various mixed but unidentified mineral constituents. A computer printout of

he size and volume distribution of illite (clay) in a Pittsburgh Seam coal is shown in igure 9. A modification of the classical normative analysis scheme using chemical,

ossbauer, and SEM-AIA data was used to interpret the results of all the analyses as preented in Table 4. Further details of this procedure can be found in the references

i ited [11,12].

71
Figure 9. Computer printout of AIA analysis of a selected

mineral constituent in a coal sample.

Table 4. AIA analysis of mineral constituents in coal. Illinois Pittsburgh Pocahontas Gholson

#6 Seam Seam, PA Seam, WV Seam, AL

Mineral SEM NORM SEM NORM SEM NORM SEM NORM

Silicates 83 75 59 76 87 74 26 27 Carbonates 0 3 6 5 5 11 71 66 Pyrite 15 15 26 19 2 3 2 7 Sulfates 1 5 6 ID 2 ID <1 OD Other 0 2 0 2 3 3

' 0 1

Single Component Powders . Knowledge of the particle size distribution in fine powders produced by grinding or other processes for pigments, catalysts, or other application is frequently required for control or specification purposes. Sieving is commonly used to measure size distributions

of particles greater than 40 micrometers in diameter, but a relatively large amount of sample material is required and the quality of sieves deteriorates with use so that the tolerances are degraded. SEM-AIA provides a very attractive alternative procedure. Scanning electron micrographs of the -400 mesh and +400-325 mesh fractions of a dispersed industrial catalyst are shown in figure 10. Histographs of the diameters of these two fractions, shown in figure 11, are essentially normal distributions with mean
-400 Mesh +400 -325 Mesh

Figure 10. Typical micrographs of two size fractions obtained by sieving.
particle diameters approximately equal to the nominal sieve sizes, and 95 percent of th particles within ± two standard deviations as expected. However, closer examination o results brings out several pertinent points relating to the accuracy of sieving techniques

The weaving procedures used in the manufacture of screens cause the dimensions of the siev openings to vary somewhat, resulting in a range of openings in individual sieves and variation in average opening from sieve to sieve. ASTM specifications for U. S. standar

test sieves in the SEM range allow a maximum variation of average opening of ±6 percent fo sieve sizes Nos. 80 and 100, and ±7 percent for Nos. 200, 325, and 400. In addition, not mor

than 5 percent of the opening shall exceed the nominal opening by more than 30 percent fo the large sizes and 45 percent for the fine-mesh screens.

To check on the variability of a typical laboratory sieve, shadow "replicas" of th sieve were prepared by evaporating gold onto a carbon disk from a point source. A SE micrograph of the replica is shown in figure 12, and the deviations from square opening

are quite evident. A cumulative frequency plot obtained by AIA on such a sieve replica i shown in figure 13. The maximum diameter of 67 urn is close to specification; however, th fraction oversize, i.e., more than 57 urn, is appreciably greater than the 5 percenj prescribed. It is clear that the accuracy of sieve testing could be improved appreciablj

by calibrating each standard screen by AIA to determine calibration and quality parameters. J minimi aaasaaaaa aaaaaaaB

BRiiasaifi •l

••a

iflflaaBBasfl (If"

ILIII.JILJ1L.III1

~aaaaa«aBaaaBaaaBi .aafci ^•i laiaafliBsaiaaflaaal ••mi aiaaaiaaaiaiaiaai

laaaaaBaaBaaaaaaai .iaaaiaaaiaiaaaii

•«»• ia>«aaaaaa«aaB«aai i.aB»»«»"»«2"""£„

«

•aBaaaaaaaBeaai

iaB»a»«aaaaa:.Baaai B>iBBBaflSa>flB«ai iiBP««Bf"«!"""SSSS

Figure 12. Scanning electron micrograph of a gold shadow "replica"

of a used standard test sieve.

74
HO OF MICROMS PES DIV. 3.00

SCALE FACTOR 2 CUM FriEO. PLOT

10 20 30 40 50 60 70 80 90 100

50ym- 33.00[ 36.001

39.00[

42. 00

67um-45. 00 [ 4d.00[

5 I . 00

54.001

57.00.1 60.00E

Figure 13. AIA derived cumulative frequency plot of opening size

on a used standard test sieve.

The results of sieve and SEM-AIA analysis of a sample catalyst powder are summarized

in Table 5. Some 3000 particles were analyzed by AIA, and to make a comparison on the basis

)f sieve sizes it was necessary to assign each to a specific sieve fraction according to ninimum diameter rather than average diameter (minimum and maximum diameter are determined

)y AIA and average diameter is computed for each particle). Presumably the generally

ellipsoidal particles pass through along their major axis. Table 5. Comparison of size distribution of phthalic anhydride catalysts obtained by automatic image analysis and sieving. Weight Percent

Mesh Opem nq Spec , urn SEM SIEVE

-400 38,

a 48,

b 57

c 2 3 -325 45 57, 66 4 7 -200 75, 91, 103 8 3 -100 150 174, 192 48 50

- 80 180 207, 227 17 13

- 60 250 283, 306 21 20

a Nominal size.

b Not to be exceeded by five percent of the openings.

c Maximum. 7 c
Particle sizing by SEM-AIA is limited to particles greater than about 0.1 urn diameter

and isnot very satisfactory for particles much above 50 urn. Clearly, the technique is most

useful for the small sizes for which sieving cannot be used and other available techniques

are less straightforward. An example of determining a size distribution curve by combined

SEM-AIA and use of a Sonic Sifter is shown in Table 6. The -325 sieve fraction was ana- lyzed by SEM-AIA and the +325 portion was sized by means of an Allen-Bradley model L3P Sonic Sifter. This device combines oscillating air and mechanical movement to determine

sieve fractions methodically. As can be seen, significant differences occur within the

fine particle fraction which would be difficult to observe by other techniques. Table 6. Size measurements of catalyst particles. Cumulative, Weight Percent Particle Size Sample A Sample B SEM

a

5 urn 1.0 0.3

10 6.4 1.5

15 13.5 4.3

20 20.0 10.4

35 29.0 20.0

50 35.0 27.3 SIEVE

13 325- (44) 37.5 29.0

200- (74) 51.5 44.0

140- (105) 65.5 61.0

100- (147) 82.5 70.5

80- (177) 90.5 87.5

60- (250) 99^5 97^

Total Particle Area

c 227 m

2 /gm 169 m

2 /gm

a SEM-AIA of 325- fraction.

bAllen-Bradley L3P Sonic Sifter. Calculated for spheres - density of 2.

Suspended Particulates . Analysis of particulates in air samples is an example of multiple-component dusts for which both particle identification and sizing are required. The sample mass is usually very

small and a large number of different compounds are often present. SEM-AIA is ideal for this application, as x-ray spectroscopy can be used to classify particles according to the relative intensities of the elements they contain by computerized matching with a stored

library of reference materials.

A SEM micrograph of a representative air sample from an exploratory study to evaluate

the AIA technique is shown at low magnification in figure 14. Micrographs of individual particles and their x-ray spectra are shown in figure 15. The preliminary results of SEM-AIA analysis of several thousand particles are shown in Table 7. When fully developed, more detailed studies with this technique will provide a means of identifying the contri- butions of various sources to the total suspended particulates in ambient air in industrial areas.

75
Figure 14. Low magnification scanning electron micrograph

of a suspended particulate air sample. (800X)

Table 7. SEM-AIA analysis of air samples (wt. %).

a Location Particle Type

b Boi ler Plant Road Ambient

Clays 41 8 27 Slag - 60 4 Fly Ash 16 - 5 Carbon 33 2 2 Fe-rich c 6 30 16 Misc. 4 - 6

illustrative example from exploratory study; computed

from measured size distribution. ^Determined from x-ray intensities of Na, Mg, Al , Si,

S, CI, K, Ca, Ti , Fe, and other metallic elements. Essentially iron oxide with traces of other elements.

77
i Oxide (Steel) A,B) Secondary Electron Micrographs of I

I Mite Clay Particles.

B) Clay (Road Dirt)

1 Oxide and

C) Digital Measurement D) Digital Measurement

C.D) Digital Measurement of Particle Diameters.

E) X-Ray Spectrum F) X-Ray Spectrum

E.F) X-Ray Spectra Used to Classify Particles by Composition. Figure 15. Illustration of AIA size measurement and identification of particles in an air sample.

78
Electron Diffraction Identification

Identification of particles by SEM-AIA is based on comparison of their x-ray spectra

th spectra from standard compounds. As in other applications of electron-probe microlalysis, the excitation and absorption of x-rays is affected by geometrical factors so that

ie relative intensities of the various peaks depend on particle size and shape. Another

)urce of difficulty with particle identification is the similarity in composition which

r ten occurs with minerals and other complex phases, as shown in Table 8. If positive

tentification of very similar phases is demanded, then AIA must be supplemented by ^ected-area electron diffraction analysis [8]. This is a time-consuming operation and

sans of automating the procedures are required. Table 8. Dimensions and composition of particle "type" classes. Average

Size, um AspectRatio Composition a PercentType Na M£ Al Si K Ca Ti Fe

A (Serpentine) 8 30 - 32 62 6

B (Pyroxene) 5 5 - 16 4 60 20

C (Clay) 7 19 1 40 50 1 8

D (Chlorite) 5 7 - 12 28 38 3 1 19

E (Mica) 6 8 - 10 24 40 9 1 1 14

F (Silica) 7 8 6 9 80 1 3 1 1 G (Augite) 5 6 8 49 - 22 21

H (Grunerite) 5 7 - 11 2 61 1 26

a Relative Intensity.

Detailed descriptions of the identification of microcrystal s from single crystal

effraction patterns are available in texts and the research literature [13]. In brief,

iterpretation of SAD patterns is accomplished by measuring two primary d spacings on the

ittern (largest d spacing or smallest reciprocal lattice vectors) and the angle between

lem, as illustrated in figure 16. The measured spacings are compared by computer with

ilculated interplanar spacings and angles from preselected known structures. Accurate

ilibration of the camera constant is essential, and this is usually achieved by vacuum

iating the sample with a thin film of gold so that a standard pattern is superimposed on

ie SAD image. Because of the greater penetrating power and higher resolution, it is ilvantageous to use the million volt microscope for SAD analysis.

A computer logic program, designated SEARCH, was developed to expedite comparison of

ie SAD data with a large number of reference compounds [14]. It includes the effects of

ittice symmetry. A typical set of data input statements required to run the SEARCH

•ogram is illustrated in figure 17.

79
4

i •

Figure 16. Illustration of basic measurements required to identify electron diffraction patterns.

PROGRAM SEARCH

Enter Di, D 2 , 6 exp

Attach Data From DIFFPAT

Figure 17. Computer logic designated SEARCH, to aid interpretation of electron-diffraction patterns.
The combined use of x-ray spectrochemical and electron-diffraction methods, as illustrated in figure 18, is essential in the analysis of air samples. For example, the nisidentif ication of amphiboles and their erroneous association with asbestos has generated

nuch confusion [15]. However, even with computer-associated pattern interpretation, it is just not practical to identify a large number of unknown particles by electron diffraction.

\ satisfactory compromise is to classify a large number of particles according to type

rlasses on the basis of x-ray spectroscopy and aspect ratio by SEM-AIA [7]. Representative

oarticles in type classes are then positively identified by the electron-diffraction

orocedures outlined above. This method introduces a statistical factor into particulate

analysis, but does permit assignment of a probable error to the apparent concentration of zritical constituents, such as amphiboles, on a valid and verifiable basis.

Figure 18. Illustration of combined use of AIA and SAD to identify particles.

81
Concl usions

As illustrated by examples, AIA methods extend the capabilities of the SEM into the realm of quantitative characterization of particulates. Data can be obtained very rapidly,

and no more than an hour is required to analyze several thousand particles and store the data for detailed interpretation by computer. The ability to determine statistically

significant means, standard deviations, and other size-distribution parameters permits detection of small differences in characteristics that may show up as significant dif- ferences in bulk properties. Such data allow the microscopist to correlate his measurements with the results of conventional analytical procedures, or to select individual par- ticles of special interest for more detailed microscopic studies. The tedium of repeti- tive measurements is eliminated, as well as subjective judgment by the operator. The investment in equipment and software development will be amply repaid by reduced analysis

costs and more accurate and complete data.

Development of some of the techniques and illustrations described in this report

(references cited) in collaboration with J. S. Lally, J. F. Kelly, A. Szirmae, S. Lentz,

N. J. Panseri , G. M. Demchsin, Hsun Hu, G. P. Huffman, and F. E. Huggins is gratefully

acknowledged. References

[1] Isaacson, M. S. and Silcox, J., Report of a Workshop on Analytical Electron Microscopy, Ultramicroscopy, 2, 89 (1976).

[2] Silcox, J., Analytical Electron Microscopy Workshop Report, Cornell, July 1978.

[3] Oron, M. and Gilbert, D. , "Combined SEM-Minicomputer System for Digital Image Processing," Proc. 9th Ann. SEM Symp. , IITRI, Vol. 1, 1976, pp. 121-128.

[4] Ekelund, S. and Werlefors, T. , "A System for the Quantitative Characterization of Microstructures by Combined Image Analysis and X-Ray Discrimination in the SEM,"

Proc. 9th Ann. SEM Symp. , IITRI, Vol. 1, 1976, pp. 419-424.

[5] Grant, G. , Hall, J. S. , Reid, A. F. , and Zuiderwyk, M. , "Multicompositional Particle Characterization Using the SEM-Microprobe," Proc. 9th Ann. SEM Symp., IITRI, Vol. 1, 1976, pp. 401-408.

[6] Hoover, M. R. , White, E. W. , Lebiedzik, J., and Johnson, Jr., G. G. , "Automated Characterization of Particulates and Inclusions by Computer Controlled SEM/Probe,"

Proc. 10th Ann. Conf . , Microbeam Anal . Soc. , 1975, pp. 54A-54B.

[7] Lee, R. J., Lally, J. S. , and Fisher, R. M. , "Identification and Counting of Mineral Fragments," NBS Spec. Pub. 506, Workshop on Asbestos: Definitions and Measurement

Methods, 1978, p. 387.

[8] Lee, R. J. and Fisher, R. M. , "Identification of Fibrous and Non-Fibrous Amphiboles in the Electron Microscope," Annals of the New York Academy of Sciences, 1978, in press.

[9] Lebiedzik, J. , "Multiple Electron Detector Method for Quantitative Microtopographic

Characterization in the SEM," Doctoral Thesis, Penn State University, University Park, PA 16802, March 1975. [10] Lee, R. J. and Hu, Hsun, "Automatic Image Analysis of MnS Precipitates in 3% Si Steel,"

1978, to be published.

[11] Lee, R. J., Huggins, F. E. , and Huffman, G. P., "Correlated SEM-Mossbauer Studies of

Coal Mineralogy," Scanning Electron Microscopy, I, 561-568 (1978).

82
2] Huggins, F. E. and Huffman, G. P., "Mossbauer Analysis of the Fe-Bearing Phases in Coal, Coke, and Ash," Rev. Chapter to be published in Analytical Methods for Coal and

Coke, Vol. 3, ed. Clarence Karr, Academic Press.

13] Lee, R. J., "Basic Concepts of Electron Diffraction and Asbestos Identification Using Selected Area Diffraction. Part I: Current Methods of Asbestos Identification Using

SAD. Part II: Single Crystal and SAD," Proc. Scanning Electron Microscopy, 1978,

Vol. 1 , SEM, Inc. , 1978.

14] Lally, J. S. and Lee, R. J., "Computer Indexing of Electron Diffraction Patterns Including the Effect of Lattice Symmetry," Proc. EMSA, 1977, p. 22. 15] Gravatt, C. C. , LaFleur, P. D. , and Heinrich, K. F. J., NBS Spec. Pub. 506, Proc. of Workshop on Asbestos: Definitions and Measurement Methods," November 1978.

83

ational Bureau of Standards Special Publication 533. This Publication Originated from a pecial Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

pciety, Ann Arbor, MI, June 22, 1978. (Issued April 1980) CHARACTERIZATION OF COAL GASIFICATION PARTICULATES BY SEM, EDS, AES, XPS, AND

ITS RELEVANCE TO INHALATION TOXICOLOGY

D. L. Davidson and E. M. Gause Southwest Research Center

P.O. Drawer 28510

San Antonio, Texas 78284 Introduction

The initial site of deposition of an inhaled particle depends primarily upon its size; articles larger than 10 pm in diameter are trapped in the nose, while particles

etween 10 and 3 pm are deposited in the upper respiratory tract, and particles

=low 3 pm reach the deep lung or alveolar region before being deposited. There

re some exceptions to these generalizations as very long, narrow asbestos fibers have been

ound in the deep lung upon autopsy [l] 1

. Particles smaller than 3 pm are generally

eferred to as being in the respirable size range. Once inspired particles are deposited in the deep lung, clearance mechanisms involve

nagocytosis by alveolar macrophages or solubilization by lung fluids. In the phagocytic

rocess, particles are ingested by alveolar macrophages which then attempt to degrade the

articles enzymatical ly , figure 1. If there are nonpolar organic compounds present on the

Figure 1. Schematic representation of the process of macrophage phagocytosis:

(1) Ingestion of the bacteria,

(2) Lysosomes containing digestive

enzymes, (3) Release of the enzymes

into the phagosome surrounding the bacteria, (4) Digestion, (5) Elimination.

jrfaces of the particles, they may be converted into aqueous-soluble forms by the action

F monooxygenases (mixed function oxidases) in preparation for excretion in urine; the

iter-soluble forms may be more or less toxic than the original form depending upon the

iture of the starting material - i.e., metabolites produced may be mutagenic or carcino-

?nic. Metallic and organo-metal 1 ic species adsorbed on particle surfaces may be removed

ither intracel 1 ularly or extracel 1 ularly by binding to proteins or dissolution in lung

luids; toxicity will depend upon the specific metals and oxidation states of the metals

: igures in brackets indicate the literature references at the end of this paper.

85
involved. After removal of substances adsorbed on particle surfaces, the composition of the residual particle may be primarily inorganic salt or mineral, or graphitic carbon; however,

if the residue is insoluble in lung fluids, the only mechanism by which it can be cleared is phagocytosis and transport out of the lung by alveolar macrophages. Since the macrophage

will not be able to digest particle residue in the same way it degrades ingested microorganisms, through the action of lysosomal hydrolytic enzymes, the undigested particle may be released to be taken up by another macrophage in a futile cycle; the release of the particle

(exocytosis) will be accompanied by the release of hydrolytic enzymes which can damage lung tissue, figure 2. Alternatively, if substances adsorbed on surfaces of the particles, or

Figure 2. Schematic representatio

mav nrrni" when a msrrnn Schematic representation of what

may occur when a macrophage cannot phagocytize a particle: (1) Ingestion, (2) Lysosomes containing digestive enzymes, (3) Which are released into the phagosome, (4)i Digestion cannot proceed, (5) particle1p and and the enzymes

el iminated.

The

or the particles themselves (e.g., silica), are toxic to macrophages, they will cause death

of the macrophages resulting in cell lysis and release of both hydrolytic enzymes and the toxic particles which can then be taken up by another macrophage to repeat the cycle. This effect can result in foci of dead and dying macrophages - an observation which has been linked to tumor formation and to tissue necrosis [2]; it will also result in local concen- trations of the phagocytized toxic particles or "hot spots." There is evidence that particles which cannot be degraded by alveolar macrophages are eventually cleared from the lung only by dissolution in lung fluids and transport into the blood system - a process which may take years, or may never be successful, depending upon the solubility properties of the particle. Toxic chemical species can be concentrated on the surfaces of respirable particles by condensation and adsorption during the cooling of combustion products, resulting in much higher biologically available levels of such species than would be anticipated from bulk particle analysis [3]. In fact, high surface concentrations of species not even detectable

by conventional bulk analysis or by single particle x-ray microprobe analysis can be attained. This surface form of concentration also maximizes biological uptake and biological impact of the toxic species, in that leaching by biological fluids is facilitated and contact of cells with the surface-bound species is maximal. Surface deposition also results

in a greater concentration of toxic trace elements the smaller the particle diameter; and the smaller the particle diameter, the more likely it is to be inhaled and deposited within

the deep lung [3]. Chemical nature, oxidation state and concentration of species bound to the surface of respirable particles are determined by the inorganic components of fuels which may be present in extremely low concentrations and by the conditions of the combustion process. The combustion process may result in condensation of minor fuel components upon surfaces

of effluent particles leading to relatively high "environmentally effective concentrations." The capacity of particles resulting from a given process for producing serious adverse health effects is presently not understood, but is growing in importance as energy technology switches to alternate fuel sources, both stationary and mobile.

86
Materials Examined

Particles described in this study were obtained from a European coal gasification tlant. Details of the particle collection procedure are unknown. The particles were sieved

" o separate particles in the respirable size range from the bulk sample, and only the frac- tion below 20 urn in diameter was examined. The larger size fractions were ground in a ball

e;|ill with alumina grinding balls and re-sieved. The fraction of this ground material below

;;0 um in diameter was also examined by surface analysis techniques.

For examination, a sample of particles was placed into reagent grade isopropyl alcohol,

nd this slurry was then flooded onto sintered silver filters (Selas Co.) having a pore

iameter of 0.45 um. Bulk Analysis

Because of the small size of the particles, electron penetration at the working voltges necessary for x-ray microprobe analysis causes fluorescence from most parts of the

-'article volume, as opposed to surface analysis by electron spectroscopy. The x-ray Analysis was carried out at the University of Texas Health Science Center in San Antonio

"sing a JSM-35 Scanning Electron Microscope (SEM) equipped with a Tracor Northern model 880 Energy dispersive x-ray spectrometer. Numerous particles were individually analyzed and Photographed. The photographs of three typical particles are shown in figure 3, and the

-ray spectroscopy of these particles is shown in figure 4. The physical appearance of the

ipHlver filter may also be seen in the photographs, and the chemical composition of the filter is shown in figure 5. From these illustrations and data taken from a number of

ther particles, the particles were found to contain principally aluminum, calcium, iron, agnesium, silicon, sulfur, and perhaps small amounts of titanium or barium, chlorine and

opper. The particles shown in figures 3a and 3b have sufficient quantitites of magnesium

r aluminum, silicon, and iron that they might be considered to be in the asbestos family

If minerals. A quantitative analysis of the particle shown in figure 3b indicated the onstituents shown in Table 1 (excluding the silver filter").

87
c Ca-Ka

tVtq

0 2 ^" Curve B 4 Energy, keV 8 Figure 4b.

4

Energy, keV

Figure 5. Energy spectrum of the silver filter carrier for the particles.

Element Concentration (%)

Al 31.8

Si 30.6

Fe 3.5

Na 14.1

CI 13.9 The techniques used in this analysis were the standard background subtraction and ZAF correction techniques furnished by the equipment manufacturer. The curve with silver filter spectrum subtracted is shown in figure 4b as curve B.

90
Auger Electrons

5 keV source

10.5 uamps beam

Surface Analysis

The same particulate material (but samples different than those examined by energy

spersive x-ray analysis) was also subjected to surface analysis by Auger Electron Spectro-

)py (AES) and x-ray Photoelectron Spectroscopy (XPS), also called ESCA. Because both of

,?se techniques [4] depend on the energy spectrum of relatively low energy electrons, only

"face and near-surface material is included in the analysis, as opposed to the larger

lume of material from which x-rays originate in the microprobe analysis. Equipment

lufactured by Physical Electronics Industries was used for both the AES and XPS analyses.

The Auger electron spectra of the particulate material, figure 6, and of the ground

i sieved material, figure 7, show that the unground material has a greater surface con- ization of constituent elements than does the ground material, which has a higher con- ization of carbon. As with the bulk analyses, aluminum, magnesium, and silicon are

|in prominent elements, although it is not possible to know if they are in the correct

.icentrations to be considered as any of the minerals constituting asbestos. The presence

\ sulfur in both spectra is also considered significant, even though the concentration is

91
1 1

i i i i i i Auger Electrons

5 keV source -

i

5 pamps beam -

fS\ CI JAn rrin Fe Si

1g

-

1 i i i I i

i

-

0 200 400 600 800 1000 1200 1400 1600 1800 2001 ELECTRON ENERGY, eV Figure 7. Auger electron spectrum of the ground particulates.

The x-ray photoelectron spectra of the unground and ground particulates are shown in figures 8 and 9. The most significant finding from these spectra is the presence of the heavy metals, lead, selenium, and molybdenum, on the surface of the unground material; lead

is indicated to be in fairly high concentration. For the ground material there is comparatively a higher concentration of carbon and less of the other significant elements. In this spectra, the presence of a small nitrogen peak is clearly indicated, while it was not clearly found for the underground material; whereas there may, in fact, be a nitrogen peak

in the unground material spectra, the concentration is very low compared to that for the ground material

92
i 1000 900 800 700 600 500 400 300 200 100 BINDING ENERGY, eV Figure 8. X-ray photoel ectron spectrum of the unground particles.

: I

93
The x-ray photoelectron carbon Is peak for the unground and ground material were

examined at higher resolution, figures 10 and 11. The C Is peak for the unground material

is that expected for graphite, while for the ground material there has been a shift to 0.6 eV higher energy, indicating the possible presence of some more complex forms of carbon

than graphite, namely hydrocarbons. An extensive effort to determine which hydrocarbons

are present has not been made, and the chemical formula shown in figure 11 is given only to indicate what hydrocarbons might exist at the energy transitions indicated. Considerable

effort would be required for a more positive identification of which hydrocarbon was

present.

94
x-ray photoelectron Spectroscopy

r Carbon Peak

Graphite

295 285 Binding Energy eV

Figure 10. X-ray photoel ectron spectrum of the unground carbon Is peak.

275
CH3

C0OH Graphite

x-ray photoelectron Spectroscopy

Carbon Peak

Ground Material

!

Figure 11. Binding Energy eVX-ray photoelectron spectrum of the ground material carbon Is peak.

As the large particulates were ground and sieved, the material was noted as having an "oily" appearance and texture, and it tended to agglomerate, a characteristic not found in the unground material. Thus, the presence of hydrocarbons in the interior of this particulate matter appears to be a reasonable finding. The nitrogen peak found on the x-ray photoelectron spectra of the ground material was also examined at higher energy resolution,

figure 12. Although the indicated peak energy is that expected for nitrogen gas, it is much broader than expected, and it appears as though it might be deconvoluted into three

or four peaks, each having a shift in energy from that of gaseous nitrogen. For the peak indicated at about 402 eV, the compounds could possibly be (CH 3 ) 2 N0 or NH3 0HC1 , or perhaps

a number of others. The peak indicated at about 400 eV could possibly be C0NH 2 or be indicative of an NH3 radical [5]. Again, sorting out which of the numerous possible

compounds is actually present would require considerable effort [6].

96
N(E)

x-ray photoelectron Spectroscopy

Nitrogen Peak Ground Material

406 400 394 BINDING ENERGY eV

Figure 12. X-ray photoelectron spectrum of the ground material nitrogen Is peak.

The Auger electron spectra of the ground material was examined after removal of approximately 100 A of material by argon ion bombardment (sputtering). The aluminum, iron, magnesium, and silicon peaks, found to be largely suppressed as compared to their amplitude

for the unground material, were found to again be present in small concentrations, and the

carbon peak was somewhat attenuated in comparison to the unsputtered peak. This finding

appears to indicate that there is a thin covering of carbon, possibly in the form of hydrocarbons, on the surface of the ground material, which would correlate well with the

XPS and visual observations.

Results of the present study indicate that there is a large degree of variability in bulk composition and physical properties between individual particles originating from a common source, suggesting that careful attention must be given to obtaining representative

(samples. While the surface analysis techniques employed here do not allow examination of individual particles, it is likely that the observed differences in particle bulk composition are reflected in the nature of chemical species adsorbed on the surfaces of the particles due to variations in temperature of volatilization and condensation, position

within the stack at which particle cooling allows condensation/adsorption onto surfaces,

reducing or oxidizing atmospheres, etc. Surface anlaysis revealed the presence of lead and selenium, both of which have welldocumented toxicities associated with inhalation exposure [7]. Lead and selenium exhibit

neurotoxicity with central nervous system involvement in addition to causing damage to various other organs such as kidney, liver, and spleen; selenium is also considered to be embryotoxic and teratogenic. The observation that the concentration of these two elements

was greatly attenuated after grinding of the particles offers additional proof of their

surface localization and concentration.

97
In contrast to lead and selenium which were found only on the particulate surfaces,

sulfur was observed both on the surface of the ground and unground particles and in bulk by x-ray fluorescence, indicating that it is present throughout the particles. Although it was

not determined in these studies, the chemical form of sulfur could be quite significant with

respect to potential toxicities of the particles. Other surface changes observed after grinding of the particles were: (1) a shift in the position of carbon peak indicating the presence of hydrocarbons, and (2) surface exposure of reduced forms of nitrogen, some of which were observed to be chemically bound to other elements. The association of combined

nitrogen and hydrocarbon- 1 i ke carbon may well reflect the occurrence of organic nitrogen- containing compounds which would be expected to result from the high temperatures of the

coal gasification process. Many organic nitrogen-containing compounds such as aromatic

amines have been found to be carcinogenic or mutagenic [8]. Both bulk and surface analyses indicated the presence of elements comprising the various minerals generically known as asbestos although the actual existence of these

minerals in samples examined was not verified. Asbestos is, of course, capable of producing

grave pulmonary disease, in that asbestos fibers too long to be ingested by macrophages

cause collagen production and fibrogenesis or asbestosis; asbestos can also cause lung cancer [9]. Inhalation of particulates is a direct route of entry into the body. It has been

reported that approximately 25 percent of inhaled particles in the respirable size range

settle in lung tissues, a similar amount is exhaled, and the remaining 50 percent is diverted to the pharynx, where it is swallowed [10]. Combustion-derived particulates

apparently possess a variety of chemical species condensed onto or adsorbed on their

surfaces, including trace metals, organic compounds, and ionic species. Alveolar absorptive

efficiency for most trace elements is 50-80 [3] and efficiency of absorption in the stomach

is 5-15 percent [11]. Many trace elements are carcinogenic, mutagenic, cytotoxic, or can disturb vital biochemical equilibria causing a variety of toxicological manifestations.

Organic compounds are either metabolized by phagocytic cells or solubilized by binding to proteins and transported to other sites; many representatives of this class of compounds

are either cytotoxic (causing cell death), or carcinogenic and therefore capable of causing

cancer of the lung or of other organs upon transport to distal sites in the body. The processes of carcinogenesis and mutagenesis are characterized by very long lag times (decades) between exposure and appearance of effect; there processes may also be initiated

by extremely small amounts of material, so that low doses of inhaled particulates may be responsible for cancers or other irreversible toxicities appearing many years later. The presence of several toxic metal species on the su; faces of the particles described

herein and exposure of other potentially toxic material upon grinding of the particles, indicating that these substances could be gradually released or extracted by tissues, illus- trate the need for careful consideration and quantification of the concentrations and distributions of these surface-bound species and of tissue residence times and bioavail- ability of occult bulk species within a representative sample of respirable particulates.

This information could then be employed for estimation of extent of exposure; and when

relatistic information as to atmospheric concentration becomes available, and when dose- response data is obtained from animal exposure studies, it will be possible to estimate

risks involved in human inhalation exposures. Summary and Conclusions

Surface analytical techniques (Auger electron and x-ray photoelectron spectroscopies)

have found biologically important chemical species not detected by bulk (x-ray microprobe)

analysi s. From consideration of the chemical nature of surface-bound species, together with their concentration and biological accessibility, there is reason to believe that, for most types

of respirable particles, the chemical species found on their surfaces may be more significant

with respect to potential toxicological effects than the particles themselves.

98
This work was supported in part by the U. S. Environmental Protection Agency under

ontract No. 68-02-2286 MDD2. We very much appreciate access to the Health Science Center

EM Laboratory equipment, and the help of Dr. Nancy Smith of that Laboratory. The assisance of Carl Hildebrand of Physical Electronics Industries in arranging access to the AES

.nd XPS surface analysis equipment is a

1 so gratefully acknowledged. A useful discussion

<ith John Funnell, Institute Scientist, is also acknowledged. References

[1] Timbrell, V., Inhalation and Biological Effects of Asbestos, in Assessment of Airborne

Particles, T. T. Mercer, et al .

, editors, Thomas Publishers, Springfield, IL, (1972)

pp. 429-441.

[2] Mohr, U. , Rezni k-Schul ler, H. , Reznik, G. , Grimmer, G. , and Misfeld, J., Investigations

on the Carcinogenic Burden by Air Pollution in Man. XIV. Effects of Automobile

Exhaust Condensate on the Syrian Golden Hamster Lung, Zbl. Bakt. Hyg. , I. Abt. Orig.

B, 163, 425-432 (1976).

[3] Natusch, D. F. S. , Wallace, J. R. , and Evans, C. A., Jr., Toxic Trace Elements: Preferential Concentration in Respirable Particles, Science, 183, 202-204 (1974).

[4] Characterization of Metal and Polymer Surfaces, Vol. I and II, ed. by Lieng-Huang Lee, Academic Press, New York, 1977, pp. 105 and 399.

[5] Grieger, G. R. , American Laboratory, 8(4) , 77 (1976).

[6] Novakov, T. , Chang, S. G. , and Harker, A. B. , Science, 186, 259 (1974).

[7] Beliles, R. P., Metals, in Toxicology, The Basic Science of Poisons, L. J. Casarett

and J. Doull, editors, Macmillan, New York (1975) pp. 454-502.

[8] Clayson, D. B. and Garner, R. C. , Carcinogenic Aromatic Amines and Related Compounds,

in Chemical Carcinogens, ACS Monograph 173, G. E. Searle, editor, American Chemical

Society, Washington, D. C. (1976) pp. 366-461.

[9] Harrington, J. S. and, Allison, A. C. , Tissue and Cellular Reactions to Particles,

Fibers, and Aerosols Retained After Inhalation, in Handbook of Physiology, Sec. 9, Reactions to Environmental Agents, D. H. K. Lee, editor, American Physiol. Soc. , Bethesda, MD (1977) pp. 263-283.

[10] Schroeder, H. A., Environment, 13, 18 (1971).

[11] Patterson, C. C. , Arch. Environ. Health, 11, 344 (1965).

99

National Bureau of Standards Special Publication 533. This Publication Originated from a Special Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

Society, Ann Arbor, MI, June 22, 1978. (Issued April 1980) ACCURACY OF ELECTRON MICROPROBE ANALYSIS OF BIOLOGICAL FLUIDS: CHOICE OF STANDARD

SOLUTIONS, AND RANGE OF LINEARITY OF THE CALIBRATION CURVES Nicole Roinel , Lucienne Meny,

CEA, CEN Saclay 91190 Gif sur Yvette, France

and Jean Henoc CNET 92220 Bagneux, France Introduction

In investigations of cellular mechanisms, the volume of biological fluids for analysis

is often too small for conventional analytical techniques. The sensitivity of the electron

nicroprobe, however, is adequate to determine elements in fluids of picoliter volumes

[8] 1

. The principle of the use of the electron microprobe in this case is simple. The

x-ray intensity of an element, determined in unknown solutions, is compared with that

obtained from identical volumes of standard solutions of known composition. One assumes

that the emerging intensity is proportional to concentration. Absorption of x-rays and

electrons is the main limitation to the validity of this assumption. To minimize absorption, solutions are rapidly frozen and lyophilized, which results in samples composed of submicron size crystals; in such samples, the measured x-ray intensity of an element is Droportional to its concentration, even for elements of rather soft x-rays such as sodium

[11]. The concentrations of various elements in unknown samples are directly deduced from

this linear relationship, without correction for absorption, fluorescence, or atomic

number effect. This technique has now been used by many groups for the determination of concentrations

3f elements [1,5,9,10,12,13] or organic compounds [2] in biological solutions, using either

wavelength dispersive, or the energy dispersive x-ray detection systems [14,15,17]. The

accuracy of this kind of analysis rests upon the assumption that the proportionality factor

oetween background corrected signal and concentration be the same for standard and unknown

solutions, at least within some range. Questions remain, however. For example: what are

the limits within which the response is linear? Can any solution of known composition be

used as a standard? What is the influence of the matrix upon the emerging x-ray intensity

3f the various elements? Without any theoretical formulation, these questions must be solved empirically; more particularly, each biological fluid to be analyzed necessitates a complete study of the more optimal standard solutions to insure accuracy.

The present paper attempts to answer a few of these questions and to consider the

choice of the composition of the standard solutions. We compare intensities measured from

real samples to those calculated for a thin film of same composition, in order to see

whether the range of proportionality of the measured x-ray intensity to the element concentration can be deduced from a theoretical model.

figures in brackets indicate the literature references at the end of this paper.

101
Sample Preparation and Results

The preparation technique presently used at Saclay comprises two steps [19]: the deposit of biological and standard solutions on a specimen holder and the treatment of the dried deposits for electron microprobe analysis. This two-step procedure allows the dried

samples to be stored without any special precaution and the same holder to be used repeatedly for various experiments until its surface is completely covered with samples. Sub- sequent electron probe analysis is automatic, directed by means of a computer program [18] which facilitates the analysis of large series of samples. The solutions are deposited using a constriction micropipette on the polished surface

of a beryllium holder. The holder surface is covered with paraffin oil to avoid spontaneous

evaporation at the tip of the pipette during deposit of droplets. The oil is then washed

off in a chloroform bath and the samples are allowed to dry in the open air. Prior to electron microprobe analysis, the droplets are rehydrated by cooling the holder to 4 °C on a Peltier plate to cause water to condense from the cooled air; the atmospheric water is trapped by the salt crystals. The holder is then placed on a piece

of dry ice causing the droplets to freeze immediately; they are then lyophilized at -40 °C

in a 10" 2 Torr vacuum. Samples are now ready for analysis. They consist of a multitude of crystals spread over a circular area. The topography of the dried samples will be described

below. The area is a function of the sample volume and of the hydrophilic property of the surface holder, which may vary from one experiment to the next. A mean sample mass thickness is calculated as the ratio of the deposited dry mass of salts to the surface area. This technique has been applied mainly to renal physiological investigations for anal- ysis of fluids obtained from kidney tubules by micropuncture. The principal elements are

Na and CI, plus K, Ca, P, and Mg, elements whose atomic number exceeds 10. Standard solu- tions are designed to have a composition as similar as possible to that of the biological

samples. The samples are fully irradiated by a defocused electron beam. Linear calibration

curves are routinely obtained over the biological range of concentrations as shown in figure

1 for various elements, where x-rays are measured by crystal spectrometers. The intercept

at the ordinate of the curves is the background value measured on the beryllium holder, between the samples, at the same Bragg angle. The background value is proportional to the beam intensity, and increases as a function of the atomic number of the holder and of the beam voltage. The slope of the calibration curves is also proportional to the beam intensity, the sample volume, and the inverse of the beam cross section (provided the sample is fully irradiated by the beam). The slope decreases with increasing accelerating voltage when the overvoltage ratio (ratio of accelerating voltage to the excitation potential of the analyzed line) is more than two or three. The calibration curves are linear at 12 kV for samples of calculated mean mass thickness of 0.09 mg/cm2 or less. Table 1 gives

typical values measured from a series of experiments of the slope-to-background ratio,; which represents the ratio of the characteristic signal of 1 mM/1 of an element (sample volume = 0.15 nl) to the background signal; this ratio measured with a Cameca MS-46 electron

probe is obtained for a mass thickness of 10~ 4 mg/cm2 of this element.

102
2

£8

103
Table 1. Ratios of 1 mM/1 concentration of an element to the background. E = 15 kV $ = 70/jm

v =0.15 nl

UIOOnA; t= 10 s I = 300nA, t=50s 1 = 300 nA ; t=100s CI PET 3 Na KAP

Ca

PET 3 K PEU

P PET3 Mg KAP

Background 20 10 435 210 130 335

1mM/l siqnal Background ^SE j n = 13

2.0 ±0.2

1.9 ±0.1 2.6 ±0.2

2.7 ±0.2 ±0.3

2.2 ±0.2 ImM/l mass

thickness mg/cm 2 Ux10"

4 9x 10"5

1.6 x 10"^ 1.5x10"

4 1.2x10"4 9.5x10"

5

Table 2 gives the 95 percent confidence level for precision of 1 mM/1 of an element

measured under the conditions described in the table. The geometry of the lyophilized

samples does not affect the counting rate, as shown by the fact that the standard deviation

of the counting rates of five replicates of a solution is not larger than the standard

deviation expected from Poisson's law [11]. Table 2. The 95 percent confidence level precision over 1 mM/1 measurement. Na

KAP

CI

PET CaPET K

PET P

PET Mg

KAP

BG = background 300 200 870 400 130 335

N = signal 1mM/l 570 400 2260 1080 533 737

<f = VN + 2 BG 34.2 28.3 63.2 43.3 28.2 38.8

to.05 x 6

VT6

24.4 20.2 45.2 30.9 20.2 27.7 Precision % 4.3 5.0 2.0 2.9 3.8 3.8 3VBG

minimum defecta

ble concentration mM/l

mass thickness mg/cm 2

52.0 0.09

8x10-6

42.2

0.10

1.4x10-5

88.5

0.04

6x10-6

60.0

0.05

7x10-6

34.2 0.06

7x10-6

55.0

0.07

7x10-6

probe: 15 kV _

CI 70 urn .100 se :100nA

conds - samp

others :300

le volume : 0

A

15 nl

Table 2 gives, under the same analysis conditions, the minimum detectable concentration as defined by a signal equal to three times the standard deviation of the background. The minimum detectable concentration corresponds to an element mass thickness of 10 -16 g/um2

, or 10~ 5 mg/cm2

. It can be improved by increasing the slope-to-background ratio, or 104
ncreasing the number of counts. The slope-to-background ratio is increased by lowering

:he beam voltage, provided this does not affect the linearity of the calibration curves

i [by absorption of the electrons within the samples). The number of counts is increased by ncreasing the analysis time or the beam intensity, provided this does not affect the

stability of the counting rate. Accuracy of Results

The validity of using calibration curves without correction for absorption, fluorescence, and atomic number depends upon: 1) the identity of the oxidation degree when it affects the energy of the line to be analyzed; 2) the stability of the counting rate of the

i/arious elements; and 3) the similarity of standard and unknown solutions in terms of the

lain matrix. Only the first and second points will be considered here.

1. Influence of the degree of oxidation

Among the various elements of interest for the biologist, sulfur exhibits different

iegrees of oxidation, either as sulfate in the tubular fluid of the kidney, or with an

i-H bond in the amino acids cysteine, cystine and methionine. According to Faessler and

ioehring [4], an increase of the Ka energy of 1.2 eV from S° to S 6+ results in a decrease

pf 0.003 K of the wavelength of sulfur. This decrease is easily observed with the PET

:rystal of a CAMECA MS-46 microprobe. Figure 2 illustrates the S signal, measured from

sulfate, cysteine, and methionine samples, as a function of the PET crystal position. The

signal p - « too %

15kV-100nA - 90/jm - 10s - 0.18 nl

a MgS04 , 7H20 IOOmM/1

o Na 2 S04 100 mM/l

. L- cysteine -CI 100mM/l

methionine-Cl 100mM/l /TV?

J

PENTAERYTRI TOL

\

\

CSTAL POSITION a.u.

Figure 2. The characteristic signal of sulfur from various sulfur containing solutions as a function of the crystal spectrometer position (higher figures) and of the cor- responding wavelength value (lower figures), a.u. = arbitrary units.

105
106
ignal is expressed as a percentage of the highest counting rate. Samples are measured at

. beam current density which does not affect the stability of the sulfur signal counting

ate. The sulfate curve is clearly different from the methionine and cysteine curves,

"nly 50 percent of the maximal cysteine and methionine signals are measured when the crystal pectrometer is positioned for the maximal sulfate signal [20]. The measurement of sulfur

n samples containing various sulfur compounds must take this into account.

2. Stability of the counting rates

The counting rates of Na, Mg, P, Ca, and K are stable in both biological and mineral

olutions (when they are mixtures of salts) for at least 1000 s irradiation with a beam

current density as high as 0.008 A/cm2

. The chlorine counting rate is stable in biological Huids such as plasma, urine, and kidney tubular fluid. It decreases with time, however,

n mineral solutions when the probe current density and the sample mass thickness increase

19]. This effect is largely dependent on the nature of the accompanying cation (figure

:'.). For example, ammonium chloride has a particularly volatile chlorine signal. On the

ame figure is shown the influence of the beam intensity on the time-dependent decrease in :hlorine counting rate. Figure 4 shows that when a pure mineral chloride salt is irradiated, the cation

ounting rate decreases, along with chlorine, but to a lesser extent. Moreover, as shown

n the same figure, samples obtained from identical volumes of the same solution do not

ose their chlorine and cation signals at the same rate, probably due to variations in the

•eplicate mass thickness.

(jox100)

O/

° 15 KV- 300 nA- 80 >um_( 13* 7 ) s

NaCl 200 mM/l 0.12 nl 59 x

10"

,3 g//jm 2

10.

500 ' 1000 1500 IRRADIATION TIME IN SECONDS

Figure 4. The decrease in chlorine and sodium counting rate as a function of irradiation

time. Number at the end of each line identifies replicates.

107
Bromine and iodine behave like chlorine; their counting rates decrease with the time

in mineral solutions (figures 5 and 6). In a solution of a pure salt, the counting rate

of the accompanying cation decreases too, but always to a lesser extent.

KBr 150 mM/l - 0.2 nl

K PET 3

0<?°°o°, ' v B r l i f

15KV-65yum -{ 13 + 7 )s automatic

300 n A

500 1000 1500 IRRADIATION TIME SECONDS

Figure 5. The decrease in bromine and potassium counting rate as a function of irradiation

time. Open symbol - bromine signal. Black symbol - potassium signal. The same symbols refer to the same replicates.

108
Instability with irradiation time of the sulfur signal is also observed in sulfate

solutions, but not in methionine or cysteine solutions (figure 7). A non-hydrated sulfate

salt always exhibits a decrease of its S signal, and to a lesser extent of its cation

signal, with time (figure 8). Hydrated sulfate salts, such as MgS04 , 7H2 0, exhibit either

a decrease (figure 9) or an increase (figure 10) of their S signal, with a corresponding

change of the cation signal (figure 10).

109
s

x 100 7. .8 *

D 8

12 kV 300nA 60/jm t=10 s v=0.2nl

. MgSC^ 7H20 100 mM/

° L cyst eine 60 mM/ I * methionine 90 mM/

mean over 2 samples

50 100 150 200 TIME IN SECONDS

Figure 7. The variation in the sulfur counting rates as a function of irradiation time for various sulfur containing solutions.

Figure i

Na 2 SOA 100 mM/ 1 0.12 nl 15 x

10"'i g/yum; 15kV 300nA (13+7)s Na kap

30/jm 300 nA

60 jum

- 100 yum •• -

• 60/jm 100 nA

IME SECONDS

The decrease in sulfur and sodium counting rate as a function of irradiation time

in a solution of sodium sulfate. Lines refer to various probe current densities. no
S signal

-j-x1007. MgSQ, 7H2 0 iomM/i

NaCl 200mM/l - KH 2 POit 10mM/l 15kV- 60/jm-(13+7)s-0.12nl

50 nA

150 nA

300 nA

500 1000 1500 TIME IN SECONDS

igure 9. The decrease in sulfur counting rate as a function of irradiation time from a hydrated sulfate solution mixed with other salts. Lines refer to various probe current densities. Mg50/, 7H2 0 ioomM/i 0.12m

15kV (13*7)5

100 nA 60/jm 300nA 30 yum

- •• 60/jm

•• •• 100yum

500 1000 " 500 1000 TIME IN SECONDS

Figure 10. The change in sulfur and magnesium counting rate as a function of irradiation

time from a hydrated sulfate solution. Lines refer to various probe current

densities.
Because of this variability, comparison of signals of biological solutions, which are stable with time, to calibration curves obtained from mineral solutions, which are not, would lead to errors in the determination of the concentrations of certain elements in biological fluids. To obtain an accurate analysis, it is essential to have stable counting

rates. We have achieved stability either by: 1) using lower beam current densities

(2 x 10~3 A/cm2 is correct for chlorine measurement within samples with a mass thickness of 0.06 mg/cm2 ); 2) cooling the samples (a cooling to only -20 °C is sufficient); or 3) adding

organic material to the mineral solutions (e.g. urea). Problems of instability are specific

to the wavelength dispersive system, which requires higher beam densities than the energy dispersive system; neither Rick et al. [17] nor Quinton [14,15] observed instability of the

signal with the latter system. Stability of the counting rates of the various elements is obtained with the mixtures

of salts shown in figure 11 which are used as standard solutions in our laboratory.

NaCl 200 mM/t- MgCl2 , 6 H2 0 10 mM/l KH2 POt W mM/l CaCl2 =KCl= 20 mM/l NaC1=100 mM/l

500 1000 1500

Time (sec)

Ca[fox too v.]

~500 foOO 1 50(T

Time (sec ) 500 1000 1500

Time (sec ) CI [£*«»%]

ioo w ..» P\Lx 100 %]

50 _

500 1 000 1 500'

Time (sec ) v = 0.2 nl. 75 kV. QOfim.

Cl : WOn A - others : 300 r

500 1 000 1 500"^ Time (sec )

. mean over 3 replicates

500 1000 1500^

Time (sec )

Figure Stability of the counting rates of the elements from solutions used as "standard solutions".

112
Chlorine is the first element measured, with a beam density of 0.002 A/cm2

. The accuracy

of the measurement of the chlorine signal within tubular fluid extracted from kidney

structures is shown by figure 12 which compares the results of the quantitative analysis of chlorine performed both by electron microprobe and by the Ramsay microcoulometric method

[16]. The equation of the regression line is: y = 0.94 x + 52, n = 72, r = 0.94. The probability for the slope to be different from unity is smaller than 10 percent. The range

of chlorine concentration is larger than that of the calibration curves; samples were

therefore diluted for microprobe analysis, to fit within the range of concentration of the

cal ibration curves.

> CI microprobe m m/i

o loop samples

• urine samples

~~*0"0" 600 BOO~

CI coulometry mM/l

Figure 12. Comparison of chlorine measurements obtained by electron microprobe analysis

and Ramsay coulometric method. Line indicates identity. "Loop samples" refer

to tubular fluid samples from loops of Henle.

The Range of Linearity for the Calibration Curves Standard solutions for measurement of Na, CI, P, and Mg signals (H series) consist of

a mixture of NaCl , KH2 P04 and MgCl 2 , 6H2 0 salts in constant percentage, diluted to vary the concentrations by a factor of 10. Standard solutions for measurement of Ca and K (G series)

consist of solutions of 100 mM/1 NaCl, plus concentrations of CaCl 2 and KC1 varying by a 113
factor of 20. Details are given in Table 3. Aside from the necessary precautions to insure stability of the counting rates of the elements, practical considerations guided the choice

of the composition of the standard solutions: 1) calcium and phosphorus tend to precipitate together when their concentrations increase, so that each is present in only one series; 2) only two elements of atomic number less than 20 can be measured simultaneously

with our microprobe; 3) these two elements are chosen according to the ranges of crystal spectrometers and the required analysis time. Table 3. Composit ion of the standard solutions.

NaCl KH 2 P0 4 MgCl 2 Total Ha CI Mg K P H et 0

sol utions 6H2 0 dry mass

mM/

mM/1 mM/1 g/i % % % % % %

1 20 1 1 1.48 31.1 52.8 1.6 2.7 2.1 9.8

2 50 2.5 2.5 3.69

3 100 5 5 7.38

4 150 7.5 7.5 11.07

5 200 10 10 14.76

NaCl KC1 CaCl 2 Total Na CI K Ca

G solutions dry mass

mM/1 mM/1 mM/1 g/1 % % % %

1 100 1 1 6 03 38 1 60.6 0.65 0 66

2 100 2 2 6 22 37 0 60.45 1.26 1 29

3 100 5 5 6 77 34 0 60.2.9 3 0

4 100 10 10 7 70 29 9 59.8 5.

5 2

5 100 20 20 9 55 24 1 59.3 8.2 8 4

1. Scanning electron microscope images of standard solutions

After lyophi 1 ization, the standard solutions and the biological fluids appear as innumerable submicron size crystals distributed over a circular surface. Photographs were

taken of the samples with a Cambridge Stereoscan scanning electron microscope operated at

10 kV, with a sample current measured on the support of 5 x 10 12 A. The resolution is 25

nm. The holder was tilted at 30 degrees.

H series . Figure 13 shows the final appearance of samples with a volume of 0. 08 nl . It is to be noted that the sample surface increases with dry mass for the first two solu- tions and then remains constant for the last three solutions. The mean value of the sample

mass thickness is clearly only a rough estimate of the mass thickness, as samples are com- posed of piles of discrete crystals. Figure 14 shows a picture of those samples at higher magnification. The size of the discrete crystals ranges from 25 nm to 150 nm, independently

of mean mass thickness. Thus, the increase in mass thickness is manifested by a higher

number of particles per unit of surface area. Furthermore, the number of crystals per unit

of surface is smaller at the extreme periphery than in the center. Figure 15 shows pictures

taken of 0.3 nl volumes of the same solutions. When the volume increases, the sample area

increases, so that the increase in mean mass thickness is not proportional to the increase

in volume. At higher magnification (figure 16) the range of crystal size is seen to be the same as that of samples of 0.08 nl volumes. For the 0. 3 nl samples, the increase in the mass thickness is due to a higher number of crystals per unit of surface area.

114
X 700 v = 008nl lOprn

Eo = lO kV 6= 3Q 1= Sx10~ 2A

Figure 13. SEM (scanning electron microscope) images of 0.08 nl of H solutions; magnification X700.

115
! 1 6
X.700 v = 0.3nl 10 pm

117
0.005 mg/cm2

0.035 mg/cm 2

v = 03nl X 14,000 | | 1 pm

Figure 16. SEM images of 0.3 nl of H solutions; magnification X14,000. Left: periphery of the samples; right: center of the samples.

G series . The five standard solutions (G series) differ in appearance from those of

H series and from each other (figure 17). The surface is smaller at equivalent volumes

than for H solutions. This is due to the lack of phosphate ion - this ion reduces surface

tension of a solution. The picture at higher magnification (figure 18) shows that, in contrast to what occurs in samples of H series of constant composition, the size of the crystals varies as the concentrations of Ca and K increase; the size of crystals increases

from a range of 25-150 nm (lowest standard) to a range of 200-500 nm (highest standard). Figures 19 and 20 represent samples 0. 3 nl in volume. The range of crystal size is the same as that with the smaller pipette volume for each solution. The increase of mass thickness is associated with a corresponding increase in the number of particles per unit

of surface area. Again the number of crystals per unit of surface is smaller at the extreme periphery than in the center.

118
X700 M 10pm v=0.08nl

E 0= 10kV I=5x10-12 A 9=30°

0.012 mg/cm2 0.014 mg/cm2

0.015 mg/cm2 0.015 mg/cm2 NaCI IOOmM/1

CaCI2

-, 1,2,5 , IO, KCI J20mM/l

0 . 022 mg/cm2 Figure 17. SEM images of 0.08 nl of G solutions; magnification X700.

119
X 14,000 | ,1pm v=0.08nl
121
X 14000 | (1[Jni v=0.3nl

Figure 20. SEM images of 0.3 nl of G solutions; magnification X14 ,000.

These observations show that the size of the crystals seems to depend upon the composition of the solution independently of its dry mass. The increase in dry mass is associated

with an increase in the number of crystals per unit of surface area; moreover the number of crystals per unit of surface area is larger in the center than at the periphery of the samples.

2. Experimental range of linearity of calibration curves

The range of linearity of calibration curves is shortened by electron and/or x-ray absorption [11]. Electron absorption, which causes saturation curves for the thickest

samples, is suppressed by increasing accelerating voltage. X-ray absorption depends on the energy of the line and on the matrix; the loss of linearity of the calibration curves cannot be corrected by an increase of the accelerating voltage. Experimentally, the calibration curves are linear at 10 kV for a mass thickness up to 0.07 mg/cm2

, and at 12 kV for a mass thickness up to 0.09 mg/cm2. (For a given solution,

the final mass thickness can be varied by changing the volume of the sample and the hydrophilic property of the holder surface - the latter is accomplished by using chloroform

to remove grease). It is important to note that calibration curves are linear for solu- tions of 400 mi 11 iosmol s/kg water or less, i.e. approximately iso-osmotic or hypo-osmotic

to mammalian plasma. Some fluids, notably those of the renal medulla, are hyper-osmotic.

It is necessary to reduce their osmolality by diluting them with water.

122
To investigate the extent of linearity of calibration curves, solutions with H1-H5 and composition and increasing dry mass are used. The surface area of those samples is arly constant, so that their mass thickness increases with the dry mass. The samples are radiated with discrete high voltage values (12 kV - 15 kV - 20 kV - 25 kV) in a CAMECA

-46 microprobe with a 18° take-off angle.

For each element, the measured intensity is converted to "apparent concentration" by

•near extrapolation of the calibration curves of figure 1 to the higher concentrations

dicated in figures 21 and 22. This "apparent concentration" is reported as a function of

e real concentration for the different high voltage values and for any element on the gures 21 and 22. The deviation from linearity (represented by the continuous line) is st marked for the low voltage values, where a saturation effect is obtained for each

ement. When the voltage increases, the measured intensities are proportional to concenation within a larger range, especially for elements with higher atomic numbers.

a 25kV ,20kV ,l5kV *12kV 0.3 nl llOyum Na = 31.17. CI = 52.8% P = 2.1% Mg = 1.6 % K=2.6% H and 0 = 9.8 %

200 £00 600 800 1 000 1200

*~ 10 20 real concentration mM/l

II gure 21

1

in

The apparent concentration, measured by extrapolation of calibration curves like those of figure 1, is shown as a function of the actual for H solutions of increasing dry mass.

123
I = 300 nA «j) = 110yum v = 0.3 nl o25kV 20kV Al5kV v12kV llOyum

Curves as depicted in figures 21 and 22 cannot be used to correct for deviation fron linearity, since they vary from one preparation to another, depending on the surface area of the samples. The ratio of the apparent to actual concentration has been investigates

for each element at different accelerating voltages as a function of the calculated sample mass thickness. For each element a curve is then obtained, which indicates the lack o1 linearity of the extrapolated calibration curves as a function of the sample mass thickness

and of voltage (figures 23 and 24). At 12 kV the deviation from linearity of the extrapolatec calibration curves is the same for all the elements. At 15 kV the deviation from linearity

starts below 0.15 mg/cm2 for Na and Mg, and at higher mass thickness for other elements. At 25 kV, the measured intensities of CI, K, Ca, and P are still proportional to the con-| centration for an estimated mass thickness of at least 0.3 mg/cm2

, while at the same thickness the curves for Na and Mg deviate by 20 percent from proportionality. This suggests that, at 12 kV, the electron range is the factor limiting the extent of lineai extrapolation of the calibration curves, while at 25 kV, the absorption of the softei x-rays is the limiting factor. As a practical point, when the mass thickness of a sample

is smaller than 0.1 mg/cm2

, even Mg and Na will be measured accurately by extrapolation 01 the calibration curves at 12 kV. When the mass thickness is larger than 0.1 mg/cm2

, onl\ the heavier elements will be measured accurately, provided the accelerating voltage i|S appropriately adjusted to the final mass thickness.

124
•Na=31.1^ aCI=52.8^/ v P-2A %

°Mgr1.6^ K=2.6^/H, Oz9.8^/ 12 kV i 15 kV

'V 1.00

.1 .2 .3 .4 .5 20 kV

.1 .2 .3 4 .5 25 kV

1.00 4

.50 sample mass

~A !2 !3 4 !5 I6*"

thickness mgy'cm

.1 .2 .3 .4 .5

Figure 23. Lack of proportionality of the emerging intensity with the sample mass thickness. Experimental values for samples of the given composition in weight

percent. Ordinate - ratio of apparent to real concentration.

125
=Na =34% CI =60.1 %

12 kV

K = 2.9 %

.1 .2 .3 A .5 .6 20 kV

0 s : * i

sample

0 Ca = 3 %

15 kV

1 2 3 A .5 £

25 kV

thickness mg/cm2

Figure 24. Lack of proportionality of the emerging intensity with the sample mass thickness. Experimental values for samples of G3 composition (weight percent). Ordinate - ratio of apparent to real concentration.

3. Range of linearity of the calibration curves calculated for a thin film

The calculated mass thickness of the sample has a physical 'signification, since the

lack of linearity of the calibration curves is reproducible for a given mean mass thickness. A thin film model can therefore be considered as a theoretical model for those

lyophi 1 ized samples.

The solutions examined in the preceding paragraph mainly contain NaCl. The electron

energy distribution is therefore calculated within a NaCl matrix and for the same voltages experimentally examined (12 kV - 15 kV - 20 kV - 25 kV), according to a Monte Carlo process

[3] dealing with 10,000 electrons. The details of the computer program were reported earlier [6,7]. The electron range is divided into 20 to 50 steps, according to the accelerating voltage value, to get discrete mass thickness of approximately the same values. We define as relative intensity the ratio of the emerging intensity from a film of a given mass thickness to the intensity emerging from a film 0.025 mg/cm2

, corrected for the mass thickness of the samples. The relative intensity is calculated for each element, in each solu- tion (H and G3) and for discrete mass thickness values, and reported in figures 25 and 26

as a function of the mass thickness. These ratios are defined identically to the ratios reported in figures 23 and 24; they should be equal to one if the emerging intensity is pro- portional to mass thickness, i.e. proportional to the amount of element in the analyzed volume. The scales are the same for both series of graphs. Note that, qualitatively, the loss

of proportionality of the emerging intensity to the mass thickness, as latter increases,

is in the same order of magnitude for experimental results and for the thin film model.

126
.50

-1.00-a a-

> .50-

.3 .4 .5 .6

~o .50

o - —

sample mass thickness

.5 Figure 25. Lack of proportionality of the emerging intensity with the sample mass thick

ness. Theoretical values for a thin film. Ordinate - for definition o relative intensity, see text.
i.oc_ Na=34%\ a CI =60.1 %

<y <k 12 kV

420 kV

sample thickness mg/cm2

Figure 26. Lack of proportionality of the emerging intensity with the sample mass thickness. Theoretical values for a thin film of the given composition. Ordinate

- for definition of the relative intensity, see text.

H solution . At any voltage, both chlorine and phosphorus behave differently from sodium and magnesium. They exhibit a shoulder, characteristic of the x-ray depth distri- bution function, which does not appear in the experimental results. The emerging magnesium

and sodium intensities decrease when the mass thickness increases, but the effect is greater for magnesium which has a higher absorption coefficient than sodium. The phosphorus

and chlorine signals should be enhanced at 12 and 15 kV, contrary to what is experimentally

observed, while at 20 and 25 kV, the emerging intensities should be roughly proportional to sample mass thickness up to 0.4 mg/cm2

, which is experimentally observed. For sodium and magnesium, the lack of proportionality of the emerging intensity with the sample mass thickness is depicted by the thin film model at 12 and 15 kV; while, at 20 and 25 kV, the

lack of proportionality of the emerging intensity with the sample mass thickness is not

so severe as predicted by the model. G3 solution . Chlorine and sodium exhibit the same theoretical response as in the H solution (compare figures 25 and 26). The potassium and calcium lines follow very closely

that of sodium at 12 kV, and, when the voltage increases, fall intermediately between the chlorine and the sodium curves. For chlorine, the difference between experimental and theoretical results is the same as in the H solution. For sodium, the theoretical model again predicts less absorption than that experimentally observed at 12 and 15 kV, and more absorption than that observed at 20 and 25 kV. The potassium and calcium experimental

128
suits agree with the model at 20 and 25 kV, but disagree at 12 and 15 kV where experintal results decrease more rapidly with the mass thickness than predicted by the model. 2 The results from thin film model show the influence of x-ray absorption upon the loss proportionality of the emerging intensity as mass thickness increases. The small fferences between experimental and theoretical results can be explained by morphologic

pearance of the samples - their scanning electron microscope images show piles of crystals

ose size is a function of the solution composition. From these images, it seems reasonle to consider the samples as a series of units of various thickness, with a statistical

stribution in thickness. Because the experimental curves do not exhibit the shoulder

eoretically predicted for the heavier elements (CI, K, Ca, and P), nor a so severe

crease of the emerging intensities for the lighter elements (Na and Mg), it seems

obable that samples contain both units of low mass thickness and those of high mass

ickness, with the former in majority. The next approach to a theoretical model should

gin by considering a statistical distribution of the repartition of mass thickness within

e samples. Conclusion

From this study, it appears that simply obtaining linear calibration curves linking

asured intensity and concentration of an element is not sufficient to insure the accuracy

electron probe analysis of fluid. In addition, we must consider identity of the degree

oxidation and stability of the counting rate. Taking into account these factors permits

ie to achieve calibration curves whose range exceeds that normally encountered in biologiil specimens, particularly for P, CI, K, and Ca at voltage 20-25 kV. To predict the

feet of matrix on the proportionality range, a theoretical model is necessary. The thin

lm model is a good beginning but it needs to be improved. Among other things, the model

•eds to take into account the heterogeneity in mass thickness of samples, as revealed by

ie secondary electron pictures. This will require more study of the distribution and

ze of particulates constituting the sample. Such a theoretical model, by predicting the

ifluence of matrix on emerging intensities, will serve as a guide in the preparation of

.andard solutions, and should further advance the systematic application of the electron

croprobe to the analysis of biological fluid.

We thank Dr. Kurt Heinrich, Dr. Rex Jamison, and Dr. Christian de Rouffignac for Mtical reading of our manuscript.

>ee paper by Dale E. Newbury et al., Monte Carlo Electron Trajectory Simulation - an Aid

for Particle Analysis, this book.

129
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, 369, 95 (1977).

[18] Roinel , N. , Richard, J. P. , Robin, G. , and Morel , F. , J. Microscopie , 18, 285 (1973\

[19] Roinel, N. , J. Microscopie Biol . Cell . , 22, 261 (1975).

[20] Roinel, N. , Proc. of the XXVIIth International Congress of Physiological Sciences,

XII , 144 (1977).

130
ational

oecial ociety,

Bureau of Standards Special Publication 533. This Publication Originated from a Session on Particle Analysis, 13th Annual of the Microbeam Analysis

Ann Arbor, MI, June 22, 1978. (Issued April 1980)

APPLICATION OF AUGER-ELECTRON SPECTROSCOPY AND X-RAY PHOTOELECTRON

SPECTROSCOPY TO THE CHARACTERIZATION OF POLLUTANT PARTICLES 1

C. J. Powell National Bureau of Standards Surface Science Division

Washington, D. C. 20234

A short review is given of the use of Auger-electron spectroscopy

(AES) and x-ray photoel ectron spectroscopy (XPS) for surface charac- terization of pollutant particles from the atmosphere. The significance

of the surface composition is emphasized with reference to catalytic transformations of gaseous S0 2 and NO and to the possible adverse

effects on human health of sulfates? toxic trace elements, and carcinogenic polycyclic aromatic matter. AES and XPS have been used to identify elements present on particles and the variation of composition

with depth. XPS has been used to identify the chemical state of surface

species, to identify toxic trace elements, and to study catalytic

reactions involving gaseous pollutants. Areas where further work and developments are needed are (1) kinetic measurements for the significant

heterogenous transformations of gaseous pollutants on particle surfaces,

(2) analyses of aerosol and particle surfaces under ambient atmospheric

rather than vacuum conditions, and (3) surface analysis of selected

individual particles.

Over the past two decades there has been considerable public concern over pollution of

-he atmosphere. Attention was focussed initially on gaseous pollutants, but it is now

istablished th-at air pollution by particulate matter is also a serious problem [1-3] 2

. Par- ticulate pollutants from coal-fired power plants have been shown to have adverse effects on

luman health, vegetation, and materials [1-3]. Since this nation and others will depend on

energy generated at coal -fired power plants in the next several decades to a greater extent

.nan now, it is clear that the properties of pollutant particles and the nature of reactions

if gaseous pollutants on particles need to be better understood. Particulate emissions from

)ther sources (asbestos materials, automobiles, industrial furnaces) may also be significant

This article is a brief review of the applications of Auger-electron spectroscopy (AES)

iind x-ray photoel ectron spectroscopy (XPS) or electron spectroscopy for chemical analysis

^ESCA) for the characterization of the surface regions of particulate pollutants from the

atmosphere. The significance of surface characterization is described in Section 2, and the :haracteristics of AES and XPS are summarized in Section 3. Applications of AES and XPS for

oarticle characterization are described in Section 4; more detailed descriptions of the use

3f AES and XPS for surface analyses of pollutant particles are given in two recent review

articles [4-5]. Finally, in Section 5, there is a discussion of outstanding problems and a description of several recent instrumental developments which could be useful in future

investigations.

L Work carried out at the National Bureau of Standards under the sponsorship of the U.S Department of Energy Division of Biomedical and Environmental Research.

2 Figures in brackets indicate the literature references at the end of this paper.

131

Introduction

.1-3].
Nature of the Problem

A specialist group has calculated the probability of deposition of particles in dif- ferent regions of the human respiratory tract as a function of particle diameter [6]. For particle diameters greater than 10 urn, approximately 80 percent or more of the particles are deposited in the nasopharyngeal compartment. Deposition in the tracheobronchial region has a low probability (<10%) almost independent of particle size for diameters greater than 0.1 pm; the probability does increase to 30 percent for a particle diameter of 0.01 urn. The probability of deposition in the pulmonary compartment increases from about 10 percent for a particle diameter of 10 urn to 60 percent for a diameter of 0.01 urn. Particles with diameters

less than 10 pm can therefore be inhaled deeply into the human lungs and have to be considered

in epidemiological studies. Although the actual mechanism of deposition is primarily

dependent upon the particle size, the shape of a particle can also affect the efficiency of

its deposition [6]. The size range of pollutant particles in the atmosphere to be considered

are, first, the so-called primary particles with diameters typically between 1 and 20 pm which are characteristic of an emission source and, second, the secondary particles with

diameters less than 1 pm which are produced as a result of atmospheric reactions [1]. An analysis of the recent literature concerned with investigations of particle pollutants in the atmosphere yielded the following conclusions [7]. (1) Smaller particles have longer residence times in the atmosphere.

(2) Fine particles, of diameter less than 1 pm, can be transported hundreds to thou- sands of kilometers downward from their point of formation and, because of their high surface/volume ratio, are capable of adsorbing significant quantities of toxic gases.

(3) Toxic elements such as Pb, Cd, Tl , V, and Ni have higher relative concentrations in smal ler particles.

(4) Sulfur dioxide can be catalytical ly converted to sulfate species on particle surfaces.

(5) Fine particles can act as transport vehicles for adsorbed and reacted gaseous

pollutants; synergistic effects on human health are significant [1]. (6) Polycyclic aromatic matter (PAM) is formed in combustion processes and is condensed

on particle surfaces; some PAM is carcinogenic.

The nature of the surfaces of pollutant particles and, in particular, the surface composition

are important for the following reasons [4,5,7].

(a) Gaseous pollutants in the atmosphere such as S0

? and NO can be catalytical ly converted to sulfate and nitrate species.

(b) Toxic elements can be located in greater relative concentrations in the surface

region of a particle than in the bulk.

(c) Carcinogenic PAM may be on the surface.

(d) The surface composition of a particle inhaled into the human respiratory system may

have a greater effect on health than the average composition for the entire particle.
Specific questions which should then be addressed in the characterization of particle

-faces are [7]: (i) To what extent is the surface composition different from the bulk composition?

(ii) To what extent is the surface enriched in toxic elements or carcinogenic mole- cules?

(iii) How does the surface composition correlate with particle size (and, perhaps, with method of formation and subsequent history)?

(iv) What are the reaction products and rates for various gases and gas mixtures

interacting with particles?

Surface Analysis by AES and XPS There are four techniques presently in common use for surface analyses of a great

'iety of samples: AES, XPS, secondary-ion mass spectroscopy (SIMS), and ion-scattering

?ctroscopy (ISS) [8]. The application of SIMS to particle characterization is described

a companion article by Newbury but, to the author's knowledge, there has been no appli-

:ion in this area of ISS. The surface sensitivity of AES and XPS is due to the very short inelastic mean free

th (IMFP), typically 5 to 20 A , of the electrons of interest in the sample [9]. The

formation volume, that region of the sample from which most of the detected electrons

iginate, is a function of the measurement configuration as well as properties of the

uple (primarily the IMFP). For the particulate samples of interest here, the information

lume is very difficult to define because of the structural complexities which can be oected and the likely lack of chemical homogeneity of the information volume for a par-

:ular measurement. Scanning electron micrographs of coal-derived fly-ash samples from

ectrostatic precipitators, for example, show a great variety of structural forms [10]. Ideally, it would be desirable to examine the surface composition of different

dividual particles. In practice, tradeoffs have to be made between spatial resolution,

isitivity for the detection of trace elements, and damage to the sample during the course

the measurement. Commercial AES instrumentation is now available with which submicroter spatial resolution can be obtained. For particulate samples of possibly poor elecical and thermal conductivities, charging, and electron-beam-induced damage [11] can

se severe problems if high spatial resolution was attempted. For XPS, damage by the

ray beam is believed to be minor, but the spatial resolution achievable with commercial

strumentation is typically a few millimeters. Sensitivity for the detection of trace

aments can be improved, in principle, by increasing the measurement time but, in practice,

e potential gain is limited by beam-damage effects, adsorption on the sample of moleles from the ambient vacuum, and the stability of the equipment. Applications of AES and XPS for Particle Characterization

A brief description will be given here of applications of AES and XPS for surface

aracterization of particles collected from power plants and the atmosphere. This descripon is intended to be a guide to the relevant literature and to the nature of the AES and

S investigations rather than a comprehensive summary or review [4,5].

T. Novakov has pioneered in demonstrating that XPS is useful for particulate characrization, in speciation studies of particles, and in studies of heterogenous reactions

particle surfaces [4]. He and his coworkers have been instrumental in showing the portance of surface characterization of pollutant particles for the atmosphere and the

wer of XPS (and, by implication, other methods of surface analysis) for characterizing

rticle surfaces and surface processes.

Cheng et al. [12] have used AES to characterize fly ash from the stacks and precipitars of both coal-fired and oil-fired power plants. The Auger spectrum for the sample from

133
the oil-fired plant showed a strong vanadium signal in addition to peaks for C, S, 0, and

Mg. The AES data for the sample from the coal-fired plant showed structure due to C, S, 0, Ca, N, Fe, and Na. Linton et al . [13] have measured AES depth profiles, i.e., changes in the relative

strengths of different elemental signals as the surface was eroded by sputtering, for

fly ash samples collected from coal-fired power-plant stacks. The signals due to K, Na, and S were enhanced in a surface region of approximately 30 K depth compared to those for deeper regions while the signals due to Fe, Al , and Si did not vary appreciably with depth. Lindfors and Hovland [14] have used both AES and XPS to detect elements present on the surface of fly ash from the precipitator of a coal-fired power plant. These authors detected Al , Si, K, C, 0, Fe, Na, Ca , S, CI, and N on individual particles from different parts

of the precipitator, with some elements being present in one region and not in the other. Many of the elements were detected also by XPS analysis of an assemblage of particles.

AES depth profiles for a particle showed a predominance of Si and 0 while XPS depth profiles

for an assemblage from the precipitator outlet showed surface enrichment of C, S, and Na and surface depletion of Al , Fe, and Ca. Keyser et al. [5] have reported AES and SIMS depth profiles for large (>10 urn) auto- mobile exhaust particles. The AES measurements showed an appreciable surface enrichment

of Pb and Br and a lesser enrichment of S. XPS has been used by Hulett and coworkers in several investigations of fly-ash particles. In one study, fly-ash samples from the precipitators of several power plants were

analyzed and it was found that the Al and Si XPS signals were enhanced, while the S signal due to sulfate species was diminished after the samples were leached with rainwater to simulate the effects of rain [15]. Grieger [16] has collected particle samples from urban, suburban, and rural areas

both 1 day and 14 days after rain. XPS measurements showed that the particles from the

rural area had appreciably smaller concentrations of Pb, S, and N than the other areas, and that the suburban area had a lesser amount of Pb than the urban area but comparable amounts

of S and N. Rain washed away some of the N and S compounds. Novakov and coworkers have performed many XPS studies of particle samples from the atmosphere [4]. In an early paper [17], the small "chemical shifts" of XPS lines for

N and S were analyzed to give information on the relative amounts of nitrate-, ammonium-,

amino-, and pyridi ne-nitrogen compounds and of sulfate and sulfite compounds on aerosols of different sizes and collected at different times during a day in Pasadena. Further XPS work [18]_ showed the presence of seven separate chemical species of sulfur (S0 3 , S0 4

2

, S0 2 , S0 3

2

, S, and two sulfides) on atmospheric aerosols. Chang and Novakov [19] conducted

laboratory experiments in which NO and NH 3 were reacted with soot and graphite at various

temperatures. XPS measurements showed the presence of ammonium complexes at ambient tem- peratures while amines, amides, and nitriles were produced at higher temperatures. Com- parisons of this data with XPS measurements of aerosol particles led to the assignment

of three nitrogen features as being due to ammonium, amine and/or amide, and nitrile

species. A similar XPS investigation [20] involving the reaction with S0 2 with soot showed

that soot particles in the atmosphere can play a major role in the catalytic conversion of

S0 2 to sulfate species. Barbaray et al . [21] have used XPS to study the oxidation of S0 2 over V 2 0 5 particles

and carbon. There was little direct interaction between S0 2 and V 2 0 5 for temperatures

below 150 °C, but at 200 °C oxidation proceeded to adsorbed sulfate and sulfur trioxide.

In the presence of N0 2 or H 2 0, however, sulfate is formed at 25 °C. XPS has been used by Campbell et al . [22] to examine a fly ash designated SRM 1633

by the National Bureau of Standards. These authors determined the oxidation states of a number of elements and found that the concentrations of Na, C, 0, o and S decreased and the concentrations of Si, Al , and Fe increased when approximately 50 A of the sample was re- moved by sputtering.

134
Allegrini and Mattogno [23] have examined particulate emissions from several sources

ith XPS. They have identified the chemical states of S and N in the samples from the chemcal shifts of the elemental XPS lines. Finally, Jach et al . [24] have made XPS analysis of several fly-ash and urban dust

amples. By accumulating data with a multichannel analyzer over limited spectral regions

nd with multiple sweeps, these authors were able to detect some 30 elements, some of which

ere not detected in "bulk" analyses by neutron activation. Amongst the elements detected

In a sample from one source were Si, Al , K, Fe, Ca, Ti , Na, As, Co, Bi , CI, Sr, Ba, Zn, V,

r, P, Sb, Mo, Pb, and Ni. Concluding Remarks

A description has been given of recent applications of AES and XPS to determine the

iurface composition of pollutant particles from the atmosphere. These techniques have the ensitivity to detect elements present in the outermost ~ 10 & of a solid sample and, by

emoval of surface atoms by sputtering, to determine the variation of composition with

epth. AES has the capability to measure individual particles although it has yet to be :emonstrated that this can be done routinely without significant damage to the sample. The surface composition of pollutant particles is important for several reasons. First,

aseous pollutants such as S0 2 and NO can be catalytically converted to sulfate and nitrate

pecies on the particle surfaces. Sulfates, in particular, have been associated with

dverse health effects and damage to vegetation and materials. Second, toxic elements

fay be located in the surface region of a particle to a greater relative concentration than

he bulk. Third, carcinogenic polycyclic aromatic matter (PAM) may be in the particle

urface. The amounts of toxic elements and PAM on inhaled particles need to be known for ealth-effects studies.

AES and XPS have been used to identify elements present on particle surfaces and to etermine the variation of composition with depth. XPS has been used for the identification

f chemical species, the detection of toxic trace elements, and the study of catalytic

onversions of gaseous pollutants. These studies have demonstrated the basic feasibility

f the approach and need to be extended to the examination of pollutant particles from

ifferent regions and to the acquisition of kinetic data for the more important reactions. There are two areas where improvements in measurement capability would be valuable,

irst, surface analyses by AES and XPS need to be made with the sample in an ultrahigh

acuum. Volatile species can be lost from the sample surface during pumpdown, although this

an be minimized by appropriate cooling of the sample [19]. It would be very desirable

io be able to measure surface composition, with a sensitivity and specificity comparable to

hat of AES and XPS, of aerosols and particles at atmospheric pressure. One approach is

o use particle-induced x-ray emission (PIXE) with MeV proton beams brought from an ccelerator vacuum through a thin window to a sample in a helium environment at or near tmospheric pressure [25,26]. Light elements cannot be detected by PIXE, but proton- lastic-scattering can be used for this purpose [25]. Although PIXE does not have the

urface sensitivity of AES and XPS, it could be used to detect changes in elemental concenrations as environmental or reaction conditions (partial pressure of S0 2 or N0

x

, humidity,

emperature, etc.) are varied. An alternative approach is to use a combination of x-ray

nd electron spectroscopies that may be feasible in the near future as more intense sources

f variable-energy x-rays become available [27].

A second area where instrumental improvements would be desirable is in surface

nalyses of selected individual particles. Analyses of this type can now be performed by ES and SIMS, but beam-damage effects may limit the scope of the analysis (e.g., the detecion of trace elements). Several techniques could be useful in the future. First, the

damage products" of electron bombardment, namely ions, could be detected as in SIMS [28]. econd, the scanning XPS system proposed by Cazaux [29] and demonstrated by Hovland [30]

iould be ideally suited for XPS analyses of selected particles; this technique has a patial resolution of about 10 urn. Finally, the photoelectron microscope developed by riff ith et al . [31] can detect ~ 10 urn particles. By varying the wavelength of the xciting ultraviolet radiation, it might be possible to detect and selectively image

urface ligands with differing work function or ionization potential.
REFERENCES

[I] Burchard, J. K. , J. Air Pollution Control Assoc. 24, 1141 (1974); ibid. 25, 99 (1975); Harrington, R.E., J. Air Pollution Control Assoc. 24, 927 (1974); Fennelly, P. F. , J. Air Pollution Control Assoc. 25, 697 (1975).

[2] Ferris, B. G. , J. Air Pollution Control Assoc. 28, 482 (1978); Lave, L. B. , and Seskin, E. P., American Scientist 67, 178 (1979).

[3] Rauch, R. J., Chemical and Engineering News 57, 25, 47 (1979); Crandal 1 , R. W. , ibid . 57, 29, 51 (1979); Barber, W. C. , ibid. 57, 34 (1979); Lave, L. B. , and Seskin, E. P., ibid . 57, 38, 49 (1979); Comar, C. L. , ibid . 57, 42, 48 (1979).

[4] Novakov, T. , Chang, S. G. , and Dod, R. L. , in Contemporary Topics in Analytical and Clinical Chemistry, edited by D. M. Hercules, G. M. Hieftze, L. R. Snyder, and

M. A. Evenson (Plenum Press, New York, 1977), Volume 1, p. 249. [5] Keyser, T. R. , Natusch, D. F. S. , Evans, Jr., C. A., and Linton, R. W. , Environ.

Sci. and Tech. 12, 768 (1978).

[6] Air Quality Criteria for Particulate Matter, National Air Pollution Control Administration Publication No. AP-49 (U. S. Department of Health, Education, and Welfare, Washington, D. C. , January, 1969), Chapter 9. [7] Powell, C. J., Surface Composition of Particulate Pollutants in the Atmosphere, unpublished Issue Study, May 1976.

[8] Powell, C. J., Applications of Surf. Science!, 143 (1978).

[9] Powell, C. J., Surf. Science 44, 29 (1974).

[10] Fisher, G. L. , Chang, D. P. Y. , and Brummer, M. , Science 192, 553 (1976).

[II] Isaacson, M. S. , in Principles and Techniques of Electron Microscopy, edited by

M. A. Hayat (Van Nostrand Reinhold Co., New York, 1977), Volume 7; T. E. Made'y and

J. T. Yates, Jr. , to be published.

[12] Cheng, R. J., Mohnen, V. A., Shen, T. T. , Current, M. , and Hudson, J. B. , J. Air Pollution Control Assoc. 26, 787 (1976); Menotti , F. , Hudson, J. B. , Cheng, R. J., and Mohnen, V. A., in Proceedings of the Conference on Carbonaceous Particles,

Berkeley, Calif., March 20-22, 1978 (Lawrence Berkeley Laboratory Report), edited by

T. Novakov, to be published.

[13] Linton, R. W. , Loh, A., Natusch, D. F. S. , Evans, Jr., C. A. and Williams, P., Science 191_, 852 (1976); Linton, R. W. , Williams, P., Evans, Jr., C. A., and Natusch, D. F. S. , Anal. Chem. 49, 1514 (1977).

[14] Lindfors, P. A., and Hovland, C. T. , in Environmental Pollutants, Detection and Measurement, edited by T. Y. Toribara, J. R. Coleman, B. E. Dahneke, and I. Feldman (Plenum Press, N. Y. , 1978), p. 349. [15] Hulett, L. D. , Dunn, H. W. , Dale, J. M. , Emery, J. F. , Lyon, W. S. , and Murty, P. S.

,

in Measurement, Detection and Control of Environmental Pollutants, Proceedings of a Symposium, Vienna, 15-19 March 1976 (International Atomic Energy Agency, Vienna,

1976), p. 29. [16] Grieger, G. R. , Am. Laboratory 8, 77 (April, 1976). [17] Novakov, T. , Mueller, P. K. , Alcocer, A. E. , and Otvos, J. W. , J. Colloid Interface

Sci. 39, 225 (1972).

136
[18] Craig, N. L. , Harker, A. B. , and Novakov, T. , Atmos. Environments, 15 (1974).

[19] Chang, S. G. , and Novakov, T. , Atmos. Environment 9, 495 (1975).

[20] Novakov, T. , Chang, S. G. , and Harker, A. B. , Science 185, 259 (1974).

[21] Barbaray, B. , Contour, J. P., and Mouvier, G. , Atmos. Environment U, 351 (1977); Environmental Sci. and Tech. 12, 1294 (1978).

[22] Campbell, J. A., Smith, R. D. , and Davis, L. E. , Appl. Spectrosc. 32, 316 (1978).

[23] Allegrini, I., and Mattogno, G. , Sci. Total Environ. 9, 227 (1978).

[24] Jach, T. J. , Powell , C. J. , Small , J. A. , and Newbury, D. E. (to be published).

[25] Ziegler, J. F. , Physics Today 29, 52 (November, 1976).

[26] Deconninck, G. , Nucl. Instr. Methods 142, 275 (1977).

[27] Powell, C. J., J. Vac. Sci. Tech. 15, 549 (1978).

[28] Joshi, A., and Davis, L. E. , J. Vac. Sci. Tech. 14, 1310 (1977).

[29] Cazaux, J., Rev. Phys. Appl. 10, 263 (1975).

[30] Hovland, C. T. , in Proceedings of the Seventh International Vacuum Congress and

the Third International Conference on Solid Surfaces, edited by R. Dobrozemsky,

F. Rudenauer, F. P. Viehbock, and A. Breth (R. Dobrozemsky et al., Vienna, 1977),

Vol. 3, p. 2363.

[31] Dam, R. J., Kongslie, K. F. , and Griffith, D. H. , Photochemistry and Photobiology 22, 265 (1975).

137

tional Bureau of Standards Special Publication 533. This Publication Originated from a ecial Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

ciety, Ann Arbor, MI, June 22, 1978. (Issued April 1980)

SECONDARY ION MASS SPECTROMETRY FOR THE ANALYSIS OF SINGLE PARTICLES

Dale E. Newbury

National Bureau of Standards Center for Analytical Chemistry

Washington, D. C. 20234 Introduction

When particle aggregates are examined by means of electron probe microanalysis, it is equently observed that the compositions of individual particles vary markedly, even when

e sample originates from a single source (l) 1

. In examining a single micrometer-sized

rticle by electron beam excitation, virtually all of the particle is sampled and the uposition so determined is an average over the sampled volume. The next level of inquiry

to consider possible heterogeneity within the particle itself, i. e. , to determine the crostructure of the particle. When the sampling volume by electron excitation is a all fraction of the particle volume, heterogeneities in the composition from place to

ace in a single particle are frequently observed. Another possible microstructural

ature of interest is the distribution of constituents with depth in a particle. That

, does the surface differ in composition from the interior? The electron interaction

lume is of the order of 1 pm3

, with a sampling depth of 1 pm or greater, which makes

parate analysis of the surface and the interior virtually impossible. To answer questions

ch as this, the technique of secondary ion mass spectrometry offers special capabilities

r particle analysis. Secondary ion mass spectrometry (SIMS) has evolved into a powerful technique for the

alysis of a wide range of specimens of interest in the physical and biological sciences

d in various technological applications (2,3,4). In the SIMS technique, a beam of enertic ions is used to bombard a target, causing the process of sputtering, in which indivual atoms or clusters of atoms lying near the surface are ejected. A fraction of the uttered particles, the so-called secondary ions, is ejected in a charged state. The

condary ions are collected and mass analyzed in a magnetic spectrometer or a quadrupole

ss filter. Instrumentation for SIMS has been described extensively in the literature

,5).Because of the shallow sampling depth of the secondary ion signal, which originates

om a depth of about 1-2 nm, SIMS is capable of obtaining information from the surface

a target. Along with Auger electron spectroscopy (AES), x-ray photoel ectron specoscopy (XRS), and ion scattering spectroscopy (ISS), SIMS is considered one of the major

rface analysis techniques (5). In addition, since the primary ion beam can be focussed

I form a small probe on the sample, restricting the region sampled to an area with dimenons in the micrometer range, SIMS can also be used as a microanalysis technique, with a nimum sampling volume of 0.01 ym 3

. SIMS offers a number of advantages for the study of individual particles, including

e capabilities for detection of all elements, isotope ratio measurements, compound

tection, depth profiling, and ion imaging of specific constituents. Each of these

pabilities will be described in this paper with special reference to particulate studies.

igures in brackets indicate the literature references at the end of this paper.

139
Elemental Detection

Characteristics

Examination of positive and negative secondary ion spectra from a single urban air particulate, figure 1, reveals the potential of SIMS for characterizing a complicated, multi-element target. All elements in the particle can be detected by SIMS, including

hydrogen. The peaks are characterized by a high signal-to-background ratio. In the case of a major element, the peak-to-background ratio can often exceed 106

:1 per nanoamp of primary ion current. (Note that the background is often independent of the beam current,

so that an increase in the beam current can increase the peak counting rate without sub- stantially affecting the background.) This high peak-to-background is observed for many

elements, and as a result the SIMS technique can be used to realize very low values for

the minimum detection limit. The high sensitivity per unit current makes possible the use

of f inely-focussed primary ion beams. Useful secondary ion spectra of particles can be obtained from targets as small as 1 urn with existing instruments. Improvements in source brightness and ion optics should extend this limit to 0.1 urn in the future. Detection Limits

In considering the minimum detection limit, two factors must be taken into account:

(1) the characteristics of the species of interest and (2) the matrix in which it resides. The minimum detection limit varies considerably from one element to another. The secondary

ion signal is a strong function of the electronic character of the surface region from which the secondary ions are emitted. Under bombardment with oxygen primary ions, those

elements which tend to react strongly with oxygen produce the highest relative signals in the positive secondary ion spectrum. Andersen (6) has demonstrated that the range of sensitivity

for the pure elements is as great as six orders of magnitude, with gold the least sensitive,

and elements such as aluminum and silicon the most sensitive. When several elements are dispersed in a common, oxygen-rich matrix, such as a silicate, the range of relative sensitivity is somewhat compressed. The range of the secondary ion yields becomes smaller,

and therefore the minimum detectable limit shows less variation. In Table 1, a list is compiled of the minimum detectable limit for a variety of elements in a lead-silicate

matrix. For the conditions of beam current employed, which were appropriate to micro- analysis with a beam size of approximately 2 urn, the absolute detection limit is of the order of 1 part per million for many elements in the absence of interferences. Since many

particulates, especially those produced by natural processes, tend to be highly oxidized,

the detection limits given in Table 1 are likely to be appropriate to the analysis of unknowns.

140
141
142
Table 1. Detection Limits in an Oxygen-Rich Matrix

Element

3 Detection Limitb

Li 0. B 6 Mg 0. Al 0. P 23

Ti 0. Cr 1 Fe 2

Ni 3 Gc 4 Zr 0. Ba 4 Ce 2 Eu 5 Ta 12 Th 2

U 2

aAll elements dispersed as solutes in a glass matrix of Si-Pb-0. ^Detection limit for a 1 nA 16 0 ion beam and a 1 sec integration

time taken as the concentration expected to produce three times

the background count rate. Quantitative analysis

Practical quantitative elemental analysis of particles by SIMS can proceed from two distinct approaches: (1) empirical analysis, based on the use of relative elemental

sensitivity factors derived from standards and (2) analysis based on a physical model of secondary ion formation (3,7). Sensitivity factor analysis

A relative elemental sensitivity factor can be defined as: _

(i x /C

x

f x

} S * /R

=

< vw (1)

where i is the measured secondary ion current, C is the atomic concentration, f is the

isotopic abundance of the line measured, x denotes the element of interest and R denotes

a reference element. Relative elemental sensitivity factors are measured from a suite of

known standards for all elements of interest. The reference element R is usually taken as

a matrix element.

143
In the analysis of an unknown, the sensitivity factor can be used to convert a measured

secondary ion intensity ratio, i /i„, into a concentration ratio:

X R S x/R

l R where I = i/f, the total secondary ion signal for all isotopes of an element. By measuring

all elements in a sample, and assuming Kx + C

R = 1 the absolute value of can be determined, and by use of equation (2), all of the C x values

can be found, giving a total analysis of the sample. The accuracy of such a procedure

depends to a great extent on how strongly the sensitivity factors depend on the matrix. Although absolute sensitivity can vary strongly, relative sensitivity is not as susceptible to matrix effects. This is especially true in the case of highly oxidized samples,

in which the sample typically contains 60 atomic percent oxygen. When such a target is analyzed with an oxygen primary ion beam, which further increases the oxygen content, the secondary ions are formed in an oxygen-rich environment, producing a similar matrix despite

differences in the electropositive matrix species. The distribution of errors which has been observed in the actual analysis of samples by the method of relative sensitivity

factors is shown in figure 2. Approximately 50 percent of the analyses fall within a factor of 1.2 of the correct value, and 80 percent within a factor of 2. Physical model

In principle, it should be possible to predict the secondary ion emission from a multi- element target by means of an appropriate model of secondary ion emission, and, consequently

,

to relate measured secondary ion intensities to the composition. A number of models of secondary ion emission are available. The most successful model for describing secondary

ion emission from multi-element oxidic samples is the local thermal equilibrium (LTE)

model (6,8). The LTE model describes the region of secondary ion formation as a dense plasma in thermal equilibrium. The ratio of sputtered ions to neutral atoms in this plasma is related to the temperature and electron density, as well as material parameters

such as ionization potential and partition functions. In applying the LTE model to a practical analysis situation, the temperature and electron density appropriate to the analysis conditions are derived from the measured secondary ion intensities and known concentrations for two elements in the sample. These values of the temperature and electron

density can then be employed to relate the measured secondary ion intensities of the remaining unknown elements to composition. Use of the LTE model thus requires some prior

knowledge of the specimen composition, preferably the compositional values of the major

elements. In this regard, it is not as flexible in application as the sensitivity factor

method.

As an example of the accuracy which can be achieved with the LTE model for oxidic sam- ples, an error factor histogram is shown in figure 3. This histogram has been compiled from analyses of glass standards of known composition, testing various combinations of elements

as "internal standards" for analysis. The distribution of errors is such that about 50 percent of the analyses fall within a factor of two of the correct value, and 80 percent

within a factor of five. Detection of Compounds

In addition to the elemental signals available in the SIMS spectrum, peaks which correspond to molecular consti tutents of a sample are frequently observed. For example,

in the spectrum shown in figure 1, a number of di- and tri-atomic molecules can be observed, including Fe 2 , Cu 2 , SiO, FeO, FeCa, Fe 2 0, Fe 2 Ca. Benninghoven et al. (9) have demonstrated

that complicated organic molecules of a molecular weight as high as 300 can be successfully

sputtered. In order to observe complicated molecules, it is generally necessary to minimize

144
Blind Sample Round Robin

-r-40

(l/F)>2-4

1 case

1/F

0-83^F <V2

0-50<F5 2 57%

91%

F>2«/»

3 cases

Figure 2. Error histogram of quantitative ion microprobe analyses performed by the method

of relative sensitivity factors by four independent laboratories. Specimens: Multi-component silicate glasses.

145
number

(1/F)>5

6 determinations

1/F*

70 NBS Glasses

LTE Analysis

0/0 2

, Si/SiO,

and no oxide F = C(true)/c(LTE)

311 determinations

0-5<F^ 2 53%

0

. 2 <F<5 U%

F> 5

1*2 determinations

Overestimate Underestimate

Figure 3. Error histogram of quantitative ion microprobe analyses with data reduction with

the local thermal equilibrium model. Specimens: Multi-component silicate

glasses.

the damage to the surface caused by prior ion bombardment through the use of low primary

ion current densities. Benninghoven identifies conditions of static and dynamic SIMS

(10). In static SIMS, the current density, typically less than 10'9 A/cm2

, is so low that

any ion striking the surface has a very low probability of striking a site disrupted pre- viously by another energetic ion. The total dose during an experiment is generally less than 10 13 /cm2

, and considering the number of surface sites as 10 15 /cm2

, only about 1/100 of the surface atoms are sputtered. The surface thus remains in an unperturbed or "static"

state. In dynamic SIMS, the current density is in the range of 10"3 A/cm2 or more. The

ion damage to the surface is so extensive that virtually all surface sites will be hit by

ions during recording of the spectrum. The molecules at the surface are thus likely to be broken down during the measurement process, preventing a representative spectrum from being

obtai ned. 146
The current densities necessary to achieve a true static SIMS condition are so low that

order to obtain an adequate total current for practical measurement, about 10

_1

° A, the am size must be of the order of 1 mm diameter or greater. In order to apply a static SIMS periment to the study of particles, it would therefore be necessary to examine aggregates

many parti_cles. In recent experiments with the ion microprobe operating with a current

nsity of 10 6 A/cm2

, midway between true static SIMS (10~ 9 A/cm2) and the dynamic SIMS of « typical high current density ion probe (10 1 A/cm2 ), we have been able to observe molecur spectra from a number of compounds, including glycine and f 1 uorodopami ne , Figures 4(a)

d 4(b). The principal molecular signals were found to include parent molecule species,

agments similar to those patterns seen in the electron impact ionization mass spectrometry,

d complexes with the substrate metal atoms. Peak-to-background ratios as high as 1000:1

uld be produced with total beam currents of 1 nA. Spectra were successfully obtained from

ese compounds dispersed onto single silver particles as small as 20 urn in diameter,

ese experiments suggest that, at least for some compounds, SIMS at intermediate current

nsities can be used to study organic layers on individual particles, as well as studying

eciation from spectra of inorganic compounds.

igure 4(a). Positive secondary ion mass spectrum of glycine applied to a nickel substrate.

147
Depth Profiling

One of the most powerful modes of operation in SIMS is that of depth profiling. Since

the sample is worn away in a controlled fashion and at any time the secondary ion signal is produced from a surface layer only 1 nm deep, it is possible to follow the distribution in depth of an elemental or simple compound species. For an optimum sample geometry, flat with

no appreciable surface topography, and with controlled sputtering rates, profiles with

a depth resolution of 5 nm are possible (11). The depth resolution is ultimately limited by

a number of physical phenomena, including knock-on of sample atoms by the bombarding ions,

ion channeling, and the development of topography due to sputtering. The maximum depth attainable is limited to about 5 pm due to time and stability considerations.

Depth profiling can be successfully applied to individual particles, although the depth resolution is degraded somewhat by the irregular topography of a particle. An example of a depth profile following several elements in a single urban airborne particulate 10 pm in diameter is shown in Figure 5. In order to minimize the effects of variations in the matrix

oxygen content upon the secondary ion yields, the signals were normalized with the signal for silicon, a major constituent. Of principal interest is the behavior of the barium and lead constituents, which appear to be concentrated by more than an order of magnitude at the surface of the sample. In addition, a discontinuity is observed, suggesting that the particle

is layered.

14C
149
In order to make maximum use of the depth profiling mode, it is useful to have a spec- trometer which can be rapidly switched from one peak of interest to another to achieve a near simultaneous data collection, or a multi-channel spectrum. Since a typical particle can easily have fifteen or more constituents of interest, the data handling problem can be quite

difficult. Since SIMS by necessity must destroy the sample as it is examined, it would be particularly interesting to have truly simultaneous data collection for several ion species,

so that the location of the constituents could be more precisely determined.

Ion Imaging

Ion images showing the spatial distribution of an elemental or molecular constituent

can be obtained in the ion microscope or the ion microprobe (12,13). In the ion microscope,

a true image is produced by a lens system coupled with a mass spectrometer. The limiting

lateral resolution is about 0.5 urn. In the ion microprobe, the image is constructed by scanning a finely focussed ion beam over a raster and intensity-modulating a cathode ray tube scanned in synchronism with a signal derived from a particular mass peak. In the ion microprobe, the limiting beam size is about 1 urn, although with a suitable primary ion condenser

lens system, a probe size of 0.1 um should be possible.

As an example, figure 6 shows an image with the 23 Na signal obtained from a contamination particle on a silicon wafer. An edge resolution of about 1 um is achieved. The scanning time and sputtering rate was such that an average of 2 nm of material was removed while

preparing the image. Besides elemental signals, molecular signals can also be used for the preparation of ion imaaes.

Figure 6. Secondary ion image of a sodium-rich particle on a silicon substrate,

(a) Optical image, (b) Scanning ion image. 150
Because of the strong variations in the secondary ion signals with different matrix

fects, the direct interpretation of image intensities in secondary ion images in terms of mcentration is difficult. It is necessary to record the data digitally, apply quantitative

irrections by the sensitivity factor or local thermal equilibrium methods, and then recon- duct a final compositional image (14). Summary

Secondary ion mass spectrometry offers a number of powerful capabilities for the

:udy of individual particles: (1) the detection of all elements and isotopes; (2) limits

r detection in the microbeam mode in the range of 1 ppm; (3) the possibility of detecting

^ganic and inorganic compounds; (4) the determination of the distribution in depth of a jnstituent, with a high depth resolution; (5) high lateral specificity; (6) the capability

r preparing ion images showing the lateral distribution of a constituent. Quantitative

lalysis with a relative accuracy of a factor of 2 is routinely available by the method of elative sensitivity factors or by a physical model for secondary ion emission. The

-eatest potential of SIMS will be obtained when it is used in conjunction with other

jrface analysis and microanalysis methods, such as Auger electron spectroscopy, scanning

iectron microscopy with x-ray microanalysis, and laser Raman microanalysis. References

I] Small, J. A. and Zoller, W. H. , "Single Particle Analysis of the Ash from the Dickerson

Coal-Fired Power Plant" in Methods and Standards for Environmental Measurement, ed. Kirchhoff, W. H. , National Bureau of Standards Special Publication 464 (Washington,

1977).

2] Secondary Ion Mass Spectrometry, eds. Heinrich, K. F. J. and Newbury, D. E. , National Bureau of Standards Special Publication 427 (Washington, 1975).

3] McHugh, J. A., "Secondary Ion Mass Spectrometry" in Methods of Surface Analysis, ed. Czanderna, A. W. (Elsevier, Amsterdam, 1975) 223-278.

4] Newbury, D. E. , "Secondary Ion Mass Spectrometry for Particulate Analysis" in Environmental Pollutants Detection and Measurement, eds. Toribara, T. Y. , Coleman, J. R. , Dahneke, B. E. , andFeldman, I. (Plenum, 1978) 317-348.

5] Czanderna, A. W. , Methods of Surface Analysis (Elsevier, Amsterdam, 1975).

6] Andersen, C. A. , "Analytic Methods and Applications of the IonMicroprobe Mass Analyzer"

in Microprobe Analysis , ed. Andersen, C. A. (Wiley, 1973) 531-553.

7] Newbury, D. E. , "Quantitative Analysis by Secondary Ion Mass Spectrometry" in Quantitative Surface Analysis of Materials, ed. Mclntyre, N. S. , ASTM STP 643 (ASTM, Phi 1 a- dephia, 1978) 127-149.

8] Andersen, C. A. and Hinthorne, J. R. , "Thermodynamic Approach to the Quantitative Inter- pretation of Sputtered Ion Mass Spectra", Analyt. Chem. , 45 (1973) 1422-1438.

*9] Benni nghoven , A., Jaspers, D. , and Sichtermann, W. , "Secondary Ion Emission of Amino

Acids" Appl. Phys. 11 (1976) 35-39.

10] Benninghoven, A., Surface Sci. 53 (1975) 596.

II] McHugh, J. A., "Factors that Influence an Elemental Depth Profile", in NBS SP 427, ibid, 179-189.

12] Morrison, G. H. and Slodzian, G. , "Ion Microscopy", Analyt. Chem. 47 (1975) 932A-943A.

13] Newbury, D. E. , "Ion Imaging in Secondary Ion Mass Spectrometry", in Multidiscipl inary Microscopy, Proc. Soc. Photo-Optical Instrumentation Engrs. , 104 (1977) 85-89.

14] Morrison, G. H. , "Digital Image Processing in Ion Microscopy," Proc. 2nd U. S. Japan

Seminar on Secondary Ion Mass Spectrometry", Osaka (Oct. 23-27, 1978).

151
[13] Newbury, D. E. , "Ion Imaging in Secondary Ion Mass Spectrometry", in Multidiscipl inary Microscopy, Proc. Soc. Photo-Optical Instrumentation Engrs. , J04 (1977) 85-89.

[14] Morrison, G. H. , "Digital Image Processing in Ion Microscopy," Proc. 2nd U. S. Japan

Seminar on Secondary Ion Mass Spectrometry", Osaka (Oct. 23-27, 1978).

152
National Bureau of Standards Special Publication 533. This Publication Originated from a Special Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

society, Ann Arbor, MI, June 22, 1978. (Issued April 1980) SCOPE AND LIMITATIONS OF SINGLE PARTICLE ANALYSIS BY RAMAN MICR0PR0BE SPECTROSCOPY

Edgar S. Etz and John J. Blaha Center for Analytical Chemistry

National Bureau of Standards Washington, D. C. 20234 Introduction

From the time of its discovery in 1928 until a few years ago, Raman scattering was used

is a tool for the study of bulk samples of macroscopic dimensions, furnishing information

about fundamental molecular properties as well as serving an important function in laboratory

;pectrochemical analysis [1-3] 1

. The advent of lasers as sources for excitation of Raman

spectra and the ongoing developments in instrumentation for optical spectroscopy have

increased the sensitivity of Raman scattering experiments to the point where vibrational

spectra can now routinely be obtained from discrete microsamples or sampling volumes of

nass approaching one picogram [4-7]. Raman measurements in the microscopic domain are

Deing conducted in a number of laboratories throughout the world and at present involve the

jse of two types of instruments. One is the Raman microprobe developed at NBS [6] specifically for the analysis of micrometer-size particles, and the other is the now commercially

available Raman microprobe/microscope MOLE [7]. The fundamentals of Raman microprobe spectroscopy and the microanalytical applications

^covering the literature through 1978) of these new instruments have recently been

"eviewed [8]. Detail on critical aspects of instrument design and performance and on measurement criteria important to optimized microanalysis has been reported elsewhere [9,10]. The emphasis of the work published to date has been to demonstrate the practical uses

jpf the technique in several major application areas, and a few of these investigations can

:e cited here as being illustrative of this research [7-18]. The problems which have been

examined fall into the broad areas of (i) materials analysis and characterization of microstructure [7,11,12], (ii) particulate contamination studies [7,11], (iii) environmental

oarticulate pollution analysis [13-15], (iv) micromineralogy and mineral "inclusion studies

[9,12,16], and (v) investigations of biological and pathological tissues [ ,17,18]. Much has been learned in the course of these studies concerning the principal advantages and inherent shortcomings of Raman microprobe analysis [8,10]. The recognition of these aspects permits projections to be made as to the further development nd future

potential of Raman scattering as a viable probe technique [19-23].

In this paper we will present our current views of the scope and limitations of Raman

nicroprobe spectroscopy. This perspective is largely based on our experiences resulting

'from the development at NBS of micro-Raman instrumentation and the application of the

technique to a diversity of microanalytical problems. We will briefly review the fundamentals of laser-Raman spectroscopy and show how, with present methodology, the principles

of normal (or spontaneous) Raman scattering have successfully been applied to chemical

microanalysis. This will include a description of the design and performance of the NBS developed microprobe and comments on the MOLE (Molecular Optical Laser Examiner) microprobe

simultaneously developed in France. The general analytical characteristics of these microorobes are demonstrated by measurement results obtained with the NBS instrument. These are addressed in terms of the basic parameters of interest, including spatial resolution,

sampling volume, limits of detection, and spectral specificity. Examples of application

''ill emphasize results from the analysis of single particles, supplemented by selected

illustrations of capability for the investigation of the other types of microsamples. The figures in brackets indicate the literature references at the end of this paper. 153
experimental limitations of the technique are discussed in relation to laser-induced sample heating and fluorescence, the chemical reactivity of microparticles, the intrinsic weakness

of the Raman effect, and the lack of an adequately developed theory for measurements to be placed on a quantitative basis. The results obtained in the areas identified above demonstrate the broad applicability of this new method of microanalysis and illustrate the unique information that can be obtained from micro-Raman scattering experiments. These results

also suggest numerous other opportunities for significant research in materials characterization and, we believe, are certain to contribute to the further development of the technique. Fundamentals of Raman Microprobe Spectroscopy

A. The Analytical Goal The most widely used techniques of instrumental microanalysis readily identify and determine the quantity of elemental constituents present but do not distinguish the chemical

forms of elements present as specific compounds in a microsample. The few physical methods

of microanalysis that permit obtaining information about the compounds present include techniques such as x-ray photoelectron spectroscopy (XPS or ESCA) , x-ray diffraction (XRD), infrared spectroscopy (IR), and thermoanalysi s. These provide possibilities for the quali- tative identification and, in some cases, even the quantitative determination of molecular

species - such as C, N, S compounds - and are coming into more widespread use for the

total characterization of environmental particulate matter [24]. None of these compoundspecific techniques, however, are truly microprobe methods in that the analytical signal is obtained from a single particle a few (<10 urn) micrometers in size or from a microscopic

sampling volume of equivalent dimensions. By these methods, the analytical information is generally obtained from a considerably larger sample mass (typically in the microgram to milligram range) which in the case of dust analysis requires a large number of particles. Micro-Raman spectroscopy now provides a powerful complement to these techniques by enabling routine, compound-specific microanalysis of discrete microscopic particles or probe regions approaching 1 picogram in sample mass [8]. Among the chief advantages of the method are that it is non-destructive of the sample, information on chemical species is obtained regardless of the physical state (usually solid or liquid) of the sample, and -

with respect to solids - the Raman spectra are analytically diagnostic for both crystalline

and amorphous phases. Raman spectroscopy, therefore, can be considered a highly specific

and sensitive technique of investigating molecular vibrational phenomena in all phases of matter. Applied to chemical microanalysis, it is an unequaled tool for the characterization

and identification of principal molecular constituents which are fingerprinted by their

vibrational spectra. In addition, as was inferred above, these spectra most often contain

information on the local molecular environment and the structural order of the solid phase (crystalline or glassy state) in which the species resides.

B. The Raman Scattering Process

The spectroscopic measurements performed with today's Raman microprobes are based upon

the excitation of the normal or spontaneous Raman effect. This effect provides the basis

for conventional Raman spectroscopy and has been extensively reviewed in the context of modern chemical analysis [1-3,25]. The measurement consists of the study of the spectral distribution of inelastical ly scattered light emitted by the sample irradiated with a monoenergetic, visible beam of laser light. The scattered radiation contains weak lines,

at frequencies both lower and higher than the exciting radiation. The frequency dif- ferences, called Raman shifts, are characteristic of molecular vibrations in the sample

and are independent of the exciting frequency. Thus, these spectra (distributions of scattered light intensity with frequency or wavelength) of the Raman scattered light identify the scattering molecules and - in the case of solids - contain information from which the nature and extent of crystal 1 i ni ty may be inferred. The spectra that are obtained in these instruments are the so-called Stokes-Raman spectra. They arise from molecules which scatter photons of lower frequency (Stokes lines) than that of the exciting

line. The corresponding higher frequency (anti-Stokes) lines are, under ordinary conditions,

of considerably lower intensity - thus more difficult to detect - and are generally recorded

154
ly when special information (e.g., temperature data from Stokes/anti-Stokes intensity

tios) on the sample is sought. Raman scattering is a secondary scattering phenomenon (Mie or elastic scattering is ders of magnitude more intense) and thus Raman line intensities are weak. This places

fficult requirements on the performance of a Raman spectrometer designed for microalytical applications. In a typical Raman experiment - for scattering by solids - only

e photon from the 10 6 -10 8 incident on the sample is scattered inelastically by molecular

brations. For this reason, intense excitation sources, perfect optics for collecting

e scattered radiation, and a highly efficient monochromator coupled to a low-background

otodetector are required to successfully detect a Raman line. The intensity of the Raman scattered light is proportional to the fourth power of the equency of the incident radiation. Band intensities are determined by the cross section

r Raman scattering and are directly proportional to the number density or concentration

scattering molecules in a specific energy state. Because of the indicated frequency

pendence of the Raman signal and the lack of highly effective detectors in the red and

ar infrared range, the frequency of the exciting radiation must be in the visible, or

tter, toward the ultraviolet range. In the case of excitation in the near ultraviolet,

serious difficulty may arise caused by the fluorescence of molecules in the Stokes range.

The Raman Information Content

Raman spectroscopy can be used for the analysis of polyatomic molecules or ions whose

larizability changes during vibration (the requirement for infrared activity is a change

the dipole moment). Most materials - sulfates, nitrates, carbonates, oxides, silicates,

imonium salts, and organic compounds - show characteristic Raman-active vibrations

nternal modes). Structural information is derived via the symmetry of molecules, the

'imber and strength of chemical bonds, and the atomic masses which determine the position

Raman bands. This allows distinguishing between compounds having the same elemental

imposition but different molecular coordination and structure.

A further degree of specificity of the Raman spectrum - in the case of solids - derives

•om motions of the crystal lattice as a whole that give rise to external or lattice vibraons. These modes are usually seen in the low-frequency region (below 400 cm

-1

, Raman

lift) and generally do not couple with the structure-specific internal modes. Important to microanalysis is the experimental observation that the Raman frequencies

f molecules present in microsampl es (e.g., microparticles) are no different from those

iserved in the spectra of macroscopic samples. Thus the selection rules for Raman

Mattering appear to be preserved. This correspondence among the spectra of particles and

leir bulk sample counterparts permits the use of Raman data reported in the literature as source of reference for the identification of chemical species in unknown particles.

One other point is noteworthy in the application of the technique to micro-analysis,

lis is the fact that even though the discriminating power of the Raman effect may not

ways remove spectral ambiguities due to interfering molecules, the microsample is less

=ikely to consist of a broad mixture of substances than the bulk of the material or larger

•amples from it. Consequently, the likelihood of several major, spectroscopical ly inter- ring components in the microsample is usually small. This can be expected to facilitate

he interpretation of micro-Raman spectra. Experimental Methods and Techniques

Requirements for Microsample Analysis

The various criteria important to Raman analysis of microsamples , and microparticles

i particular, have been described [5,6,9,10]. These center on a number of specific

istrument performance requirements which must be met by a practical Raman microprobe as

ill as on the judicious choice of several measurement parameters to ensure non-destructive

lalysis. In the former category is the requirement for detection of extremely low signal

jvels. This includes the need for full optimization of the signal from the sample

1 55
(frequently of mass ^10~12

g, as in the case of a single microparticle) and the effective

rejection of optical interferences. Among the various sources of optical interference are

the high light levels from the intense elastic scattering of the incident beam by the sample

and the supporting substrate (or the host) and the spectral interferences from the Raman scattering by the substrate (or the host) itself. Crucial also is the level of irradiance

(or power density, in watts per square centimeter) directed at the sample in a focused beam

a few micrometers in diameter (cross section). A third consideration, related to the first,

is the choice of substrate material used for supporting samples for measurement.

The irradiance levels typically required to permit the observation of the spectrum from

a small particle are apt to cause significant sample heating in cases where the particle

absorbs some or all of the energy at the exciting frequency. For this reason, any radiant energy absorbed by the particle and converted into heat must rapidly be dissipated. An important function of the substrate is therefore to provide an effective heat sink, thereby maintaining the temperature of the sample to values permitting non-destructive analysis. The selection of the irradiance level and substrate material is particularly pertinent in the analysis of environmental particles for which the optical absorption properties are

not known or easily determined.

In the following sections we describe the basic instrumentation required for microRaman scattering experiments, present a discussion of the important design/performance

features of the NBS microprobe and give an overview of the characteristics and measurement

capabilities of the MOLE Raman microprobe/microscope. This is followed by some experimental

detail on sample preparation and measurement procedures as applied to particles with a discussion of experimental limitations of the Raman microprobe measurement.

B. Instrumentation for Micro-Raman Spectroscopy

1. The Basic Raman Experiment

We will give a brief survey here of the basic instrumentation available for micro-Raman

scattering experiments. Only those components of the general instrument configuration are considered which - by design and performance - are important to microanalytical applications. In this context it is useful to discuss micro-Raman instrumentation under the headings of (i) excitation sources, (ii) monochromators and spectrographs, (iii) detectors

and recording systems, (iv) sampling arrangements, and (v) computer techniques. A thorough discussion of instrumentation for conventional, macro-Raman spectroscopy can be found in the literature [26]. The analytical applications of lasers in the field of atomic and molecular spectroscopy have recently been presented in a broad coverage of the topic [27].

(a) Excitation Sources . In microprobes now in use, gas lasers are used as excitation

sources. These lasers provide concentrated, polarized, coherent, and highly monochromatic

radiation. The intensity of the exciting line and the frequency of excitation may be varied. The laser lines most commonly used lie in the visible region of the spectrum, and good continuous power levels (output power of up to 200 mW in a given line is adequate for most micro-Raman work) are readily attainable from lasers that are commercially available.

The gas lasers in most common use are the argon ion (Ar+), krypton ion (Kr+), and mixed gas

(Ar +/Kr+) lasers which conveniently provide strong output lines from the blue to the red at principal wavelengths 488.0 nm (blue), 514.5 nm (green), 568.2 nm (yellow), and 647.1 nm (red). A helium-neon laser (He/Ne) may also be used. Its primary output wavelength is at 638. 2 nm. In addition to gas lasers, continuous wave (cw) dye lasers that can be tuned to any frequency from yellow to red with power outputs of several hundred milliwatts are increasingly being used in Raman spectroscopy. However, these have not been employed so far in micro-Raman investigations. They suffer from the problem that the dye laser emission

has a relatively high background.

The choice of the exciting line is dictated by the color of the sample. The requirement that the sample be transparent (ideally) to the incident radiation means that for spectral excitation a line should be chosen that most closely matches the color of the sample. For colorless (transparent) samples any exciting line in the visible region may be used.

156
(b) Monochromators and Spectrographs . The (scanning) monochromator of the Raman nstrument separates the very weak Raman signal from the considerably more intense Rayleigh

i.e., elastic component) scattered and reflected radiation. In addition to the desirable

haracteri sties of good resolution and low stray light levels, the monochromator should have

high light throughput (i.e., light gathering efficiency), since the limit of measurement

ensitivity is invariably governed by the intensity of the scattered light reaching the

etector. All of these considerations have been approached in different ways by various

iesigns. The most advanced spectrometer systems now in use employ double or triple monohromators fitted with new types of gratings. The recently developed holographic gratings

hich are now commonly employed, exhibit superb stray light capability. For example, the

oncave holographic grating double monochromators used in Raman microprobes have a stated

tray light rejection of 10 -12 at 20 cm

-1 (frequency shift from the exciting line). Other

ttributes of these gratings are high dispersion, good spectral resolution, and the spectra

re completely free from grating ghosts (i.e. , spurious lines). New types of spectrographs have been developed in recent years that take advantage of

he stray light rejection capabilities of holographic gratings. In micro-Raman instrumentaion, these spectrographs are employed with multichannel spectral analyzers using image- ntensified TV-type detectors (e.g., vidicon tubes) [7,22]. In these low light level

j pplications, the photosensitive surface of the detector is placed in the focal plane of the arge-aperture spectrograph. In this way, either a major segment or the entire spectrum is ocused on the detector active area from where it can be recorded onto a read-out device,

o mechanical scanning is necessary with this technique which permits the recording of

! pectra in fractions of a second (e.g., -^lO -3 sec, in principle), thus making the observa-

.ion of transient species possible (as in kinetic studies).

(c) Detectors and Recording Systems , (i) Photomul tip! iers . Despite recent advances

n spectroscopic detection systems, photomultipl iers (PMT) are still the detectors which

I 'rovide lowest noise for very low light level signals in the range from the ultraviolet to

ibout 850 nm. The primary advantage of photomultipl iers is their amplification, by factors m the order of 10 6

, with very low noise. The sensitivity (or spectral response) of these

i levices when used in the photon counting mode is determined by their quantum efficiencies,

ind these are a function of the wavelength region in which they are employed. Typical

luantum efficiencies for a tube with S-20 response photocathode are 25 percent at 400 nm,

! percent at 700 nm, and 0.3 percent at 800 nm. For this reason, excitation of the sample

/ith the blue or green line from an Ar+ laser is preferred to that with the red lines from a le/Ne or Kr+ laser, provided that sample fluorescence or sample heating (due to radiation

ibsorption) is not a limitation.

For the kinds of applications considered here the photomultipl ier tube is usually

:ooled down to -30 °C to reduce the dark count to values less than five counts per second.

".n many measurement situations where the background count is negligible, cooling therefore

)rovides an easy way to increase the signal-to-noise (S/N) ratio. Typical signal detection

^ates in Raman microprobe measurements of micrometer-sized particles may vary from a low

if 20-30 counts/sec to signal rates frequently exceeding 10 4 counts/sec.

(ii) Spectral Multichannel Detectors . A second category of spectroscopic detectors

is developing at an accelerated rate and these are the optical multichannel detectors.

These detection systems offer an important advantage over a conventional photomultipl ier Principally from the point of view of data handling capability. These detectors allow data

acquisition times to be significantly reduced - compared with conventional single channel

operation - in proportion to the number of wavelength resolved intervals that are simultaleously detected by the device. They consist of image- i ntensi fied , TV-type detectors (or

:ameras) composed of a combination of one or more optical image-intensifiers and a two- dimensional transducer such as a vidicon or diode array. This type of multichannel detector

:an be used to provide sufficient amplification for photon counting sensitivity over a twodimensional matrix. This combination is particularly useful for Raman microprobe measure- ments because it permits simultaneous spatial and spectral multiplexing. The principles

jnderlying these multichannel detectors (or image devices) and their uses in analytical

spectroscopy have recently been reviewed [28-30]. A number of these optical multichannel

devices are now available as complete detector systems and are commonly known as silicon

vidicon, silicon intensified target vidicon (SIT), intensified SIT, and intensified diode

array (IDA) detectors. The performance of these devices vs. photomul tipl ier detectors in optical spectroscopy has been described with particular emphasis on signal-to-noise

157
relationships [31]. The most recent versions of these systems are becoming available as cooled detectors and possess improved analytical potential with respect to photon counting

sensitivity, dynamic range, signal-to-noise ratio and data handling capability [20,32]. Research efforts are underway to fully explore the combined capabilities of advanced, novel-design holographic grating spectrometer/spectrographs and various forms of these

optical multichannel analyzer (OMA) systems to yield Raman microprobe instrumentation with sensitivities truly approaching those of photomultipl iers , but having the multiplex advantage with high resolution [22]. The presently available commercial versions of these OMAs

are computer-compatible and provide expanded capabilities for data presentation and manipulation. These systems will further facilitate Raman scattering studies from microsamples and should enhance the possibilities for non-destructive analysis, because measurement times

can be significantly reduced.

(iii) Recording Systems . Traditionally, the output of the photomultipl ier detector is recorded in one of two ways. The least expensive method, d.c. amplification, works well at both high and low light levels, and the analog signal is recorded on a strip chart recorder. Clearly, the method of choice in micro-Raman spectroscopy is signal detection by photon counting which offers greater versatility as the digital output is directly compatible with

other digital equipment such as signal averagers and computers.

(d) Sampl i ng Arrangements . The most important criterion in the sampling arrangement

of a Raman microprobe is the illumination/collection geometry utilized for the generation

and efficient gathering of the scattered radiation. The foremost aim is to provide efficient illumination and collection and to select a design that will minimize optical interferences.

The most common scattering geometries in Raman spectroscopy employ either 90° or 180° (angle of laser beam incident on sample, relative to direction of collection) illumination.

The two types of Raman microprobes now in use both employ a backscatteri ng geometry. The particular designs utilized in both instruments - and the advantages derived from them - have been described [6,7,23] and will only briefly be reviewed in subsequent discussions.

In choosing an appropriate scattering configuration to obtain spectra from microsamples,

factors to be considered include maximizing the collected Raman signal, minimizing the amount of elastically scattered light which enters the spectrometer, and minimizing any

spectral contributions from the supporting substrate. The backscattering geometry is an effective means for the collection of scattered light and minimizes scattering of stray

laser light into the spectrometer. It is also of particular advantage for the probing of strongly absorbing materials, as the focused laser penetrates only little (by perhaps only

a few tenths of a micrometer) into the sample surface making a backscattering configuration

necessary. Beyond the collection optics, a means must be provided for efficient optical coupling between the sample and the monochromator. This is achieved by appropriate collection lenses matched to the optical aperture of the spectrometer.

One other factor, mentioned earlier, is the presence of the supporting substrate (or the host) which may lead to spectral interferences in the Raman scattering from microsamples. In this regard the substrate material itself should be non-interfering, i.e., have little or no Raman scattering, absorption or fluorescence. In the case of a hetero- geneous sample presenting an arbitrary host (e.g., as in the analysis of microparticulate

inclusions in a mineral host or in a biological matrix) this requirement is usually not

met. In such cases the optical system needs to be optimized so that collection of the light scattered by the microscopic inclusion is maximized and collection of any radiation scattered by the host is minimized.

(e) Computer Techniques . The application of computers in Raman spectroscopy for experiment control, data acquisition, and reduction has led to improvements in data accuracy

and to conveniences in data handling. Digital methods and automation techniques for Raman experiments have been described [33-35]. Advances in hardware and software development for spectroscopic applications have made

Raman systems enormously powerful. Usually, the functions of controlling the experiment, acquisition and storage of the data, are performed under active computer control, i.e.

,

1 53
i-line, while the data evaluation or reduction step is performed off-line at a later time,

t is probably in the area of data evaluation and analysis that the computer has had the reatest impact on Raman spectroscopy, providing a powerful method for data manipulations

trich were impossible to perform without digital techniques. Fast data display, implementing

nstrumental corrections, obtaining difference spectra (addition or subtraction), smoothing

f spectra, curve resolution, and peak area determination for calculating the concentration

f species, are now commonly performed by computer techniques.

The micro-Raman systems presently in use and those under development are computerompatible and are readily interfaced to either dedicated or time-shared computers to ncrease their capabilities. In these systems, the computer controls the functions of the pectrometer (i.e., the scanning of the wavelength drive, slit settings, etc.), the move-

•ent of the sample stage, and the complete data acquisition process (e.g., digitized photon

ounting). Appropriate software designs allow for data refinement (e.g., spectrum

stripping", ratioing, etc.), graphic display, and development of a spectral library.

. The Raman Microprobe Developed at NBS

For a detailed description of the design and construction of the NBS Raman microprobe,

he reader is referred to accounts given in earlier published work [6,36]. The basic layout

if the instrument is shown in the schematic of figure 1 and is identical, in principle, to hat of a conventional, monochannel Raman spectrometer. It employs a mixed gas, Ar+/Kr~

aser for excitation, and any one of the several prominent emission lines are used. Beamlirecting, prefiltering and focusing optics are used to furnish a tightly-focused excitation

>eam (fore-optics). A separate optical system is utilized for the collection and transfer

)f the scattered radiation to a state-of-the-art double monochromator equipped with concave

®

®

I Bt AM EXPAND6P

! BEAM DIRECTOR

* rELLlN-SROCA PRISM

1 tors omcAt rail system

» entrance pinhole

s focusing. viewing. *

collection optics

7 exit pinhole

8 MONOCHROMATOH INPUT OPT

9 ENTRANCE StIT

10 DOUBLE MONOCHROMATOR

Figure 1. Configuration of the laser-Raman microprobe developed

at NBS. The excitation source is a continuous-wave

gas -laser.- The fore-optical system (cf. fig. 2) utilizes a backscatteri ng illumination/collection

geometry. Spectral analysis is by a scanning mono- chromator and photomultiplier detection. The instru- ment is set up on a vibration-isolated optical table (granite).
holographic gratings (Ramanor HG-2, Instruments SA, Inc., J-Y Optical Systems Division). 2 A PMT based photon counting electronic detection system and a minicomputer are employed for data acquisition and total system control (e.g., sample stage positioning, wavelength scan, slit settings, etc.). Commercially available optical and mechanical components have been incorporated in the design wherever feasible. Optimum performance is required from each subsystem of the entire spectrometer. High-precision adjustments are provided for each

optical and mechanical component. The components utilized to focus the radiation on the sample - most often a single microparticle - position the sample substrate, and collect the scattered radiation are mounted along the optic axis at the center of a four-rail support

system. These components are shown in a schematic view in figure 2. A lens (not shown) on the rail focuses the incident laser beam (entering from the left) through the entrance

pinhole along the optical axis of the fore-optical system. The entrance pinhole is situated

at the image point of a beam- focusing microscope objective. Either a reflecting objective

(as shown) or a refractive objective lens are used to provide beam spots that may be varied

Figure 2. Schematic of the fore-optical system of the NBS Raman microprobe, showing beam focusing, sample

viewing, and scattered light collection optics mounted on support rails.

from ~2-20 urn in diameter (lateral resolution). Either of these objectives (with long working distance) focuses the laser beam to a small spot on the sample through a circular

opening in the center of an ellipsoidal mirror collector of high numerical aperture (N.A. U 0.86), thereby providing efficient, large solid-angle collection of the scattered light. & The sample, i.e., the particle, held on the surface of a substrate (typically an optically 1 transparent disc of sapphire or lithium fluoride) is mounted perpendicular to the incident | beam on a sample stage that can be accurately and reproducibly positioned by remotely- controlled piezoelectric translators. The beam-focusing objective also serves to view the

2 Certain commercial equipment, instruments, or materials are identified in this paper in order to adequately describe the subject discussed. In no case does such identification

imply recommendation or endorsement by the National Bureau of Standards, nor does it imply

that the item identified is necessarily the best available for the purpose.

160
.ample, by means of a beam splitter and a viewing eyepiece. In this spectrometer microscope,

;he sample can be viewed in transmitted light - with a fiber-optic guide mounted behind the

substrate - at variable magnifications up to 400X to aid in the location and precise posi-

: ' ;ioning of particles of interest. The focal point of the laser beam is made to precisely

;oincide with the near focus of the ellipsoidal mirror. Exact positioning of the particle

at this point then results in the focusing of the collected, scattered light at the second

Dr far focal point of the ellipsoidal mirror which is made the position of an exit pinhole.

: This pinhole serves to define and limit the effective light collection volume. The collec-

:ion of radiation scattered by the particle is thereby optimized and (interfering) scattered radiation from the supporting substrate is minimized. The exit pinhole is imaged on

:: the entrance slit of the monochromator. The scattered light at the position of the exit

:: slit is detected by a (thermoelectrical ly) cooled photomultipl ier tube with measured dark

: count of under five counts per second. Conventional photon counting equipment is used for amplification and monitoring of the Raman signal.

D. The Raman Microprobe/Microscope (MOLE) Developed at C.N.R.S.

The Raman microprobe/microscope (MOLE) that is now commercially available (Instruments

SA, Inc. , J-Y Optical Systems Division) is based on instrumentation developed several years

ago at the Centre National de la Recherche Scientifique (C.N.R.S., Lille-France) to obtain

Raman spectra of microsamples and images of microscopic features using a characteristic

'Raman frequency [4,7]. Applications of the instrument to chemical/biological microanalysis

and to microstructural investigations of solid state materials have been described [11,12].

Since the MOLE is the microprobe now being adopted by several laboratories, and instruments

of its type are likely to find increasing use, we present here a description of the MOLE

that identifies its main features and outlines its analytical function.

1. Basic Configuration

The basic configuration of the MOLE results from the coupling of a conventional light microscope (with bright and dark field illumination) to a scanning spectrometer/spectrograph

equipped with concave holographic gratings, followed by a multichannel and/or monochannel

detection system. A laser (typically argon ion) is the monochromatic source of light used

for irradiating the sample. The light microscope provides the sample stage and forms part

of the imaging system. All modes of observation available in a standard optical microscope

are available in the instrument. Therefore, microsamples can be examined i_n si tu without

any more sample preparation than that required for incident light observation.

The double monochromator spectrometer has very low stray light level and permits the

spectral separation (at good resolution) of characteristic Raman lines as they appear in the vibrational spectrum. It is also capable of transmitting spectral line images over a wide spectral range. The associated detection system consists of two separate assemblies,

a conventional monochannel detector (e.g., photomultipl ier , PM) and a sensitive multichannel optical detection system (typically an intensified vidicon detector). The latter

system is linked to a visualization system that displays the micrographic images formed in

a spectral line on a CRT. A computer with disc or tape memory can be interfaced to the instrument for data processing and storage. A schematic diagram of the instrument layout

is given in figure 3. This configuration results in a versatile microprobe/microscope because it permits two fundamentally different and independent modes of operation. One function is that of a molecular microprobe, the other that of a molecular microscope. They can be described as follows (cf. fig. 3).

161
DOUBLE CONCAVE HOLOGRAPHIC GRATING FILTER

POINT GLOBAL MULTICHANNEL MONOCHANEL

^ILLUMINATION I LLUMINATION/ ,D ETECTOR DETECTOR ILLUMINATION DETECTION

Figure 3. Diagram of the Raman microprobe/microscope (MOLE) developed at C. N. R. S. (Lille-France), illustrating

schemes of sample illumination and signal detection. The double grating filter is both a scanning monochromator and a spectrograph allowing two modes

of instrument operation (see text).

2. Modes of Operation

(a) Point Illumination with Monochannel or Multichannel Detection (Spectral Mode) . By

use of the bright field illumination system of the microscope, the objective focuses the laser beam into a microscopic spot, and the sample or sample region of interest is moved by translation of the microscope stage into the focal volume of the beam. The light scattered

by the sample is collected in the backscatteri ng direction through the same focusing objec- tive and directed into the monochromator/spectrograph (double concave holographic filter).

To obtain the Raman spectrum, the optical filter can work as (i) a Raman spectrometer when

the detector is a photomultipl ier followed by an amplifier and a chart recorder, or (ii) a Raman spectrograph when the detector is an image intensifier tube coupled to a low light

level TV camera (SIT or SEC tube).

(b) Area Illumination and Raman Imaging System (Imaging Mode) . In this mode, a larger

area (typically a circular area, anywhere from 150-400 urn in diameter) of the sample is illuminated from above with defocused laser radiation. In this mode of area (or global) illumination, the laser beam is rotated to form an annular beam of light which is directed

to the sample by the condenser of a dark field illuminator. By selecting a frequency in the Raman spectrum characteristic of one specific component in the sample, a micrographic

image is produced which indicates the distribution of this component throughout the illumi- nated area. This Raman line imaging is achieved by transferring the optical image formed

in the microscope onto the gratings, and from there the Raman image is transferred to the photocathode of the intensifier tube/multichannel detector.

In the monochannel spectral mode, classical Raman spectra can be recorded of the entire microsample or a specific volume element thereof. This mode corresponds to the function of the NBS microprobe. In the multichannel spectral mode, the Raman spectra are observed in spectrographic form on an oscilloscope, in real time, where up to 100 cm

-1 segments of a spectrum can be displayed. This mode is potentially useful for monitoring time-dependent
langes in a sample (e.g., spectral changes due to heating, photo-degradation, etc.). The

naging mode allows the localization of individual components of a multicomponent heteroeneous sample (i.e., "mapping" of the distribution of a species) with a resolving power

imited, in principle, only by the wavelength of the detected scattered light. In practice,

ne spatial resolution of the Raman line images is about 1 urn.

. Samples and thei r Measurement

1. Sample Preparation

Full detail on sample preparation and measurement techniques in the Raman analysis of

ingle particles has been presented [36]. Various techniques have been applied in preparing

mounting) specimens for analysis and generally those procedures followed in electron- and on-probe analysis are utilized. Samples for micro-Raman analysis do not, however, require

oating by a conductive film (e.g., Al , C, Au) as is frequently required by the conventional

ethods of microanalysis to dissipate specimen charging. Thin film overcoats, in fact, can

le detrimental in the Raman microprobe measurement as these films (typically ^20-40 nm

hick) are sufficiently radiation-absorbing to induce sample heating, modification or even

estruction.

(a) Substrate Selection . The selection of suitable substrate materials has been mportant for reasons alluded to earlier. To this point, the best choices have been highurity sapphire (a-Al 2 03 ) and lithium fluoride (LiF) of single-crystal quality, commercially

.vailable in various forms (e.g., as optical windows) with a high-polish surface finish to

i>ermit locating microscopic particles by light microscopy. They are used in the NBS work

due to size constraints imposed by the collection system) in the shape of small rods (4 mm

liameter, 6 mm long) held in an open, non-obstructing support collar. Sapphire is a weak

laman scatterer and does not give rise to significant spectral interferences for particles

arger than about 2-3 urn. The material is well suited for the direct sampling (by impaction)

if reactive aerosols (e.g., stack particulates from power plant emissions) because of its iurability and chemical inertness. Moreover, sapphire has high thermal conductivity and

therefore helps to minimize potentially destructive heating by serving as a heat sink to the rradiated particle. Lithium fluoride is useful as a substrate material because it lacks

; irst-order Raman activity and is obtained in high enough purity to be free from fluorescence. In use, the surfaces of LiF substrates do, however, gradually deteriorate due to

:he attack by moisture in the ambient air, and the surfaces have been shown to react with

. lygroscopic particles, for example, causing chemical transformations to take place [10,15].

6 If' Various other types of materials have been examined with respect to their utility as

; nicro-Raman substrates. Polished, highly-reflective metals (e.g., invar, stainless steels)

• :an be used, although heating effects have been noted in some cases. Also, these are less

desirable as a sampling surface for reactive aerosols.

Of some interest has been the evaluation of non-reactive polymeric membranes as supporting films for particle collections. Several types of plastic films are commonly

jsed as filter media (e.g., Millipore, Nucleopore, Fluoropore, etc.) for the collection of ambient aerosol. These thin, microporous membrane filters (the nominal thickness of 0.8 urn pore size Nucleopore filter is ^10 urn) are not suitable as supporting films for particles

i to be analyzed in the Raman microprobe. For example, membrane filters of the polycarbonate

and Teflon variety exhibit fairly complex Raman spectra with intense bands over the entire

I spectral range of interest. These serious interferences preclude the use of these membranes

as substrates and require the removal of particle collections from such filters.

(b) Particle Mounti ng and Samp! j ng Techniques . A number of techniques have come into

use for the preparation of single particle mounts and the optimized sampling of suspended

particles. These procedures have been described with particular reference to the characterization of particulates collected from the ambient air [15,36] and from emissions by stationary sources [13]. Particle mounts on substrates are usually obtained from dispersions

of bulk samples (e.g., filter-collected samples of airborne dusts). This involves transfer

of a small, representative fraction of the bulk dust sample onto the substrate, with the aim

to achieve a low density particle deposit devoid of extensive particle agglomeration. In

163
some cases, individual particles of interest isolated from a bulk particulate sample are transferred to Raman substrates by the usual particle handling techniques used by particle

analysts [37].

In the study of airborne particles and power plant stack particulates, we have attempted

to optimize the collection of samples by J_n situ sampling of the particles suspended in the

gas phase directly on Raman substrates. This second method of sample preparation involves

the use of multi-stage cascade impactors [24,38]. For most size-classified samplings of aerosols we have used a five-stage impactor of the Battelle design modified to accept on each impaction stage the Raman substrate of standard design. By using this type of sampler

and appropriate sampling times (to control the number density of particles collected, thus

the mass loading) we have sought to achieve minimum quantity sampling in order to minimize

all opportunities for changes to be induced (by particle-particle interactions) in the physical and chemical properties of the collected particles [39].

(c) Other Types of Microsamples . Frequently the sample under study is something other

than a single microparticle or a collection of particles. Examples of the analysis of such specimens are drawn from NBS work in the investigation of fluid inclusions in minerals and

the study of biological and pathological tissue sections. Microscopic inclusions (solid, liquid, or gaseous phases) in geological samples can be examined in the microprobe in a straightforward way, although optimized sample preparation

takes on special significance. Measurement limitations arise from constraints placed by 1 the optical system on the location (in the mineral specimen prepared for analysis), geometry I and dimensions of the inclusion. The inclusion must be observable without serious obstruc- ; tion. A specimen prepared for normal microscopy (typically with a flat polished or natural face) is suitable for the microprobe measurement. Also, the host mineral should be reason

ably transparent in the visible part of the spectrum (450 to 650 nm), and the contents of I the inclusion cannot be highly absorbing at the exciting laser wavelength. There are other

j intrinsic limitations (e.g., spectral) which will be indicated in the discussion of a specific example. The examination of biological samples in the Raman microprobe presents another set of requirements on sample preparation. In the preparation of biological tissues for micro- analysis, a major objective is that the j_n vivo distribution and concentration of elements

and compounds in the different cellular and extracellular compartments is not changed. Important also is the correlation of composition with tissue morphology. Various techniques"

have come into routine use for the preparation of tissue sections (typically of thickness

j

2-10 urn) suitable for elemental microanalysis by the conventional scanning electron microscope (SEM)/energy dispersive x-ray analysis (EDXA) approach. These methods - for soft

1 tissue - usually consist of suitable procedures for the fixation, dehydration, embedding

and sectioning of the tissue, and have been extensively described [40,41]. A number of the standard methods for the preparation of biological/pathological sections are fully compatible

j with the sample requirements for Raman microanalysis. Tissue sections prepared by cryosec- tioning techniques followed by air-drying, and standard sections embedded in paraffin have

j been satisfactory and have allowed non-destructive, in situ characterization of major molecj ular constituents. Measurement difficulties have been encountered in the investigation of 1 , tissue sections prepared by techniques involving exposure to some of the common fixatives,

j buffering agents and histological stains, as well as resulting from several of the common;

plastic embedding media. In general these tissue fixation and processing materials compli-'

cate the analysis either by causing absorption heating or by presenting serious spectral interferences (e.g., fluorescence).

2. Measurement Procedures

In the typical scheme of Raman microprobe analysis, the particle sample is first examined by light microscopy to single out and locate (with the aid of a thin aluminum film particle finder grid deposited on the substrate surface) individual particles of interest. The parameters observed include particle shape, size, color, transparency, surface roughness,

and frequently also birefringence and extinction. Recognition of these properties can be of value in the subsequent Raman investigation.

164
If a particle is colored, this may determine the choice of excitation frequency and

;;e level of laser irradiance used. Examination in the optical microscope - supplemented

optical micrographs taken before and after Raman analysis, to check on possible laser

mage - is then followed by the microprobe measurement. The spectra presented in this

::.per have been recorded by scanning the monochromator and plotting, on a strip chart reorder, the analog signal proportional to the number of photon counts observed in a lected measurement time (i.e., the time constant). Typically, these spectra are obtained

." using irradiance levels ranging from several megawatts/cm2 to values of a few kilowatts/

2

. (As a point of reference, the sun's irradiance - over the visible spectrum - amounts

: 135 milliwatt/cm2

). The lowest practical power densities are often required for the

is obing of unknown, environmental particles or radiation-sensitive biological samples, for

:?;ample. Measurements generally require signal integration times from 1-4 seconds at scan

eftes of 50 cm

-1 /min to 10 cm

_1 /min, respectively. A scan (with typical 3 cm

-1 spectral

solution) which covers the Raman spectral range from 0 to 3600 cm

-1 (frequency shift, Ai>) y therefore require from 1-6 hours of measurement time. The spectra of essentially

: lorless particles can be obtained at moderate to high power densities without deleterious

:• fects on the sample. Such scans are recorded with integration times from 0.2 to 0.5

ulieonds at scan rates of 200 to 100 cm

_1 /min, respectively. Optimized instrument perfornce (achieved by careful optical alignment) furnishes spectra of high signal-to-noise

tio with insignificant spectral interferences from either substrate (e.g., sapphire) missions or the elastic scattering component,

on i] In many of our studies we find it useful to apply electron- and ion-probe analysis to termine elemental compositions as an aid to the interpretation of the Raman spectra.

: ray area scans which indicate the micrometer and submicrometer inhomogeneity of a particle

; ve been found to corroborate the results of micro-Raman measurements. Because of the

• gher elemental sensitivity (and other factors related to the fragmentation of compounds

; der ion beam bombardment) the interpretation of ion probe mass spectra and their correla-

• ' on with the Raman data is more complicated. The full integration of the micro-Raman

i chnique with the elemental microanalysis methods is actively pursued. Limitations of Raman Microprobe Analysis

We will focus here on several aspects of the Raman microprobe measurement important to

: croanalysis. We will restrict this discussion to comments on (i) effective sampling

,\ ilume and spatial resolution, (ii) laser-induced sample heating, (iii) sample fluorescence

>s|l(l (iv) quantitation. With these comments we do not intend to convey a complete understandr jig of all the factors involved, but rather wish to identify those critical areas requiring

•-. :irther elucidation if the prospects for effective analytical implementation of micro-Raman

iectroscopy are to be enhanced. Effective Sampling Volume and Spatial Resolution

An important experimental goal in microprobe analysis is to obtain measurements with as recise and well known a spatial resolution as is possible. In Raman microprobe work,

tatial resolution may be defined by the intersection of the incident focused laser beam

Sue. , the laser spot) and the field of view or the sampling volume of the collection

: )tics. In the NBS microprobe, spatial resolution is determined by the particular configuraiOn of the focusing/light collection optics utilized in the fore-optical system (cf.

igure 2). The optical and geometrical factors that determine the effective sampling volume and

ince the effective spatial (lateral and depth) resolution have been discussed for the case

single microparticles supported by a substrate and for microscopic regions localized in

" below the surface of a heterogeneous bulk specimen [9,23]. Calculations show that for

iscrete microscopic samples the diameter of the exit spatial filter closely determines the

intensions of the collection volume. With a 140 urn diameter exit spatial filter (i.e., size

: c exit pinhole used for most measurements), the collection volume is ideally an ellipsoid

ith axial dimensions of 8 urn and 9 urn. Due to spherical aberrations and coma, the true

jpth (along the optic axis) of the collection volume is more like 12 urn (in air). Thus,

ie Raman signal originates from both the surface and some portion of the interior, or bulk,

f the sample. For p.jbe volumes embedded in a host (e.g., the case of a microscopic fluid

165
inclusion), the effective spatial resolution is less well defined owing to several optical effects and aberrations (distortions) of the sampling volume. The degree of spatial filtering, determining the rejection of interfering scattering by I the substrate, can be illustrated by the spectra shown in figure 4. Two measurements were!

performed on a thorium oxide particle (a microsphere) of submicrometer size (diam. 0.8 um),| utilizing identical irradiance conditions (approx. 1 MW/cm2

) but obtaining the signal with-I

out the exit pinhole in the second scan. The oxide displays a simple Raman spectrum [42]

consisting of a single line (marked P) with shift 467 cm

-1

. The Raman bands characteristic!

of sapphire [43] are labeled S. The effect of limiting the collection volume of the ellips-j

oid by the size of the exit spatial filter is seen by comparing the signal-to-backgroundl

ratios of the two spectra.

Figure 4. Raman spectra of a submicron thorium oxide particle showing the effect of spatial filtering on the spectral interference b^ the sapphire substrate. Bands marked Fjj and S derive from the particle and sub- strate, respectively. Upper spectrun obtained using 85 urn diameter exit spatial filter, lower spectrum without the exit pinhole.

B. Laser-Induced Sample Heating

Strong absorption of the focused laser radiation by colored samples gives rise to samplf

heating and may lead to their thermal decomposition. Measurements must therefore be madsiiS under irradiance conditions commensurate with preserving the integrity of the sample. Th( 1

microprobe systems in use have been designed so that the signal-to-background ratio i essentially independent of irradiance level. This means that the power density on the sample can be reduced, but this requires that measurement times are increased. The case of sample heating for radiation absorbing spherical microparticles has beet„ considered [9,23,44]. From model calculations, estimates have been derived for the transient

and steady state temperature reached by optically absorbing spherical particles immersed ir a host (e.g., air or A1 2 0 3 ). Results show that heating effects become less severe as th< particle size decreases (which is also born out by experiment) and that a sapphire host, fot 166
ample, is three orders of magnitude more efficient as a heat sink than air. The calculaons indicate also that destructive heating of microparticles can be attributed to highly

calized absorption and large temperature gradients in the particle. These effects can be ought on by light-absorbing surface layers or microscopic inclusions. In these cases, e heat-sinking properties of the substrate material are likely to be ineffective. Laser-induced sample heating usually leads to noticeable spectral changes. Bands tend

' shift to lower wavenumbers and broaden and sample changes, such as phase transitions or mpositional modifications, can occur. Not much is known about real energy density threshds for significant absorption-induced perturbations of microsamples. Complete sample

eakdown (e.g., melting, vaporization) by simple absorption heating sets an upper limit on

e allowable intensity of the focused beam. The spectra of figure 5 were obtained in two successive measurements under conditions

low and high irradiance, employing 514.5 nm excitation. The sample is a ~3 urn particle

olated from a bulk sample of airborne dust. The unknown particle is identified as sodium

trate (NaN0 3 ) with reference to published Raman data for this salt [45]. The upper

ectrum was obtained first at an irradiance of 5.7 kW/cm2

; the lower spectrum was then

tained at 0.32 MW/cm2

. The most pronounced difference in the two spectra consists of the

o broad bands in the 1200-1700 cm

-1 region and the appearance of a much higher luminescence

vel in the high irradiance spectrum. Other differences are noted in both the intensity

d in the spectral definition of the bands, with frequency shifts 98, 185, 724, 1068, and

85 cm

-1

, attributed to sodium nitrate. The two prominent, broad bands in the lower

ectrum, centered at 1350 and 1600 cm

-1

, are associated with the presence of a form of lymeric (also called graphitic or elemental) carbon not detected in the low irradiance

ectrum. A repeat scan (not shown) of the particle under the same low irradiance condions showed the same spectral features as the high irradiance scan. In these spectra we

le the result of the absorption-induced conversion of an environmental carbonaceous material

r minor constituent of the particle, likely surface-adsorbed) to a form of polymeric carbon

th graphitic structure [14,46].

:

Figure 5. Effect of laser irradiance (watts/cm2

) on the spectrum of a microparticle of sodium

nitrate (NaN0 3 ) in urban air particulate

dust. Power density at sample: top, 5.7 kW/cm2

; bottom, 0.32 MW/cm2

. Shown also

is the (interfering) spectrum of the sap- phire substrate.

IOOO cm O

167
The carbon bands, so frequently detected in the spectra of pollution particles, have

been of special interest to us from two points of view. First, there is the question of the source and nature of this carbon material in the environment and, second, the possi- bility of the conversion of any associated organic (i.e. , hydrocarbon) material to a form of polycrystalline graphite as a result of the high-i rradiance microprobe measurement. These

questions were examined following numerous experimental observations of the appearance of these bands in the spectra, their sensitivity to laser irradiation, as evidenced by readily perceptible changes in the shape and the relative intensities of the two bands.

In a series of modeling experiments described elsewhere [14], laboratory-prepared

particle samples of soluble anhydrite (CaS04 , known to undergo a phase transition at ^300

°C, converting to the insoluble anhydrite form) were coated with thin layers of various

forms of carbon (e.g., vapor-deposited vitreous carbon) or carbonaceous organic material

(e.g., petroleum hydrocarbons) to relate the spectral profile of the carbon bands to both

the nature of the surface film and the irradiance conditions of the measurement. Figure 6 shows spectra of CaS0 4 microparticles coated, in one case (spectrum B) with a (liquid) film

of n-hexadecane. The two spectra were obtained under identical irradiance conditions. The spectrum of the particle coated with the hydrocarbon liquid exhibits the familiar spectral features assigned to polymeric elemental carbon and indicates that in this measurement the organic film has been converted to a form of graphitic carbon. In other Raman work on carbonaceous particles sampled from polluted air, this form of carbon has been identified

with soot [47]. Thus, the two distinct bands have developed as a consequence of the decomposition of the hydrocarbon with the formation of a carbon residue of microcrystall ine structure [46]. Continued exposure of this sample to laser irradiation brought on a partial transformation from the soluble to the insoluble form of anhydrite. This conversion is thought to have occurred by the heating of the particle due to the optically absorbing

carbon film that had formed.

Figure 6. Raman microprobe spectra of particles of soluble anhydrite (CaS0 4 ) with and without

a coating of n-hexadecane. A. Non-coated < particle. Measurement parameters: par

tide size, 6x16 urn; substrate, a-Al 2 0 3 ; laser, \0 = 514.5 nm; power, 90 mW (atH

sample); beam spot, ^6 urn diameter; spec- ; tral slit width, 3 cm

-1

; time constant,

0.5 sec; scan rate, 100 cnrVmin; inten-jl

sity, 1000 counts full scale. B. Particle : coated with hydrocarbon liquid; size, 8x12 urn. Measurement conditions as for A,

1 except: time constant, 1.0 sec; scan

' rate, 50 cm

_1 /min.

.J
Sample Fluorescence

Fluorescence assumes major importance in the selection of excitation wavelength,

occurs when one or more constituents of the observed system (e.g., a single particle or

/biological tissue section) absorb part of the incident light and then emit some of this sorbed energy. The fluorescence emission can be many orders of magnitude stronger than

man scattering from the sample. Thus, fluorescence from sample impurities or contaminants

n provide severe background interference to microprobe measurements. In the analysis of vironmental particulates, fluorescence can be attributed to absorption by organic combus-

;on residues (present as contaminating films) or other types of adsorbed materials. In ganic and biological samples, this fluorescence can be very strong. The fluorescence in these measurements manifests itself as a broad continuum in the

}man spectrum of many samples. With microsamples , there is not much that one can do to

'duce the fluorescence background to manageable levels, such as by sample "clean-up" as in 'cro-Raman work. Sometimes, however, the fluorescence background decays with time to the

;int at which a suitable signal-to-noise level is reached. In rare cases can one subtract

e fluorescence background to yield a reliable Raman spectrum.

In recent work we have more systematically examined the problem of sample fluores- ce. As part of a broader study, the spectra of microsamples of a series of polynuclear

: omatic hydrocarbons (PAHs) were obtained. The object was to evaluate the analytical

;tential of micro-Raman spectroscopy in the trace characterization of solid organic

;llutants [48]. The PAHs were measured as single microparticles , generally of size 2-10

: , and include representative members of the 3-ring (e.g., phenanthrene) and 4-ring (e.g.,

: rysene, pyrene, f 1 uoranthene) systems. The fluorescence levels were examined in the ectra excited at three laser wavelengths - 514.5 nm (green), 568.2 nm (yellow), and

7.1 nm (red). In general, excitation with 514.5 nm radiation under the lowest practical

radiance conditions (typically 2 mW at sample in a 20 urn beam spot) furnishes spectra

aracterized by high, broad-band fluorescence levels. In these situations, a useful ectrum cannot be obtained. Excitation at 568.2 nm results in spectra that have apprecily lower background levels, indicating much diminished fluorescence emission at this

velength. With 647.1 nm excitation, fluorescence from these compounds is virtually

n-exi stent.

A result from these investigations is the spectrum shown in figure 7 for a subnanogram

crocrystal of fluoranthene excited with the yellow laser line. The spectrum has excellent

gnal-to-background due to the absence of fluorescence. This inconsequential background is en further diminished in the red. With green line excitation, overwhelming fluorescence

n'ssion was encountered from these particles upon which the strongest bands in the spectrum

fjiuld barely be detected. The sharp doublet at the high frequency end (i.e., at higher

"ivenumber shifts) is not attributed to the spectrum of fluoranthene but arises from the ruby

_:r2 0 3 , present as a trace impurity) fluorescence in sapphire. This fluorescence doublet

'! lines of ruby) appears at wavenumber shifts 3167 cm

-1 (R2 line, 692.9 nm) and 3196 cm

-1 11 line, 694.3 nm) with 568.2 nm spectral excitation. The ruby doublet from sapphire

ibstrates represents a more serious interference in spectra excited with the red line, for

'ien the two intense bands appear in a highly diagnostic region (e.g., for sulfates, carbon-

'.es) of the spectrum, at Raman shifts 1021 cm

-1 and 1050 cm

-1

. This makes necessary the

;e of lithium fluoride substrates for which this spectral interference does not arise.

169
Figure 7. The spectra of fluorescence sensitized polynuclear aromatic hydrocarbons (PAHs). Microprobe spectrum of fluoranthene (C 16 H 10 ). Measurement parameters: particle

size, 7x9 urn; substrate, a-Al 2 0 3 ; laser, A0 = 568.2 nm; power, 5 mW (at sample); beam spot, M8 urn diameter; spectral slit width, 3 cm" 1

; time constant, 0.2 sec; scan rate, 200 cm~1 /min; intensity, 1000 counts full scale. Bands marked S arise

from the fluorescence of the substrate.

The spectra of these structurally closely related PAHs (e.g., the compounds in the 4-ring system) are sufficiently different to allow unequivocal identification of these molecular solids. Other studies on selected isomeric compounds of the 5-ring system (e.g., benzo[a]pyrene , perylene) indicate a similarly high specificity of the Raman spectrum. A detection limit (with the Raman microprobe in its present state of development) of 10-100 pg

is indicated for many of these environmentally significant hydrocarbons.

D. Quantitation

The relationships for quantitative analysis in conventional macro-Raman spectroscopy*

are based on the observation that the Raman scattering intensity is proportional to the concentration of the species which generates the line in the spectrum. The band intensities,* which are meaningful for quantitation of Raman data are the relative integrated intensities.^

Raman signal intensities from different solid samples cannot ordinarly be directly compared, I because the scattering phenomena are complicated and instrumental factors play a decisive I

role. Despite these complications, in much of contemporary Raman work (e.g., solution- and gas-phase analysis), reliable quantitative results can be obtained by reference to internal)!

or external calibration standards [3]. This approach compensates for differences in matrix!.! effects (e.g., bulk optical properties), sample geometry (relative to excitation/col lection I configuration) and instrumental factors. When the conventional considerations basic to quantitation in macro-Raman spectroscopy

are extended to the Raman scattering of light by microscopic samples, formidable complica- ; tions arise. The fundamental difficulties result from the lack of an adequately developec theory of inelastic (Raman and fluorescence) scattering from microparticles [19]. The I detailed effects that need to be considered in any model for inelastic scattering are ! complicated, and their elucidation is the subject of ongoing work by several investigators! I [19,49-52]. Any approach to the quantitative estimation of species concentrations in micro-' i particles must take these detailed effects into account.

The theoretical foundations for inelastic scattering by microscopic particles will notjji be reviewed here. However, some comments on this topic are appropriate in outlining the;

j relationship to quantitation in Raman microprobe analysis. The theories show that the' morphological (e.g., size and shape) and optical properties (e.g., refractive index) of the particle profoundly influence the Raman scattering. Adding further to these effects on the signal are factors related to the distribution of active molecules within the particle. These properties strongly influence the local electric field which excites molecular

170
"ansitions and the angular distribution, polarization, and intensity of the emitted

idiation. From an experimental point of view, particle orientation effects, angle of oservation and polarization phenomena must be considered in conjunction with the optical

jsign of the instrument and the instrument function itself. Thus, one can anticipate a implicated relation between Raman intensity and component concentration. In the attempts

ade to quantify several of these effects from exact Mie (elastic) and Raman (inelastic)

rattering theory, they have been considered to arise from the influence of the particle

Dundary both upon the internal or local electric field at the incident frequency and upon

ie emissions at the shifted frequency rather than from any alterations of the molecular

^ansitions [50]. The theoretical treatments which have been advanced all consider the interaction of the

icident radiation (or electric) field with spherical particles [49-52]. This has led to alculations for Raman scattering by molecules embedded in isotropic, dielectric spheres and

icludes the case of light scattering by structured (layered) spheres. These theories

ttempt to estimate the properties of the electric fields within the particle (i.e., the

ielectric response of the material) and their effects on the properties of the i nel astical ly :attered field. It has been proposed that the electric fields within the particle are

|

. I'ghly structured and vary in polarization and strength with particle size, shape, and

-j:3fractive index. The treatments have further recognized that, since inelastic scattering

illy molecules embedded in microparticles is stimulated by the local internal field and since

c[ne local dissipation of heat for particles also arises from interaction with this field,

:Jne two processes of optical absorption and scattering are related [50-52]. Thus, the pattering dependence upon particle properties is qualitatively similar to the dependence

f the absorption upon these properties.

In calculations of the efficiency for optical absorption by microscopic particles, the

-sneoretical prediction of resonances in the efficiency factors for absorption has led to

;. he formulation of a corresponding fine structure in the Raman scattering from microarticles, described in terms of internal field resonance effects that parallel those known

pu

l!rom elastic light scattering (or Debye-Mie scattering) theory [51-53]. Since these

esonances in the internal fields depend on the frequency of the exciting radiation, diferent regions of the inelastic scattering spectrum can have quite different intensities,

lurthermore, the calculations predict that these peaks in both the elastic and inelastic

cattering are a sensitivite function of the optical absorption and the exact size of the

j article. An accurate prediction of these resonance effects on the Raman spectrum of ijicroparticles that do not fit the model of a perfect sphere is exceedingly difficult, and

- ias not been made.

4i A preliminary experimental investigation (514.5 nm excitation) of the intensity of the

i llastic and inelastic (467 cm

-1 band, cf. fig. 4) scattering from microspheres of thorium

-<

! xide, ranging in size (diameter) from 1 to 10 urn, has been performed with the Raman microivK-robe [9]. Results of these measurements are shown in figure 8. Plotted are scattered

\ intensity (Mie and Raman) versus particle diameter. The theoretical curve predicted from

xact Mie scattering theory (with intensities integrated over a scattering angle from

; :64-120°) is shown in the upper graph with the experimental points from a large number of bservations closely falling about this solid curve. The experimental points are in quite

j ood agreement with the prediction of the Mie theory, showing a r

2 dependence (where r is Jrhe particle radius) of the scattered intensity on particle size. The fine structure Associated with the Mie scattering curve results from the resonances. With respect to the

eijaman data, in a first approximation one would expect the inelastic scattering intensities

o be proportional to the number of scattering molecules contained in the particle, or

imply proportional to the volume of the particle. This expected behaviour is indicated

• y the solid line, drawn to show this r

3 dependence. The experimental Raman intensities

I verall show this trend with particle volume. However, there are deviations from this

imple relationship which are suggestive of the resonance structure predicted by current

heory, and similar to that noted for the Mie intensity curve [49-53]. Experimental work

•

;

: s continuing in this area to firmly establish the existence of these resonances in the

•vraman scattering intensity both for narrow intervals of the size parameter, or for a fixed

•^ article size, over a narrow excitation wavelength interval.

171
Figure 8. Mie (elastic) and Raman (inelastic) scat- tered intensities as a function of par- ticle size for thorium oxide (Th0 2 ) microspheres. Raman intensities measured for

the band with shift 467 cm" 1 (cf. fig.

4). Solid curves calculated from first principles; points are experimental.

0 5 10 DIAMETER (|jm)

Applications of Raman Microprobe Spectroscopy

A. Areas of Investigation

We will present here selected examples of investigations conducted with the NBS microprobe in several areas of microanalysis. Research along similar lines has been performed

with the MOLE and literature citations to this work have been given [7,11,12]. Earlier in the discussion of this paper, reference was made to the general problem areas that have been investigated by micro-Raman techniques.

The NBS micro-Raman work has focused on a diversity of problems related to environmental particulate pollution, with emphasis on the spectroscopic characterization of airborne

particles and atmospheric aerosols [13-15,36]. Interest has centered on the identification

of the principal sulfur- and nitrogen-bearing species, such as sulfate (S0 4

2 ~), nitrate

(N0 3 ") and ammonium (NH 4

+

) in the coarse (>2 \jm) size fraction of the particle collections.

Samples (of mass in the subnanogram range) composed of submicrometer-size aerosol collected

from the South Pole atmosphere have been analyzed to correlate results with elemental data obtained by x-ray microanalysis [15]. Microparticulate emissions from power plants, i.e., fly ash and stack aerosol, have been studied to discern the molecular identities of those

species whose major elements were determined by x-ray microanalysis [13,54]. Carbonaceous

matter was found to be associated with many of the environmental particles analyzed, and a major fraction of this material could be attributed to a form of elemental carbon with

structures similar to polycrystal 1 i ne graphite. These studies of environmental particles

have furnished new insights on particle transformations, sampling effects on the chemistry

of inicroparticles, and a better assessment of the effects of the microprobe measurement on the sample and the spectroscopic information that can be obtained. In the area of micro- mineralogy, non-destructive i_n situ analysis of individual phases in fluid inclusions in geological samples have furnished new results of interest [9,55]. Individual microscopic

172
rystals and fibers of several of the common asbestos minerals (i.e., sheet and chain

ilicates) have been characterized by microprobe measurements [16,54]. The aim was to elucidate any spectral differences that might be ascribed to the distinct fibrous and non-

''ibrous morphologies of these minerals. In feasibility studies, micro-Raman spectroscopy

ias been evaluated as a sensitive and specific detection method for organic fractions

eparated by liquid chromatography .[48]. In this area of trace organic analysis, the dentif ication of structurally similar polynuclear aromatic hydrocarbons (PAHs), many of

Vhich are potent carcinogens, is of importance to pollution studies. The possibilities for

•ibrational analysis at the microscopic level in biology and medicine are very exciting,

'reliminary investigations in this area have resulted in demonstrating nondestructive

*nalysis of thin sections of soft and hard biological tissues [17,18]. Here we will briefly

nention the unique information obtained in the study of bone and tooth mineralization

17]. A second example is provided by microprobe measurements on standard sections of ntact pathological tissue leading to the identification of organic, microparticulate

? oreign-body inclusions [18]. The examples we have chosen to discuss from the above areas of application are intended

;o provide a perspective of the practical utility of the technique and the prospects for

7 urther analytical implementation in the future.

5. Study of Airborne Particles

The analysis of airborne particles is important in many fields of human endeavor,

including concerns related to pollution monitoring, global climate modification, health

Hazard evaluation, and contamination control. In our studies on particles collected from

;he ambient air, we demonstrated detection and identification of a broad range of substances

oresent in the atmospheric environment. The principal inorganic species for which spectroscopic characterization in microparticles is sought include the common minerals (e.g., silicates), oxides, carbonates, sulfates, sulfites, nitrates, phosphates, and ammonium

salts. Since a number of these species also exist as water-soluble compounds (e.g.,

vNH 4 ) 2 S0 4 , Pb(N0 3 ) 2 ) they may also occur in the dissolved state of liquid microparticles,

and, in fact, are commonly encountered either in solution or extensively hydrated, particularly when such hygroscopic species are associated with the fine (<2 um) size fraction of atmospheric aerosol (e.g., acid aerosol). In the analysis of liquid microparticles, the nicroprobe spectra can furnish unique information (not obtained by conventional microprobes

which require the sample to be placed in a vacuum) on the specific chemical states of dissolved species, their extent of dissociation, and in addition can provide some measure of relative concentrations. In measurements on microdroplets of laboratory-generated sulfuric

acid aerosol, we have shown capability for the detection of dissolved molecular ions [36]

and can illustrate these results with the spectra shown in figure 9. In these experiments

we have examined the transformation of individual (liquid) H 2 S04 microparticles to solid, m'crocrystal 1 ine (NH4 ) 2 S0 4 by reaction with ammonia vapor. This conversion is one of considerable interest to the study (e.g., mechanisms, kinetics) of atmospheric reactions

involving the neutralization of ambient acid aerosol.

173
|(NH4 ljS04|

/ I II I

1

1 1 1

Figure 9. Raman microprobe spectra of sulfate spe- cies in liquid and solid microparticles.

(i) Spectrum of a microdroplet (^30 urn diameter) of sulfuric acid. Indicated are

the characteristic Raman shifts (cm -1

) of HSO4" and S0 4 2- ions in the aqueous solu- tion phase. (ii) Spectrum of a ^8 pm particle of crystalline ammonium sulfate,

(iii) Spectrum of a ^5 pm particle of anhydrite. The v designations indicate

the frequencies of the fundamental internal vibrational modes of the sulfate ion

in CaS0 4.

The upper spectrum of figure 9 demonstrates the detection and characterization in the liquid phase of the various sulfate species in a single microdroplet (size, ^-30 pm diameter)

of sulfuric acid. In concentrated H 2 S0 4 , all three species - undi ssoci ated H 2 S0 4 , HS0 4~

,

and S04

2 ~ - are detectable. The Raman shifts characteristic of the HS0 4- and S042 ~ ion in solution are indicated. The weak band at 903 cm

-1 is assigned to the undissociated H 2 S04 molecule [56]. The middle spectrum was obtained from a microcrystal (^8 pm in size) of ammonium sulfate, formed by "gas phase titration" whereby a microdroplet of H 2 S0 4 was exposed to trace concentrations (^50 ppm) of ammonia (NH 3 ) [36]. All of the predicted Raman modes are present [57]. The predominant band is due to the symmetric sulfate stretch with characteristic Raman shift 976 cm

-1

. The other bands appear at the expected frequencies

(cf. Table 1). The lower spectrum was obtained in other studies; it is a reference spectrum

of the mineral anhydrite obtained from a 5 pm particle. For this sulfate, the symmetric

stretch (vx ) is found at 1018 cm

-1

. The experimentally observed frequencies of the other

fundamental internal vibrational modes (designated v 3 , v 4 , and v 2 ), which are those predicted

from theory, are indicated (cf. Table 1) [58]. From spectroscopic studies - such as these described above - of known materials and compounds, reference spectra are obtained to aid

the interpretation of unfamiliar spectra. The spectra of microsamples of known identity and composition also serve to establish limits of detection for classes or specific types of compounds of interest.

174
Table 1. Raman shifts of sulfates in the solid phase.

S0 4

2 ~ Frequency Shift, cm

-1 ompound

i 2 S0 4 -H 2 0

a 2 S0 4 Na2 S03 , sulfite)

S04 NH4 ) 2 S0 4 iS0 4 -(NH 4 ) 2 S0 4 -6H2 0 aS0 4 aS04 -2H 2 0

"2 ^3 ^4 Asymrn Stretch Asyrnrn. Bond

1 008 518 1118

997 472 455 1 1 62 1135, 1110 CCl fxAC] 983 632 947 985 452 1 120 976 452, 447 1062, 1075, 1089 617, 612

985 455 1069, 1098, 1134 623 1018 497, 418 1060, 1128, 1108 674, 628, 608

1006 493, 413 1142, 1135, 1116 670, 623

ree S0 4 981 451 ! 104 613 2 ion The Raman shifts observed from microparticles of several common crystalline sulfates

ire given in Table 1 [59] and are representative of the internal vibrational modes (S-0 tretching or bending) of the S0 4

2 ~ ion of tetrahedral symmetry. The frequencies of xternal or lattice modes characteristic of the crystal lattice are not given. Sulfates and

ulfites (cf. Na2 S0 4 vs. Na 2 S0 3 ) can readily be distinguished, as the sulfite ion has

>yramidal symmetry. Similarly, a comparison of the frequency shifts for the sulfate ion in mhydrite (CaS04 ) and in gypsum (CaS0 4 -2H 2 0) allows distinct hydration states to be issigned to these solids [58,60]. The Raman shifts given for the free S0 4

2 ~ ion correspond

;o the frequencies of the fundamental modes of the ion in solution (cf. figure 9) [59]. For the analysis of airborne particles we have used samples collected by impactors as

veil as filter samples obtained in the use of conventional high-volume air sampling equipnent. In this work, described in detail elsewhere, we have reported critical observations

•egarding the sampling process [36]. Evidence was presented for the chemical transformation

3f particles in cases where bulk sample collections were made over extended periods of

ampling. Specifically, particle reactions could be inferred that resulted from exposure of

the filter-collected sample to ambient atmospheric acid aerosol. These observations

indicated the importance of unambiguous sampling and suggested a useful application of the

taman microprobe to the study of the sampling process itself. Spectroscopic evidence for

this kind of an effect is shown in figure 10. The particle analyzed was isolated from a oulk sample of St. Louis urban dust which had been collected on a glass fiber filter

employing a high-volume air sampler. Qualitative comparison of the spectrum of the particle

rfith reference spectra [58,61] identifies the unknown to principally consist of calcite

(CaC03 ) as the major component and insoluble anhydrite (CaS0 4 , cf. fig. 9) as a minor

component. All five Raman active modes of CaC0 3 (1432, 1088, 714, 283, and 156 cm

-1

) are present [61]. The 1432 cm

-1 band is almost completely obscured by the broad spectral

feature in the 1200 to 1700 cm

-1 region. This feature entails two band maxima at M350

and ~1600 cm

-1

, assigned to the carbon bands characteristic of polycrystal 1 ine graphite.

They arise from the presence of (or contamination by) a form of carbon similar to soot. Bands similar to these have been observed in the spectra of many different types of environmental particles (cf. figure 5). In some of the spectra obtained from airborne dust

particles, these were the only discernible features. The presence of CaS0 4 as a minor

constituent is indicated by the band at 1018 cm

-1 (cf. Table 1). This feature is the most

prominent one in the spectrum of CaS04 , and on the basis of its intensity and the rela- tively high spectral background we do not expect to be able to discern the other characteristic bands. We have interpreted the presence of CaS04 to indicate the partial transformation of CaC0 3 by acid aerosol [36]. 175
3000 2000 cm 1000 0

Figure 10. Raman spectrum of a particle of calcite (CaC0 3 ) in urban air particulate dust. Measurement conditions are indicated.

C. Microparticulate Organics

Airborne particles can also be of organic origin and composition (e.g., pesticide

dusts) or they may consist of an inorganic core (e.g., oxides produced at high temperatures,

-fly ash) with a surface layer of an organic material formed by the condensation of organics in the vapor phase (e.g., polycyclic hydrocarbons from the combustion of fossil

fuels). A large fraction of the organic material in ambient air is found with atmospheric

particles in the respirable size (<10 urn) range [62]. Many of these compounds are sus- pected carcinogens. Raman microprobe techniques are eminently suited for the characterization of microparticulate organics and polymers, or hydrocarbon films [18,36,48]. Organic

compounds give informative, diagnostical ly useful Raman spectra [63]. Many different types of organic compounds have been examined in the Raman microprobe

[8]. These studies have established practical limits of detection for various classes of organics and have provided some insight into potential measurement difficulties as well as problems in the interpretation of the spectra - due to their complexities - that one can expect to encounter with organic molecules. Two examples from these measurements are shown in figures 11 and 12, for microparticles of laboratory-grade materials. Certain organochlorine pesticides have been recognized as persistent environmental chemicals and

are known to be transported in air. They are colorless, crystalline solids, and are therefore not expected to heat or modify in the microprobe measurement, nor would these compounds be expected to give rise to fluorescence interferences. The chlorocarbon insec-1- ticides kepone and mirex, for example, are closely related compounds and have many similar properties [13]. Their spectra (fig. 11) permit these two pesticides to be readily dis- tinguished. This shows that even though closely related molecular solids have similar

spectra, spectral regions can usually be found which allow positive discrimination between

the various possibilities.

176
KEPONE 5g

b°eom~ 14 ^d'ameTer'''

Pmhole 140 urn O U Scon rate 0.83 0

Full scole |q3counls

-4- A*

1

i i i

i 2000 cm -l

SompleMIREX SiieS^pn c , Sjbslrote Li F r\~

L

°p

5o««M

l O nXtotson.pl.) b,.m- |4 pn, M. Spec.-ol SID -Olh 3 cm"' 61 - -

T.me constont 0.3 5 P.nhole 140 ,,LScon role 3.33 cnf<A

^11 scole «».s

1

1 1 1 1 000

Figure 11. Reference spectra of microparticles of the chlorocarbon

insecticides kepone and mirex.

177
tnt

568 2 nm

\

647.1 nm

I

I r—l

1 1 1 1

1 1 1 1 1 1 1 1 r 3000 2000 1000 0

cm- 1

Figure 12. Spectra of microcrystal s of trinitrotoluene (TNT) excited at two laser wavelengths. Measurement parameters: Top - particle size, 20 x 60 pm; power, 8 mW

(at sample); beam spot, M6 pm diameter; time constant, 2.0 sec; scan rate, 50 cnrVmin. Bottom - particle size, 15 x 25 pm; power, 30 mW (at sample); beam

spot, ^12 pm diameter; time constant, 2.0 sec; scan rate, 50 cm

_1 /min. For both spectra - spectral slit width, 3 cm

-1

; pinhole, 140 pm; intensity, 1000 counts

full scale. Particles supported by a sapphire substrate. Bands marked S in lower spectrum are due to substrate fluorescence.

Spectral changes induced by laser irradiance are frequently observed in the analysis of organic microparticles. However, these changes cannot always be fully explained as resulting from thermal ly- i nduced modifications of the sample, but may result from photo- decomposition (e.g., photooxidation, photolysis), as many organic molecules are unstable to high-intensity visible laser radiation. The spectra of figure 12, of two microcrystal s of trinitrotoluene (TNT explosive, straw-yellow colored) excited with the yellow and red line

of the laser, illustrate this kind of observation. The bands in the TNT spectrum arise from vibrations of the phenyl (C 6 ) ring, C-H and ON bonds, and vibrations of the N0 2 groups

[63]. No spectra could be obtained with green line (514.5 nm) excitation owing to instan- taneous sample decomposition (melting point 82 °C). The top spectrum - obtained under low- irradiance conditions - shows a slowly progressing sample modification, evidenced by the changing or developing background during the course of the measurement. This luminescent background cannot be attributed to thermal radiation (incandescence), for the microcrystal

is still at a low (noni ncandescent) temperature well below its melting point. From this observation we cannot exclude - in this and other such examples - the possibility of the optically-induced formation of a fluorescing species. Since the substrate material is sapphire, we note in the bottom spectrum the fluorescence interference (cf. fig. 7) from trace amounts of chromium (Cr3+

) in the sapphire, appearing as a sharp doublet at 1021 cm 1 and 1050 cm

-1 with red-line excitation. The TNT particle spectra thus illustrate a back- ground interference problem which is excitation dependent but not necessarily thermally

i nduced.

178
South Pole Atmospheric Aerosol

The chemical composition of South Pole atmospheric aerosol is of interest in many areas atmospheric science, particularly in relation to a better understanding of the global ansport of pollutants in the lower stratosphere and to the long-range effects on the

rth's climate. A major thrust of stratospheric aerosol studies has been in the physical

d morphological characterization of the aerosol [64,65]. Microchemical spot tests have

lown sulfate to be a principal component of the aerosol. Results of scanning electron

croscopy (SEM), energy-dispersive x-ray microanalysi s , x-ray diffraction, and wet-chemical

iudies have implicated the existence of H 2 S04 , (NH4 ) 2 S04 , and (NH 4 )2S2 0 8 [65]. As part of larger, joint study with the University of Maryland on the characterization of South Pole

rosol , particulate samples from the antarctic atmosphere were collected for micro-Raman

vestigation [15]. The samples were obtained during two research expeditions to South Pole

ation, Antarctica. The collections utilized gound-based air samplers; both sapphire and thium fluoride substrates were employed with size-segregating impactors. The results of

e microprobe analysis give direct evidence for the existence of sulfate species in the

uth Pole aerosol. However, further studies are needed to clarify many remaining questions

ncerning the i_n situ nature of the aerosol. Foremost are questions pertaining to sampling

fects, the likely reactions of the acid aerosol with other atmospheric constituents, and

th the collection substrate, as well as chemical transformations that may have occurred

iring sample storage and handling [15]. Most of the measurements were performed on aerosol collected on the two lower impactor

.ages (size cut-off <4 urn) as the upper three impaction stages bore virtually no

iterial. The bulk of the material found on the fourth and fifth stages was of size less

tan ~2-3 urn and consisted of discrete microparticles and extensively agglomerated submicro-

;ter aerosol. Since the samples were inadvertently exposed to ambient laboratory air and

l many cases to humidity conditions high enough for moisture absorption to have taken

ace, the extreme hygroscopic nature of the aerosol could be noted. In some samples,

icroscopic droplets were seen to have formed and to have coalesced, forming larger micro-

"oplets. Thus, measurements were made also on particles formed by the recrystal 1 ization

; such droplets when samples were returned to conditions of low (^20 percent relative)

-imidity by flushing the sample compartment of the instrument with dry nitrogen. SEM/x-ray analysis of all aerosol samples showed sulfur as the only element detected

r id revealed two different crystalline morphologies. Particles of one distinct morphology

?re identified with ammonium sulfate and were found on both sapphire and lithium fluoride

jbstrates. The second distinct morphology has only been observed for particles sampled on

rf substrates which on the basis of their spectra were shown to consist of lithium

fjlfate. Figures 13 and 14 show representative spectra oDtained in these studies of the South

.3le aerosol. The spectrum of figure 13 is from one of the recrystall ized particles located

,n the fourth stage (sapphire substrate) of an impactor sample. Examination of the positions, intensities and shapes (cf. Table 1 and fig. 9) of the observed Raman bands

.ndicates that the microcrystal principally consists of (NH 4 ) 2 S0 4 [57]. The bands arising

.Vom S04

2 ~ vibrations are seen centered at frequencies 452, 614, 977, and 1080 cm

-1

, 'elative to the band intensities observed for the sulfate vibrations, we do not expect to

jetect the bands due to the internal vibrations of the NH4+ ion because of their compara-

.ively much weaker scattering intensity. These bands have shifts centered at 1429 and

.669 cm

-1

. The two broad bands at ~1 350 and ~1 600 cm" 1 are the carbon bands discussed

•efore (cf. figs. 5, 6, and 7) and indicate some amount of a carbonaceous contaminant

ossibly adsorbed by the particle during sample handling. The result shown in figure 14 is insistent with the observations made in the sample analysis discussed above. In this case

.he aerosol had been collected on a lithium fluoride substrate. The spectrum is from a icroscopic region (~6 urn in diameter, defining a sample size estimated to be well under

j ng) within a dense deposit of profusely aggregated submicrometer particles. A useful pectrum from anywhere in this sample area could only be obtained with 647.1 nm excitation,

s excitation with the 514.5 nm line produced intolerably high spectral background levels,

oth morphological forms were observed in the area analyzed, and the normally smooth and

olished substrate surface appeared rough and pitted. Again, the principal bands point to mmonium sulfate as the major component of the aerosol, based on frequency assignments made

'ith reference to neon calibration lines omitted from the spectrum but indicated by bars

•elow the recording trace. However, a second component is indicated by the band with Raman

179
shift 1008 cm

-1

, which in this analysis is attributed to the sulfate symmetric stretch in lithium sulfate (presumably Li 2 S0 4 -H 2 0; cf. Table 1) [66]. Other bands characterizing

Li 2 S04 are much weaker and are not seen owing to the appreciable spectral background. Microprobe analysis of other sample regions showed lithium sulfate to be associated with ammonium sulfate to varying degrees, with some spectra being diagnostic of an essentially

pure, hydrated phase of Li 2 S0 4 [15].

SOUTH POLE XI.7 atmospheric AEROSOL

514 5 nm

8 urn beam

106 mW

33cm-'/s

substrate Al203 -s

| Uij p ii i n 1 1 r

Figure 13. Raman microprobe spectrum of impactor-col 1 ected South Pole aerosol, Stage 4 Indicated are excitation wavelength, size (diam.) of laser spot, laser powei (at sample), scan rate, and sample support. Measurement time constant, 1.' sec; spectral slit width, 3 cm

-1

. Particle analyzed is ~3 pm in size. Band: labeled P and S are due to the particle and substrate, respectively.

Figure 14. Microprobe spectrum of submicrometer South Pole aerosol collected on Stage 5 Measurement conditions are indicated. Other parameters are: time constant

10.0 sec; spectral slit width, 3 cm

-1

; intensity, 1200 counts full scale.

ISO
From these observations we conclude that a sulfate component (e.g., H 2 S0 4 , HS04") of atmospheric aerosol has undergone a chemical transformation in the sampling process, as

n from its reaction with the Li F substrate resulting in Li 2 S0 4. This is reasonable, for

'hium fluoride is a reactive material, whereas sapphire is not. Further evidence of the

irosive nature of the sampled aerosol was seen in samples collected on sapphire substrates

ring thin-film aluminum (particle finder) grids. For these samples the aluminum film had

roded away in all areas where the acid sulfate aerosol had impacted.

We have verified these conclusions by measurements of laboratory-generated aerosol.

furic acid aerosol collected on Li F substrates reacts instantaneously forming micro-

•stalline material of the same morphological characteristics as are noted in the South

e samples. Microprobe measurements show these to be Li 2 S0 4 microcrystal s. When

ionium sulfate aerosol is sampled on Li F and stored under ambient laboratory conditions

several days, no aerosol-substrate interaction is evident. Analysis of Fly Ash from Power Plants

1. Stack Particulates from Oil-Fired Combustion

To assess the effect of pollutant particles emitted from power plants on man and the

'ironment, more information is needed on the composition of fly ash. Existing data on the

i»mical properties of fly ash are largely limited to the elemental composition of bulk

iples of particulates collected in the stack and in the plume of power plants. Most of

at is known about fly ash has been determined from the study of particulate emissions from

al-fired plants. In comparison, much less has been learned about the emissions from oi 1 - "ed power plants. In work reported on the analysis of particulates from fuel oil combus-

>n, the emphasis has been on relating the physical/chemical properties of bulk samples of

5 ash to the elemental composition of the fuels used and the conditions of the combus-

»n. The crude oils burned in power generation exhibit wide variations in sulfur content vpically 0.5-2.5 wt.% S) and in the inorganic trace element composition. Vanadium is jally the major heavy metal (typically 5-400 ppm V) component. Few studies, however,

; /e appeared on the characterization of single particles emitted by oil-fired power

ants [67]. We have applied the Raman microprobe to the study of stack aerosols and fly ash

rticles from power plants [68]. The most extensive measurements have been made on stackspended particulates from an oil-fired power plant [13,68]. Stack aerosol samples were

llected by extractive (i.e., out-of-stack) sampling employing five-stage cascade impactors de available to NBS for feasibility studies by the Environmental Protection Agency (EPA).

5 particular power plant monitored was one burning a fuel of relatively high sulfur (about

5 wt.% S) and vanadium (approx. 400 ppm V) content. Chemical analysis of the fuel also

awed trace concentrations of Ni (16 ppm), Fe (6 ppm), and Mg (5 ppm). Particle sampling

s conducted at a sampling port where the stack temperature was 164 °C. Representative of

ese stack aerosol deposits on sapphire substrates is the collection of particles shown in

e optical micrograph of figure 15. The field contains the various types of solid particutes found on the fourth impaction stage. Observation in the light microscope shows wide

riations in the size and shapes of particles and in optical properties, with microcrystal

dendritic morphology showing colors from brown to yellow-green and particles of globular

pe exhibiting similar colors in a generally colorless, transparent matrix interspersed

h bits of black, opaque material. The majority of the particles on this and on the other

ages of the sampler are too large to be accounted for by the size cut-off characteristics

each stage. This indicates that much of the material found in these samples has formed

the collection surface through the interaction of solid/liquid microparticles with other

mponents of the gas/vapor phase of the sampled stack aerosol.

181
Figure 15. Optical micrograph of oil-fired power plant stack particulates collected on

a sapphire substrate. Emissions found, on the fourth stage of a five-stage impaction sampler.

Typical of the results from particles with dendritic morphology is the spectrum showi

in figure 16, obtained from probing a small area of the large, four-leaf microcrystal (cf. fig. 15). The predominant features in this and numerous other spectra from particles c

this type are bands with Raman shifts of about 145, 280, and 1000 cm

-1

. Taken together

these are characteristic of vanadium pentoxide (V2 0 5 ) [69]. Qualitative comparison with

| reference spectrum shows good agreement, except for several medi urn- i ntensity bands in th< region 820-970 cm

-1 which are absent in the spectrum of pure V 2 0 5 (assigned frequencies an

104, 144, 285, 406, 701, and 995 cm

-1

) [13,69]. These additional bands are due to a secom

component, so far unidentified. However, they are absent in the spectra of numerous other!

brown dendritic microcrystal s (of size down to a few micrometers) whose spectra are, in al respects, identical to that of V 2 0 5

.

Figure 16. Raman spectrum recorded from probing a small region of the large, four-leavf microcrystal seen in the micrograph of figure 15. Measurement conditions us( in the analysis are indicated.

182
Our finding of V 2 0 5 as a principal component of these particulate emissions is consisit with results reported from a study of oil ash particles by Auger microprobe analysis

rj. From the peak height ratios of V and 0 observed in the Auger spectrum, it was conjded that these elements existed in these particles as V2 0 5

. Microparticles of different colors and morphologies have yielded spectra characteristic

other compounds. The particles of globular shape (cf. fig. 15) exhibit spectra many of

ich indicate the presence of complex crystalline sulfates. (To this point, vanadyl

lfate - VOSO4 - has not been found in these particle collections [13,69]). They typically

dw four well-resolved bands, with a strong, sharp band around 985 cm

-1

, and broader bands

lesser intensity centered around 625, 460, and 150 cm

-1

, the last being a lattice mode, ^se features are indicative of crystalline double sulfates, and in particular hydrated

;tal ammonium sulfates [70]. We suspect that particle transformations have occurred from

Dosure to ambient ammonia.

In the analysis of stack particles from these impactor samples, our interpretation

the spectra invariably must take into consideration the effects of the measurement on

9 sample. Figure 17 shows a typical result from the analysis of a stack particle for

ich this series of consecutive spectra documents measurement- i nduced sample changes. The

3 (A) and bottom (C) spectra were obtained under identical, low-irradiance conditions; the ddle one (B), at high irradiance. The spectra permit the following interpretation,

ckel ammonium sulfate, NiS04-(NH 4 ) 2 S04*6H 2 0, is the major - and, in the top spectrum the

ly - component of the microparticle identified by comparison with Raman data cited in the terature [70,71] and reference spectra obtained from particles of this salt. The crystalne solid has its strongest band {v 1 stretching mode) at 985 cm

-1 and the other internal lfur-oxygen modes at about 455, 625, and 1110 cm

-1 (cf. Table 1). The high-i rradiance

"asurement (B) gives evidence of a second (minor) component, with the appearance of a band

144 cm"1

, characteristic of V 2 0 5

. Other bands due to V 2 0 5 are obscured by the high minescent background of the spectrum. In parallel measurements on microparticles of two

'tier oxides of vanadium, V2 0 3 and V2 0 4 (or V0 2 ), we have shown that these lower oxides are ansformed by the intense laser radiation (via thermal oxidation) to V2 0 5

. Both of these

wer oxides are dark (black/green) colored and are highly absorbing at 514.5 nm. The

ddle spectrum also shows the graphitic carbon bands. The third measurement (C) shows proved signal-to-background resulting from sample changes that affected the presence of minescing (e.g., fluorescing) constituents or contaminants.

183
Figure 17. Spectra of a stack particulate from an oil- fired power plant, illustrating laser- induced spectral changes. Analysis conditions: particle size, 8x12 pm; substrate,

a-Al 2 0 3 ; laser, A0 = 514.5 nm; spectral slit width, 3cm"1

; intensity, 1000 counts

full scale. Parameters varied: power (at sample), 25 mW (A,C), 120 mW (B); beam

spot, ~18 pm diameter (A,C), ~8 pm (B); time constant, 3.0 sec (A,C), 1.0 sec (B); scan rate, 20 cm

-1 /min (A,C), 50 cm_1 /min

(B). Bands marked S arise from the scat- tering by the sapphire substrate.

2. Coal Fly Ash

Some results have been obtained in the study of coal fly ash particles, and their

spectra have been correlated with microprobe spectra of synthetic glasses of known elemental composition [68]. The bulk of coal fly ash consists of solids of glass-like structure

formed by high-temperature processes. The matrix of the ash consists primarily of insoluble

al umi no-si 1 icate glasses, with the surface layers of ash particles usually showing a predominance of certain trace elements [72]. Our conclusions drawn from a study of these spectra are in agreement with those drawn by others from spectroscopic studies of bulk glasses and various mineral silicates of glass-like structure [73,74]. The lack of long- range crystalline order in these materials results in extensive broadening of most spectral

features. The vibrational spectrum reveals the type of glass (e.g., high or low silica content) but is much less indicative of the composition of the material. Thus, certain

mineral glasses produced by high-temperature reactions may yield well-defined and reasonably

intense Raman spectra, whereas others give extremely poor spectra because of the low degree

of order in the glass network. It can be generally concluded that the more complex the composition of a glass becomes, the weaker and the more diffuse the Raman bands become. Spectra are then usually flat and featureless; sometimes a sharp band may be identified with

included bits of a crystalline phase (e.g. , silicate).

1 84
Characterization of Silicate Minerals

Mineral fibers and particles in the environment have been of increasing concern as a alth hazard, particularly the sheet and chain silicates commonly termed asbestos. We

ye employed the Raman microprobe to obtain characteristic spectra of some common sheet and

ain silicates (anthophyl 1 ite, tremolite, and talc are the principal minerals discussed

-e) and to identify any differentiating features in the spectra that would permit the

Drous and nonfibrous forms of a given mineral to be distinguished [16]. Raman spectra of both talc plates and fibers (pictured in figure 18) are presented in gure 19. These spectra show essentially identical features and are indistinguishable.

?ctral investigations of both fibrous and nonfibrous forms of other silicates showed

rresponding results. No systematic differences were found in the Raman spectra of the

orous and nonfibrous morphologies of a given mineral; however, each mineral has a distinct

i characteristic Raman spectrum.

Figure 18. Scanning electron micrographs of talc particles. Areas of investigation by Raman

and electron microprobes are indicated by

a square. A: 47.4 x 1 . 7 urn fiber; magnification, 2800; working distance factor,

0.32; elemental composition by electron microprobe - Mg, Si. B: 33.1 x 23.5 urn platy crystal; magnification, 2800, working distance factor, 0.90; elemental com- position by electron microprobe - Mg, Si.

185
A

iku„ Li J A

^

1

B

1200 600 _. 0

Figure 19. Raman microprobe spectra of fibrous and platy talc. A: 47.4 x 1.7 um fiber pictured in fig. 18A; substrate, LiF; laser, A0 = 514.5 nm; power, 75 mW (at sample); beam spot, ^8 pm diameter;

spectral slit width, 3 cm"1

; time constant, 2.0 sec; scan rate, 20 cnrVmin;

intensity, 1000 counts full scale. B: 33.1 x 23.5 urn platy crystal pictured in

fig. 18B; same conditions as for spec- trum A except time constant, 6.0 sec; scan rate, 10 cm

_1 /min.

There are similarities in the spectra which are useful in establishing the type of major structural units and their coordination in the lattice. All the minerals studied have

in common a silicate strip formed by crosslinking pyroxene chains. The bands associated

with the silicon-oxygen motions are assigned in the regions from 600 to 1200 cm

-1 [75,76].

A brucite-1 ike strip exists between silicate layers and is composed of octahedrally

coordinated cations (Mg2+ in talc and tremolite) and thus metal-oxygen vibrational modes

are observed in the region between 200 and 450 cm

-1 (compare figures 20A and 20C). Some silicate network deformation modes also extend into this region. The increased complexity

of this region as observed in the tremolite spectrum (figure 20A) results from the existence

of cations in sites characteristic of amphiboles either of different coordination or non- equivalent to the octahedral sites of the brucite layer. The Raman spectra of microscopic

particles of talc and tremolite exhibit sharp, well defined peaks indicating a high degree

of site occupancy and structural order. Using these spectra as representative of the .ordered structure, we can predict, to some extent, the effects of both a simple cationic substitution as in actinolite (where Fe2+ replaces Mg2+

) and a major compositional variation

and site occupancy disorder as in anthophyl 1 ite (figure 20B). In this spectrum, broadening,

shifting, and splitting of spectral features are observed in those regions characteristic

of the metal-oxygen modes and in the very low frequency, external lattice mode region below

200 cm

-1

.

106
A

i 1 1

B

C-t

[ /

Figure 20. Raman spectra of single microparticles of tremolite

(A), anthophyllite (B), and talc (C). A: tremolite - particle size, 12 x 30 urn; substrate, LiF; laser, A0 = 514.5 nm; power, 90 mW (at sample); beam spot, ^6 urn diameter; spectral slit width, 3 cm"1

; time constant, 0.5 sec; scan rate, 50 cm"1 / min; intensity, 1000 counts full scale. B: anthophyllite - particle size, 10 x 20 urn; same conditions as for A except power, 95 mW (at sample). C: talc - particle size, 5x6 urn; same conditions as for A except power, 75 mW (at sam- ple); beam spot, ~8 urn diameter; time constant,

1.0 sec.

1200 600

Analysis of Fluid Inclusions in Minerals

The analysis of fluid inclusions in minerals provides information on many mineralogcal , geological, and geochemical processes. These inclusions consist of microscopically

rapped and confined liquid and gaseous phases and frequently coexisting solid phases

daughter crystals). Fluid inclusions are abundant in many terrestrial mineral samples and

lay be as large as several hundred micrometers.

Raman microprobe techniques have been successfully applied to the non-destructive

,nalysis of microscopic inclusions in minerals [9,55,77]. These studies have included the identification and characterization of microscopic solid (e.g., CaS04 ), liquid (e.g., dissolved S04

2 ~, C0 3

2 ~, C0 2 ) and gaseous phases (e.g. , C0 2 , H 2 S, CH4 ). A result from this field of investigation is shown in figure 21. The sample analyzed

js a specimen of natural quartz (a-Si02 ) in which was localized an irregular inclusion of

'ize ^68 urn (diam.). The upper face of the inclusion was urn below the surface of the

uartz host. By examination in the Raman microprobe, the inclusion could be shown to jontain two separate phases (solid and liquid), consisting of several microscopic daughter

rystals in the brine within the fluid inclusion. The spectra of figure 21 are representaive of these inclusion studies. The spectrum of the host mineral is characteristic of rystalline quartz [59,78]. The liquid phase portion of the inclusion consists of a brine

i.e., a salt solution) in contact with several microscopic daughter crystals. The spectrum

f the brine shows bands characteristic of dissolved sulfate (cf. Table 1 and fig. 9)

56]. The sharp band at ^981 cm

-1 corresponds to the symmetric stretching mode (vx

) of

0 4

2 ~ in aqueous solution. Broader bands centered around 1640 cm-1 and 3400 cm-1 are ssigned to the bending and stretching modes, respectively, of the water in the brine,

hese bands are all superimposed upon the spectrum of the host (which represents an interference). The third spectrum is that of a typical daughter crystal, a platelet only a few icrometers (<10 urn) in size. Comparison with a reference spectrum of anhydrite identifies

his to be CaS0 4

. 187
HOST QUARTZ

.. A jjJl

BRINE 1 At H

20-bend / \ i Ai

1

DAUGHTER

CRYSTAL — 1

1 °

3400 3000 ANHYDRITE

(REF.)

cm" 1 1500 000 [.ii500

0

0

Figure 21

Spectra recorded in the Raman microprobe

analysis of fluid inclusions in a sample

of natural quartz. From top to bottom:

(i) spectrum of the host (a-Si02 ); (ii) spectrum of brine inclusion containing dissolved sulfate; (iii) spectrum of daughter crystal (CaS04 ), size 5x7x4 urn; (iv) reference spectrum of CaS0 4 crystal. Spectra recorded with 514.5 nm excitation,

80 mW laser power (at sample), ^6 urn diameter beam spot, 3 cm

-1 spectral resolution. Raman frequencies of the refer- ence anhydrite are marked along the base

line of the spectrum of the daughter

crystal

The concentration of dissolved sulfate in the brine has been estimated to be 12 ppt, based on calibrations that suggest a detection limit for dissolved sulfate in such systems

of at least 1 ppt. Often severe limitations to inclusion studies of minerals result from heating of absorbing phases within the inclusion and from spectral interferences by the host [55]. These same considerations apply to the analysis of cellular inclusions (e.g., micro- scopically localized, bioaccumulated waste products) in biological tissues.

H. Microanalysis of Biological Tissues

In the study of biological samples of macroscopic size, Raman spectroscopy has evolved

as an effective method for elucidating the structure and conformation of biomolecules

[79,80]. With the advent of Raman microprobe techniques, great possibilities for unique investigations appear to be opening up in biology, pathology, and tissue research to obtain molecular information at the cellular level. To explore these possibilities, the Raman spectra of microsamples of pure biological molecules have been examined, and these studies

have been extended to investigations of standard histological sections of biological tissues

[17,18]. The biological compounds studied in the pure state are "simple" molecules (e.g.,

urea, cholesterol, amino acids, sugars), nucleotides (e.g., ADP, ATP), and proteins (e.g., bovine serum albumin, collagen). These biomolecules give a richly detailed vibrational spectrum with good sensitivity and are amenable to molecular-level interpretation. Tissue studies have been made in two areas of application, the characterization of mineralizing tissues [17] and pathological microanalysis [18]. The diagnostically useful spectra obtained from these fragile biological materials were correlated with the information from conventional morphological and x-ray microanalytical methods [40,41]. Information regarding the precise distribution, relative abundance, and molecular identity of the 188
onstituents in such biological matrices is a significant contribution towards understanding

any essential tissue and cellular processes. Initially there was some concern that biological tissues would be quickly burned under

he intense irradiation. Under carefully chosen measurement conditions this has not proved

o be the case, however, and multiple sections of tissue conventionally prepared have been

table in the beam so that quite satisfactory spectra could be obtained. In the analysis of

oft tissue with 514.5 nm excitation, laser irradiances typically in the range from 2 to

0 kW/cm2 have been utilized. In investigations of hard tissue (e.g., bone and tooth), rradiance levels as high as 0.2 MW/cm2 have been safely focused onto the specimen without

eleterious effects. Fluorescence interferences have been encountered in some situations

e.g., analysis of lung sections) and the origin of this fluorescence can sometimes be raced to sample preparation.

Hard tissue formation is a complex process consisting of different steps. Although mch research on individual stages of this process has been done, the detailed molecular

ransformations of the matrix elements are incompletely understood. Of particular imporance in this research is the non-intrusive examination of the intact tissue and the

letermi nation of the principal components.

In collaboration with workers at the NIH National Institute of Dental Research, the NBS

licroprobe was used in the examination of thin (5-10 urn thickness) sections of cartilage,

ione, and tooth. Of interest in the study of these specimens are the processes leading to

.he calcification of tissues and the premineral ization of bone. This requires the ability

.o distinguish - in microscopic regions of the tissue - between organically and inorgancally bound calcium and phosphorus, for example.

Two types of mineralizing tissue have been studied most extensively, the enamel of the :ontinuously erupting rat incisor and the embryonic chick tibia [17]. For these types of

-issue, the initial site and regions of progressive mineralization can be easily located in ippropriately prepared cryosections and examined independently.

The major inorganic component of vertebrate hard tissue is an impure (biological)

lydroxyapatite, Ca 10 (P04 ) 6 (OH) 2 , with small amounts (typically ^2-4%) of carbonate in the

lature tissue. The chief organic component of mineralizing tissues consists of a hydrated

>roteinaceous matrix, collagenous in the case of bone and dentin and non-col 1 agenous for

n'neralizing enamel

The section of chick tibia shown in the light micrograph of figure 22 is representative

)f mineralizing tissue samples that have been prepared for Raman microprobe analysis. Good

-.pectra have been obtained in measurements with spatial resolution typically of 6-15 pm from

ireas in the mineralized and non-mineralized zones (i.e. , cartilage) of the tibia [17].

1. Biological Mineralization

189
Figure 22. Photomicrographs, in transmitted light,

of thin sections of biological tissues analyzed in the Raman microprobe. (a) 13-day embryonic chick tibia (7 urn thickness), air dried. Opaque, dense regions

are mineralized zones; lighter regions constitute collagenous tissue matrix,

(b) Standard (5pm) section of lymph node with foreign bodies of silicone rubber within multinucleated giant cells. Stained (hematoxyl i n-eosi n) . Arrows

indicate several typical inclusions of silicone polymer. Asterisk shows cyto- plasmic area analyzed to obtain the spectrum of the host tissue matrix.

The spectra of figure 23 were obtained from sequential measurements across a region in rat incisor enamel and indicate the progressive mineralization (from a through d) of the

tissue. The spectra are composed of the features characteristic of hydroxyapati te [45,81] superimposed on the spectrum of collagen [82]. The four fundamental modes specific of the

internal vibrations of the orthophosphate ion (P0 4 3_

) in the apatite lattice are the strong

V! (P-0 symmetric stretch) at 962 cm

-1

, the v 2 (O-P-O symmetric bend) between 400-500 cm

-1

, the v3 (P-0 asymmetric stretch) between 1000-1100 cm

-1

, and the v4 (O-P-0 asymmetric bend)

in the region 560-620 cm

-1

. The ^960 cm

-1 band is the most prominent and is a sensitive

indicator to changes in the extent of mineralization. The spectra of figure 23 illustrate

the dramatic increase in the intensity (approx. eight-fold) of the ^960 cm

-1 band from an area (a) in the mineralizing front to a point at the denti no-enamel junction (d).

190

3
Figure 23. Sequential Raman microprobe spectra obtained from microscopic regions (yl pm apart) in air dried section (10 pm thickness) of mineralizing rat incisor enamel. Tissue area analyzed extends from the mineralizing front (a) into the denti no- enamel junction (d), a distance of ^30 pm. Measurement conditions: laser, A 0 = 514.5

nm; power, 20 mW (at sample); beam spot, ^7 pm diameter; spectral slit width,

3 cm

-1

; time constant, 15 sec; scan rate,

5 cnrVmin. Tissue section supported by

a sapphire substrate.

These studies on mineralizing tissues are continuing. Our efforts are aimed at a more

complete understanding of the compositional and structural information obtained from the

spectra, with the hope that some insight can be gained regarding any changes in protein

structure and conformation during the development of biological mineralization.

2. Diagnostic Pathology

Thin sections (5-10 pm thickness) of human biopsy tissue have come under study for the suspected presence of microscopic foreign bodies of silicone polymer [18]. These had been previously examined by pathologists at the University of California, San Diego, using conventional methods. In one case study, the biopsy tissue was one from a patient with

axillary lymph node complications which were suspected to be related to an implanted

silicone rubber finger joint prosthesis. Standard histologic sections (5 pm; embedded in paraffin) of this biopsy material had been prepared for initial examination by light microscopy, scanning electron microscopy (SEM), and x-ray microanalysis. Other para! lei sections

(unstained) of the lymph node were mounted on sapphire substrates and deparaff i nized with

xylene for subsequent Raman microprobe analysis. Microscopically, the tissue showed

enlarged lymphoid follicles and many multinucleated foreign body giant cells, some of which

contained irregular pale-yellow fragments of a translucent material 5-60 pm in diameter. A light micrograph of a stained section of the lymph node, in figure 23, shows this foreign

material within giant cells. SEM/x-ray analysis had demonstrated that these foreign

bodies contained silicon. This suggested that the microscopic fragments were, in fact, silicone rubber particles from the prosthesis, but direct molecular identification was not possible from the information furnished by the x-ray spectrum. When the tissue section on the sapphire substrate was viewed in the microscope of the Raman microprobe the histology

was observed even in an unstained section. Spectra were obtained from various parts of the

tissue, and these are shown in figure 24. Measurements were made on areas of the tissue

(i.e., the cytoplasm matrix or host) away from the inclusions of foreign material. Spectra

were then obtained from a dozen individual inclusions, which showed identical and characteristic peaks at several frequencies. These were compared with spectra obtained under the

same conditions from particles abraded directly from a new silicone rubber joint prosthesis. The inclusions in the giant cells gave spectra identical to that from the prothesis

material with additional peaks attributable to the tissue matrix. The micro-Raman spectrum

191
of the prosthesis material is identical to published bulk Raman spectra of polydimethylsiloxane polymers (silicone rubber and gel) [83].

Figure 24. Spectra recorded in the Raman microprobe analysis of a deparaffinized standard

5 urn section of lymph node (cf. fig. 22), mounted on a sapphire (a-Al 2 0 3 ) substrate. Measurement parameters common to each spectrum: laser, K0 = 514.5

nm; beam spot, ^16 urn diameter; exit pinhole, 140 urn; spectral slit width,

3 cm

-1

. Top: spectrum of the cytoplasm away from foreign bodies; power, 40 mW

(at sample); time constant, 5.0 sec; scan rate, 20 cm _:l /min. Middle: spectrum

of a foreign body (size, ^-24 urn) located within a giant cell. Measurement con- ditions as for top spectrum. Bottom: spectrum of a small (~60 um) particle of silicone elastomer from a joint prosthesis. Conditions as for top spectrum, except - power, 60 mW (at sample); time constant, 0.5 sec; scan rate, 100 cm

_1 /min. Bands marked S on the upper and middle spectra are contributed by the sapphire substrate.

This study illustrates the effective potentialities of micro-Raman spectroscopy for the examination - i_n situ , at the cellular level - of i nhomogeneous biological material. Thus,

in biological and biomedical work, Raman microprobe analysis can be regarded as an important extension of the well established techniques of fluorescence microscopy and microspectrofluorometry which are commonly employed in the study of intact living tissues [84,85]. Conclusions

In describing the application of the Raman microprobe to several areas of particle microanalysis, we have given an overview of the kinds of problems that are amenable to investigation by micro-Raman spectroscopy. The results obtained indicate both the unique capabilities of the technique as well as its inherent limitations as an analytical tool. We perceive as one of the strengths of the technique the fact that it is emerging as a valuable complement to the more traditional microprobe methods of elemental analysis.

At this point in the development of Raman microprobe analysis, entirely new information

can be obtained from particles or microscopic sampling regions approaching one micrometer

in dimensions. Molecular microprobing in the submicrometer domain is not routinely feasible

with instrumentation now in use.

192
Various factors determine the outcome of a Raman microprobe measurement and the amount

f useful analytical information obtained from the sample. The important variables appear

o be the molecular nature of the species itself, its concentration and distribution in the

ample and the chemical and physical complexity of the matrix in which the scattering

olecules reside. From current understanding of these factors, no firm conclusions can be rawn regarding the ultimate limits of detection imposed by either sample size and morphoogy, sample heating and fluorescence, the identity of the scattering molecules, concentraion effects, and the compositional complexity of the sample. These questions have been ddressed only partially and their further elucidation must await future studies.

In many programs of materials characterization, the use of Raman microprobe techniques

an be expected to yield new and analytically useful information. With the steadily

:xpanding range of demonstrated applications and advances in experimentation and theory,

.he future of Raman microprobe analysis looks promising indeed.

We are grateful to acknowledge partial financial support of this work by several

igencies of the U. S. Government outside of NBS. These are: Air Force Technical Applica-

.ions Center, AFTAC (microprobe development and applications); Environmental Protection

Agency, EPA (stationary source emissions and trace organic analysis); National Institute of

Cental Research, NIDR (biological tissue mineralization); and National Science Foundation,

JSF (South Pole aerosol studies). Finally, we thank Kurt F. J. Heinrich of the Microanalysis Group at NBS for his guidance and numerous helpful discussions in the course of

-his research. References

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[2] Hendra, P. J., Laser Raman Spectroscopy, in Vibrational Spectra and Structure , Vol. 2, Durig, J. R. (ed.), Marcel Dekker, Inc., New York, Chap. 2, 135-383 (1975).

[3] Irish, D. E. , and Chen, H. , The Application of Raman Spectroscopy to Chemical Analysis,

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[4] Delhaye, M. , and Dhamel i ncourt , P., Raman Microprobe and Microscope with Laser Excitation, J. Raman Spectrosc . 3, 33-43 (1975).

[5] Rosasco, G. J., Etz, E. S. , and Cassatt, W. A., The Analysis of Discrete Fine Particles

by Raman Spectroscopy, Appl . Spectrosc . 29, 396-404 (1975).

[6] Rosasco, G. J., and Etz, E. S. , The Raman Microprobe, A New Analytical Tool, Res. &

Devel . 28, 20-35 (June 1977).

[7] Dhamel incourt, P., Wallart, F. , Leclercq, M. , N'Guyen, A. T. , and Landon, D. 0., Laser

Raman Molecular Microprobe (MOLE), Anal . Chem. 5J, 414A-421A (1979).

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197

ational Bureau of Standards Special Publication 533. This Publication Originated from a pecial Session on Particle Analysis, 13th Annual Conference of the Microbeam Analysis

ociety, Ann Arbor, MI, June 22, 1978. (Issued April 1980)

LASER MICR0PR0BE MASS ANALYSIS (LAMMA) IN PARTICLE ANALYSIS

R. Kaufmann Physiologisches Institut, Lehrstuhl fur Klinische Physiologie Universitat Dusseldorf, Moorenstr. 5, 4000 Dusseldorf

and

P. Wieser

Institut fur Physik, Universitat Hohenheim, Garbenstr. 30 7000 Stuttgart 70 Federal Republic of Germany Abstract

A laser microprobe mass analyzer (LAMMA) has recently been intro- duced as an instrument for microprobe analysis of atomic or molecular

constituents in organic or inorganic matter. The present contribution

gives a short technical description of the LAMMA principle, discusses its performances and limitations with respect to particle analysis (as far as the preliminary results allow) and demonstrates examples of recent

studies performed with the LAMMA instrument in various types of particles. Introduction

For the chemical analysis of microparticulate material, basically all conventional

ethods are applicable as long as one is interested in the average composition of these

aterials only. If it comes to the question of differences between single particles, more

ophisticated approaches are required. Recently the various techniques of microprobe

nalysis became more and more important in studying the chemistry of single particles,

hey have already attributed a great deal to our understanding of the mechanisms underlying

he forming, aging, and removal of aerosols, or to the significance of specific sorts of articles in pathology or ecological systems. However, the microprobe techniques available are still far from satisfying the various

nalytical request of scientists working in aerosol research or other related fields. The

ideal instrument should have the following features: (1) Besides an appropriate spatial esolution, an instrument applied in particle analysis should give as much analytical

reformation as possible about the atomic as well as about the molecular constituents

including isotope discrimination) of a particle; (2) sensitivity should be high enough to etect trace contaminants possibly down to the sub ppmw range; (3) analysis should be uantitative or at least semiquantitative; (4) the measuring procedure and data processing

hould be fast enough to accumulate the analytical data of larger particle populations in a easonable period of time; and (5), last but not least, viewing should provide for as much

s possible information on the morphology of the particles under investigation.

Clearly, such an instrument does not yet exist. Instead, a variety of techniques are

vailable, each of them complying with only one or the other of the above requirements,

e will subsequently discuss a new technique which we call laser microprobe mass analysis

LAMMA). This technique has recently become available and, according to preliminary

tudies, gives promise of fulfilling part of the above requirements where other techniques

annot compete.

199
The LAMMA Instrument, Technical Description

A detailed technical description of the instrument has been given elsewhere [T.2,3] 1

. The LAMMA principle is based on 1 aser- i nduced - mass spectrometry (LIMS). The beam of a pulsed laser (t~10 ns) is focused through a high power optical microscope onto the target

to be analyzed (figure 1), For most applications, the light of a neodymium yttriumaluminum garnet laser in the near or far UV (frequency tripled = 353 nm, or quadrupled =

265 nm) have proven to be optimal. The same microscope is used for viewing the specimen

which is preferably a thin section (M3.3 urn) or small particles supported by a very thin

(-^500 %) supporting film. No special treatment of the specimen (coating) is necessary.

Spatial resolution (both optical and analytical) is limited by diffraction to about

0.5 urn though much smaller particles can be spotted and analyzed. The specimen is mounted

in a vacuum chamber right underneath a thin quartz-window next to the focusing objective.

A time of flight (TOF) mass spectrometer is used for the analysis of ions formed in the evaporated sample volume (typically 10 12 - 10 14 cm3

). Ions are accelerated to an energy

of 3-5 keV and focused down to a field-free drift tube onto a detector (open secondary

electron multiplier). Ions of different m/e ratio are distinguished according to their different flight time which varies with y/W for singly charged ions. As the ions are generated in a very short burst within a volume small enough to constitute essentially a point source, an overall transmission of the spectrometer of 10 - 50 percent is achieved.

In the instrument so far used for particle analysis, targets are limited to a maximum

diameter of some 10 urn, because optical and ion systems are arranged on opposite sides of the target. Larger particles can be analyzed in grazing incidence with some loss in quantitation.

The mass resolution of the TOF mass spectrometer is limited by the width of the initial energy distribution of the ions, leading to a corresponding spread in flight times. This dispersion is partially compensated for by an ion reflector at the end of the drift tube. The achieved mass resolution is m/Am ~ 800. Thus, with every laser shot, complete mass

figures in brackets indicate the literature references at the end of this paper. 200
bectra are available in which mass signals differing by one mass number are discriminated

) to mass number 1000 (see also figure 2). The electron multiplier output signal is mplified, digitized with sampling intervals of 10 ns and stored for slow readout or further

ita processing by an on-line computer. r ® Ions

i.i JJ)

© Ions

o

,..i.L igure 2. Typical LAMMA spectra of positive and negative ions obtained from an epoxy resin standard specimen (0.3 urn section of Spurr's low viscosity medium) containing

known concentration (10 mM) of metal-organic complexes of Li, Na, Sr, and Pb. Inset demonstrates mass resolution at the example of the Pb-isotopes. Detection limits for a number of elements of special interest are listed in Table 1. ne values demonstrate that one of the features of the LAMMA instrument, is the combination

f very high relative as well as absolute sensitivity. Several hundred to thousand atoms

f interest in the sampled volume will usually suffice for detection. Detection of trace

lements in organic matrices may be a problem if their signals are obscured by that of ragment ions of nominally equal mass (for matrices of known composition background

jbtraction can at least partially remedy this limitation).

i i At the present state of development, quantitation of the results poses considerable

fc ifficulties (particularly if absolute quantitation is required). Nevertheless, analysis

-f standard epoxy specimen containing known concentration of a variety of elements demon- strated that a fairly linear signal intensity-concentration plot can be obtained over a

3 ,ange of about three orders of magnitude (see also Kaufmann et al., 1979 [4]). Relative

:', -uantitation should therefore be no problem provided that the instrument parameters are

Jjpt changed between measurements and comparable targets are analyzed. For absolute quan- titation one must refer to a standard specimen of at least similar general composition,

. tructure, and geometry. H.J In contrast to most of the commonly used ionization methods in mass spectrometry, laser- induced ionization yields positive and negative ion signals of about equal intensities. In

he LAMMA- instrument spectra of both, ion species can be recorded for successive shots with

hanges in polarity of only a few voltages. The intensity of positive ions (e.g., alkaline

a

| ons) depends primarily on their ionization potential, that of negative ions (e.g., CI ) on

.'.

; heir electron affinity. The influence of the target matrix on the signal intensity of tomic ions appears to be small, at least when compared to other methods such as secondary

on mass spectrometry (see Burns-Bel 1 horn , 1978 [5]). Molecules, particularly large organic

nes, will generally give typical fragment ions, though parent-molecule and cluster-ion

ignals have been recorded for quite a number of non-volatile molecules up to molecular

eight of several hundred (see Kupka et al . , 1979 [6]). The intensity of signals from large

olecules or their fragments depends strongly on the molecular structure and the chemical

eactions taking place during the evaporation process. Identification of molecules through

201
Table 1. Detection limits of the LAMMA instrument (December 1978). Absolute Relative

(g) (ppmw)

Li 2 X

10" 20 Na 2 x 10 20 Mg 4 x 10 20

Al 2 X 10 20

K 1 X

10" 20 Ca 1 X

10" 19 Cu 2 10" 18

Rb 5 X 10 20 Cs 3 X 10 20 Sr 5 X 1

20

Aq 1 10 1 9 Ba 5 X 10 Pb 1 X

10" 1 9 U 2 10 19

(10 17

)

(10 19

)

0.2 0.2

0.4

0.2

0.1 1.0 20.0 (200) 0.5

0.3 0.5 (5.0)

1.0 0.5

0.3

2.0

NOTE: Data refer to an analyzed volume of ^3 x 10 13

g of (organic matrix) material and to the condition that polyatomic fragments of the matrix do not interfere with the atomic mass signals to be measured. Data in parentheses refer to a standard

reference specimen prepared by Spurr's low viscosity medium. Here organic "background" peaks interfere with the Cu- and Sr-signal. fingerprinting methods is nevertheless possible as the fragmentation patterns and relative

signal intensities are quite reproducible for a given molecule and instrument setting. The complementary information contained in the spectra of positive and negative ions is helpful

in this respect.

Ion yield, initial energy distribution of the ions and fragmentation of larger molecules depend critically on the laser parameters, particularly on the irradiance in the

focus. The irradiances of 108 - 10 11 Wcm~ 2 used in the LAMMA instrument are well in the range where classical target absorption at the laser wavelength is not a necessary

prerequisite for the energy transfer leading to evaporation and partial ionization of the target volume. Depending on the target geometry and general type of target material

(i.e., transparent dielectric, metal, etc.) an optimal irradiance can always be found with

a few test shots. Though the details of the interaction process are not yet fully understood, experience has shown that irradiances close to the threshold of ion formation will preferentially desorb ions from the target surface facing the spectrometer. Irradiances a factor of 3-10 above threshold will lead to an evaporation of the full target volume and yield information on the bulk composition. For small particles, reproducible surface desorption may be quite difficult, and the latter mode of operation is the preferred one in most cases.

202
Performance and Limitation of the LAMMA Technique as Applied to Particulate Materials

With respect to the special requirements for particle analysis, laser microprobe mass

analysis offers a number of advantages if compared with alternative techniques: - As far as atomic composition is concerned, all elements of the periodic table can be detected, many of them at sensitivities in the ppmw or even sub-ppmw range (see Table 1). This usually allows a high sensitivity for the detection of many trace contaminants in single particles. - Since the LAMMA technique separates isotopes, isotopic ratio studies can be performed.

For instance, stable isotopes may be used in isotope dilution studies of kinetic processes in aerosol systems, or changes in natural isotopic abundances during the history of particle formation may be detected. - For the chemical characterization of aerosol particles with the aim to establish their

origin, history, and ecological significance, element analysis is usually not suf- ficient. In this regard one needs as much information as possible about the molecular

constituents (both organic and inorganic). Surely, an ideal case would be the pos- sibility to detect, e.g. , the presence of carcinogenic or toxic compounds. Since one of the unique features of LAMMA is that one obtains not only classical organic finger- print spectra, but, under favorable conditions and appropriate instrument setting, also

very characteristic and simple "desorption" spectra of major organic constituents,

there is some hope that this could provide for a considerable step ahead in the organic microprobe analysis of particulate materials. - If microprobe techniques are applied to single particle analysis, usually the problem

of distribution statistics is raised. If the measuring procedure or the time required

to perform one analysis exclude the possibility to analyze larger populations of individual particles there is always a loss of important statistical information. Therefore, the fact that with the LAMMA instrument the time needed for the analysis is limited only by data processing or writing the recorded mass spectra (at the time usually 30-60 s), a large number of analyses can be executed in a reasonable period of time. - In many studies one wants to know particle morphology (size and shape), the distribution of particles over the support or the exact position of individual particles

chosen for analysis, either as independent information or in correlation with the analytical data. This requires a suitable imaging technique. In the LAMMA instrument

we can obtain such structural information which a light microscope can deliver, including phase contrast, polarization contrast, and dark field illumination and, most importantly, all techniques of optical pattern analysis can be easily fitted to the optical part of the LAMMA instrument (see e.g., McCrone and Del ly , 1973 [7]; Morton

and McCarthey, 1975 [8]). If the structural elements of the particles or the whole

particle itself are below the spatial resolution of the optical microscope, there is still the possibility left to use size dispersive devices for controlled particle

deposition (e.g., Cadle, 1975 [9]; Mercer, 1973 [10]) or, preferably, to make a scanning electron microscope (SEM) picture of the particle(s) to be analyzed prior to the LAMMA analysis. There are also some limitations and disadvantages of the LAMMA technique either based

on physical or instrumental conditions. -LAMMA analysis is essentially destructive. This, for instance, excludes the pos- sibility of recording the spectra of positive and negative ions from the same particle. Furthermore, optimizing the operational conditions of the instrument

(e.g., adjusting the optimal power density) usually requires some test shots with

the unavoidable loss of a corresponding number of particles.

- The fact that (up to ^2 urn particle size) the whole particle is lost at once may some- times turn into a disadvantage, particularly if one aims at surface analysis. With

larger particles, however, it has been found that LAMMA allows for some modest kind

of depth profiling (at least under favorable conditions).

203
-As in most other microprobe techniques, quantitative analysis imposes many problems.

In the absence of a model for the laser-induced plasma formation, an empirical approach

is the only practical way. However, approaches to semiquantitative analysis are pos- sible on the basis that (1) matrix effects on ion yield are much less important in LAMMA than they are in SIMS, (2) intensity-concentration plots for elements are linear over several orders of magnitude at least in standard specimen, and (3) refer- ence to standards is possible whenever appropriate reference materials are available.

- With every laser-induced evaporation of an individual particle, part of the supporting

film is also evaporated (see figure 3). This material, of course, contributes to the recorded LAMMA-spectrum and inevitably creates some kind of a "background." The ratio

of these background signals to mass signals originating from the particle itself depends on the size of the particle, the thickness of the supporting foil, and the chemical nature of both materials. Since formvar, collodium, or carbon foils can be made as thin as some 100 A there is usually no background problem encountered with particles in the range down to about 0.5 urn in size. If particles become smaller or

if trace constituents are to be analyzed, the foil-induced background can be no longer

neglected. However, since the LAMMA spectra of the supporting foil are usually well defined and highly reproducible, methods of background subtraction can be successfully

appl ied.

Figure 3. SEM picture of aerosol particles deposited on a thin (500 A) formvar foil. Note

the hole at the (former) location of a particle. Diameter of the hole is about

twice (2 um) the size of the evaporated particle. - The need to bring the specimen into vacuum will create problems when the analysis of liquid or volatile particles is of interest. However, it should not be too difficult

to design a suitable cold stage for LAMMA analysis of particles partially or fully in the 1 iquid phase.

LAMMA Applications in Particle Analysis

Due to the short period of availability of the LAMMA instrument only a few scattered

applications to particle analysis have been performed so far. Considering the data presented in the subsequent paragraphs it should further be noted that the understanding

of the mechanisms involved in 1 aser- i nduced ionization is as yet limited. Assignments of mass signals to specific molecules or atoms may therefore be preliminary only in some cases (besides many unambiguous identifications).

.'04
Atmospheric Aerosol Particles

In a first survey and feasability study Wieser et al . , 1979 [11] performed a LAMMA analysis of airborne particles collected at Hohenheim (on a site 10 km from the city of Stuttgart, FRG), near the ground. For deposition of the particles on a f ormvar-coated

specimen grid (3 mm in diameter) a special impactor (Zebel and Hochrainer, 1972 [12]) was

used by which particles deposited on a single support were separated according to size

(figure 4).

For the sake of reference and Tor a nrst experience with the method, particles of

known chemical composition such as (NH 4 ) 2 S0 4 , KMn0 4 , ammonium tartrate, kaolinite

{Al 2 (0H) 4 (Si 2 0 5 )} and talcum {Mg3 (0H) 2 (Si 4 0 lo )} were analyzed. As demonstrated by figures 5a,b,c and figures 6a, b, the LAMMA spectra obtained from these reference particles

are rather simple and consist of a few strong mass signals only. It is obvious that here

an immediate and unambiguous characterization of the particles' chemical nature is possible

based on the complementary information contained in the spectra of positive and negative

ions, respectively. This is particularly true for the spectra of (NH) 2 S04 and NH 4 C 4 H 4 0 6 particles. Although in the former the appearance of the 96 S0 4 ion is a little bit unusual according to the rules of classical ionization mechanisms, its assignment in laser induced

mass spectra is not questionable (as cross checked by LAMMA analysis of Na 2 S0 4 particles

equally featuring a leading peak at mass number 96 which can truly be attributed to S0 4 because in the latter case the alternative NH2 S0 3 fragment, possibly involved in the

(NH 4 ) 2 S04 particles, is excluded).

Figure 4. Aerosol particles deposited on a thin formvar foil by a size dis- persive impactor (Zebel and Hochrainer, 1972 [12]).

205
(NH4 ) 2 S04

NH4 C4 H406

KMn04

Figure 5. LAMMA spectra of positive and negative ions as recorded from various reference particles (2 pm size) of (NH4 ) 2 S04 , NH4 C 4 H 4 0 and KMn04

. Laser irradiance three

times above threshold for detectable ion formation.

206
</? 'E3

22 60

20

, , , , 1 , , , , 1

{AI

2COH)4

CSi 205

)}

1

, , , i , , , , i , , , , i , , , , i , , , , i , , , , i — i —

'E32

60

20

1 e

1 1 1

1

i

Ji i

I I I I I I I i 'J, m/e

I,,! i. 1 1. ...

1

'

1

1

1

1 1' 1' 1

:

. 1 1

1 .

1 M

i i m g m/e

Figure 6a. Average mass spectrum of positive ions (upper panel) and negative ions Cower

panel) obtained frDom kaolinite particles (Al 2 (0H) 4 {Si 2 03} ) (size 1 urn) deposited on a 500 A formvar foil. Computer evaluation and peak assignments,

see Table 3.

207
{Mg3COH)2 CS l4010 )|

i |i m i |ii ii| h ii|hH

* 2 m/e 0

b o

l| HH|MMl»

m/e

Figure 6b. Average mass spectrum of positive ions (upper panel) and negative ions (lower panel) obtained from talcum (Mg 3 (0H) 2 (Si 4 0 10 ] ) powder particles (size 4-5 urn) deposited on a 500 A formvar foil. Computer evaluation and peak assignments,

see Table 4.

208
The LAMMA spectra of silicate (reference) particles (see figures 6a, b) are more

omplex, although fairly reproducible fingerprint spectra have been obtained in both

Al 2 (0H) 4 {Si 2 0 5 ) ) and (Mg3 (OH)2{Si40 10 } ) particles. Nevertheless, most of the prominent

eaks can be unequivocally assigned in the spectra of the positive as well as of the

legative ions. The signal intensity of the Si ion is rather low (at least at the laser

rradiance of 3 x threshold chosen). At higher irradiances (10-15 times threshold) the

ield of positive 28 Si idecular ions. ions increases in relation to the negative silicon containing

It is interesting to compare the (NH 4 ) 2 S0 4 LAMMA spectra with those obtained by SIMS

rom equal reference particles investigated in a recent Cambridge Instrument study (1978) 2

Lif upper-atmospheric fly-ash particles. Similar to the LAMMA spectrum, a prominent 18 NH4 •ignal was recorded in the SIMS spectrum of positive ions (together with strong 1 H and

7 NH3 signals not seen in the LAMMA spectrum). Since negative secondary ions are not asily available in SIMS, the information related to the 96 S0 l+ group is contained only in

i number of very small signals assignable to a large variety of positively charged

lolecules consisting of S in any possible combination with H, N, and 0. The above LAMMA spectra of reference particles have been taken at laser irradiances

<iear threshold (for evaporating material). Figure 7 compares the spectrum of one type of

.hese particles {(NH 4 ) 2 S0 4 } taken at an irradiance of about 10 times threshold intensity

with that recorded at low irradiance (3 times threshold). This spectrum is completely

lifferent, more complicated and much less suited for a straightforward chemical identifica-

.ion. However, although here the primary information obtained in the low irradiance spectra

s lost, one gains the advantage that, in the analysis of particles with unknown chemical imposition, atomic trace contaminants (for instance heavy metals) would show up under these

:onditions at optimal detection limits (ppmw to sub-ppmw in favourable cases, such as Pb

>r U).

© ©

. L..JL_ © ©

J

igure 7. Positive mass spectra of (NH 4 ) 2 S0 4 reference particles recorded at low laser irradiance (3 times threshold, lower panel) and at high irradiance (10 times threshold, upper panel). See text for further information.

'-SIMS Studies and Structural Identification of Compounds in Upper Atmosphere Fly Ash, 1-17 ASRS, Cambridge Instrument.

209
Subsequently, Weiser et al., 1979 [11], analyzed a randomly chosen population of 100 single aerosol particles between 0.5 pm and 1 pm (large particles) and 1 pm - 10 pm (giant j particles) in size.

In figures 8 and 9 a collection of LAMMA spectra are shown demonstrating typical records of either positive or negative ions in both large and giant particles. Tables 2a and 2b list the relative frequency at which signals of the most frequent mass numbers appear in the spectra of the investigated aggregate of 100 analyzed particles. In this evaluation all signals of an intensity of about 10 percent full scale were counted. Possible molecular assignments were given for most of the mass numbers but, as mentioned

before, are still the object of some uncertainty.

1

_j ilL? 1 1

fi

,

u7 _ T ® * ®

1 ... i ® %

f* 1 , ! ! oi

9

1 LJ I Ji, Figure ! LAMMA spectra of (large) aerosol particles (size 0.5-1 pm). Positive ions spectra in the upper part; negative ions spectra in the lower part. See text

for further information.

210
igure 9. LAMMA spectra of (giant) aerosol particles (size 1-10 pm). Positive ions spectra in the upper part, negative ions spectra in the lower part. See text

for further information.

211
Table 2a. Relative frequency of appearance (above 10% full scale) of mass signals in the spectra of positive ions recorded in 100 aerosol particles.

Ions which may Frequency

(percent) represent the measured m/e-values

18 71 NH4 +

, H 2 0 +

23 84 Na

+ 24 19 Mg

+ 25 19 My

+

26 19 Mg

+ 27 52 A 1 + 28 29

„ .+ „ ,, + +

Si , C 2 H 4 , CO

29 29 C2H5 , 30 39 + + +

C2H 6 , CN CH2 0

31 26 P , CH 2 0H

39 100 K+ 40 26 Ca

+

41 100 K

+ 43 45 A10

+ 44 19 A10H

+

, C02 , Ca

45 13 Si0H

+

51 10 55 35 Mn

+ 56 42 Fe

+

, Ca0

+

57 35 Ca0H

+

, Mg0 2 +

Ions which may

m/e Frequency represent the (percent) measured m/e-values

60 10

61 10 62 13 63 13 Cu

+ 65 1 3 Cu

+ 69 10

72 1 3 Fe0

+

73 29 FeOH 74

85

10

13

91 10 97 10 112 10 128 10 140 10 152 10 155 10 206 29 Pb

+ 207 29 Pb

+ 208 29 Pb

+

212
Table 2b. Relative frequency of appearance (10% full scale) of mass signals in the spectra of negative ions recorded in 100 aerosol particles.

Ions which may Ions which may

n/e Frequency represent the m/e Frequency represent the (percent) measured m/e-values (percent) measured m/e-values

1 16 h" 63 32 HN0 3 +

12 3 c" 64 58 S0 2

"

13 3 ch" 70 10

16 32 0", NH 2

~ 71 16

17 52 oh" 72 61 c6

"

19 3 F~ 73 45 c 6 h" 24 68 C 2 " 74 19 C 6 H2 25 68 c 2 h" 75 13 CeH3 26 81 C 2 H 2 ", CN" 76 26 Si0 3

"

27 32 C 2 H 3 77 10 HSi0 3

'

32 19 s" 78 10

35 61 Cl~ 79 16 P0 3

"

36 48 ci 3

" 80 81 S0 3

"

37 61 CL~, C 3 H~ 81 61 HS0 3

"

40 65 CN2

" 83 23

41 71 C 2 H0~ 87 10

42 71 C 2 H 2 0

_ 88 16 43 71 C 2 H 3 0" 96 87 S0 4

"

45 71 107 13 46 87 N0 2

~ 110 26

48 71 c 4 ", so" 111 26

49 55 119 13

50 55 120 19

51 10 146 10

59 35 CH 3 C00" 147 10 60 65 Cs~, C0 3 ", Si0 2

" 164 10

61 48 C 5 H", HC0 3 " 208 16

62 81 C 5 H 2 ", N0 3 " 224 16 PbO" 213
Table 3. Computer evaluation of average spectrum shown in figure 6a. Assignment Area of Peak Standard Deviation Standard Deviation

(percent) (percent)

Positive Ions

Mass 28 Si 710 0 124 24 17.9

Mass 29 Si 53 3 17 95 33.7

Mass 39 238 7 29 54 12.3

Mass 41 2 5 ^ 40 29. 2 Mass 43 A i 0 61 3 18 30 29.8

Mass 44 55 3 32 49 58.7

Mass 56 88 0 22 03 25.0

Mass 70 64 7 9 40 14. 5 Mass 73 54 7 2 1 78 39. 8 Negative Ions Mass 24 c 2 (f)

a

5 72 0 128 98 22.5

Mass 25 C 2 H (f) 701 6 158 54 22.6

Mass 26 C 2 H 2 (f) 822 0 292 01 35.5 Mass 28 91 2 21 52 23.6

Mass 32 S 61 6 21 17 34.4

Mass 35 CI 165 2 65 86 39.9

Mass 36 c 3 (f) 138 8 55 07 39.7 Mass 37 CI, C 3 H (f) 137 2 43 00 31.3 Mass 40 163 2 53 02 32.5

Mass 41 C 2 H0 (f) 284 8 58 71 20.6

Mass 42 428 0 206 06 48.1 Mass 43 A10 1773 2 238 53 13.5 Mass 45 152 4 22 93 15.0 Mass 48 (f) 186 8 47 26 25.3

Mass 49 (f) 148 6 40.25 27. 1 Mass 51 92 6 11 44 12.4 Mass 59 A102 1099.2 167 86 15.3

Mass 60 Si02 1086 0 189 95 17.5 Mass 61 245 4 53 44 21.8

Mass 62 75 6 8 90 11.8

Mass 63 55 6 9 50 17.

Mass 67 48 4 9 07 18.7

Mass 73 48 8 6 81 14.0

Mass 75 A10 3 101 8 17 56 17.3

Mass 76 Si0 3 224 8 27 85 12.4 Mass 77 HSi0 3 188 4 44 79 23.8

Mass 87 61 6 15 07 24.5

Mass 9 7 60 4 31 19 51.6

Mass 102 47 6 12 36 26.0

Mass 103 SiA103 125 6 33 10 26.4

Mass 119 SiA10 4 137 6 33 44 24.3

a (f) = foil.

21
Table 4. Computer evaluation of average spectrum shown in figure 6b. Assignment Area of Peak Standard Deviation Standard Deviation

(percent) (percent)

Positive Ions

Mass 23 Na 40 5 19 87 49. 1 Mass 24 Mg 4074 7 194 82 4.8

Mass 25 Mg 1670 0 168 81 10. 1 Mass 26 Mg 1759 0 278 84 15.9

Mass 27 Al 212 0 93 60 44.2

Mass 28 Si 2697 5 704 1 5 26.

Mass 29 Si 553 5 1 28 00 23.

Mass 30 Si 440 0 116 88 26.6

Mass 54 45 0 13 67 30.4

Mass 56 Mg0 2 551 0 149 55 27.1

Negative Ions

Mass 24 c 2 (f)

a 628 0 201 6/ 32. 1 Mass 25 C 2 H (f) 680 ?40 29 35. 3 Mass 26 CoHo (f) 342 4 162 91 47. 6 Mass 28 1 39 2 62 94 45. 2 Mass 32 88 0 50 1 / 57.0

Mass 36 C 3 (f) 118 0 55 97 47.4

Mass 37 C 3 H (f) 106 8 32 94 30.8

Mass 40 1 74 8 84 35 48. 3 Mass 41 C 2 H0 (f) 294 8 86 37 29. 3 Mass 43 71 2 24 18 34.0

Mass 45 106 8 29 58 27. 7 Mass 48 (f

)

1 07 2 50 85 47. 4 Mass 49 (f) 85 2 50 36 59. 1 Mass 52 48 0 23 63 49. 2 Mass 59 151 2 33 53 22.2

Mass 60 Si0 2 1838 4 454 85 24. 7 Mass 61 HSi0 2 417 2 79 56 19.

Mass 62 1 29 5 49 1 7 37. 9 Mass 73 60 0 16 26 27.

Mass 75 152 4 41 77 27.4

Mass 76 1 797 5 452 36 25.4

Mass 77 Si 0 3 H 573 2 110 04 19.2

Mass 79 60 0 15 85 26.4

Mass 84 44 0 12 71 28.9

Mass 100 SiMg0 3 359 2 83 77 23.3

Mass 101 112 8 28 14 24.9

Mass 102 80 0 21 80 27.2

Mass 116 SiMg0 4 262 8 90 39 34.4

Mass 117 SiMg0 3 H 214 8 64 20 29.9

Mass 118 77 6 27 17 35.0

Mass 119 58 4 30 72 52.6

Mass 121 48 4 19 73 40.8

3 (f) = foil.

215
~:"he LAMMA spectra of large and giant particles are basically similar. However, in large particles there is a higher incidence of metallic constituents such as Na, Mg, Al

,

Ca, Ni , Cu, Zn, and Cd, and a deficiency of NO and N0 3 , whereas in giant particles the incidence of S04 , HS0 4 , NH4 , and Pb was smaller if compared with large particles. Among a particle population of common size and appearance a few particles can always

be found, the compositions of which considerably differ from that of the majority of the population. Examples for such kind of "strange" particles are given in figure 10. The LAMMA spectrum shown in part (a) of figure 10 reveals a particle of obviously industrial origin with the large signals of Zn and Fe not observed in other spectra of the investigated

population. In view of the high ionization potential of Zn, the appearance of an intensive

Zn signal suggests a much higher Zn content than one would suspect from the signal "intensity ratios to Na, Al , K, and Fe which are also present in this particular spectrum. A completely different composition and origin must be attributed to the particle from which

the LAMMA spectrum of figure 10b was recorded. The few (saturated) signals of positive

ions (Na, Al , K, Ca, and trace amounts of Mg) suggest it's originating from the soil. Finally, in the spectrum of negative ions shown in figure 10c, a typical "fly-ash" particle

is fingerprinted with its characteristic pattern of carbon molecules up to V 10 . It is further interesting to note that in this particular spectrum an unequivocal 19

F signal appears which (if related to results obtained in standard reference specimen of known fluorine content) would indicate the presence of about 10-50 ppmw of fluorine in the analyzed particle.

Figure 10. Three LAMMA spectra showing unusual chemical particle composition in a population of 100 analyzed aerosol particles. See text for further explanation.
In about 30 percent of the analyzed particles lead was detected (see also Table 2a). There was no obvious association of lead with other constituents. This finding indicates

the occurrence of secondary agglomeration between the original (small) lead particles formed

by nucleation of car exhaust products and other atmospheric particles.

In several occasions the LAMMA spectra of giant particles obtained with the first,

second, or third laser shot (applied to the same area of the particle and removing only

part of the material present) differ considerably (figure 11). This seems to evidence

chemical i nhomogenei ties within the investigated particle. It also indicates that, under favourable conditions, some kind of a depth profiling may be possible as it has already

been shown in LAMMA studies of thin film sandwiches (Kaufmann et al . , (1979) [4]).

Figure 11. LAMMA spectra of positive ions obtained from a giant aerosol particle (size

8 urn). Laser irradiance at about three times threshold for ion formation. First shot removes only superficial layer of material, second shot vaporizes

material of a deeper layer; particle lost after the third shot. Note the difference in mass spectra recorded with the first (upper panel) and second

(lower panel) laser shot.

Coal Mine Dust Particles in Human Lymphocytes

Coal worker pneumoconiosis (CWP) has recently attracted new attention from pathologists due to the increasing demand for coal as an alternative energy source in the future

(for review see Abraham, 1978 [13]). Coal mine dust particles are certainly a mixed

population of mineral and organic particles. There is still a great deal of uncertainty

as to the correlation of the pathologic findings to the chemical nature of the particles

inducing the various morphological, functional, and, possibly, immunological reactions.

In an analytical study of DeNee, Abraham, and Geldermann (1975) [14], the typical nodular

lesions observed in lung tissues of patients with CWP were attributed to silica or silicates. 217
In a recent LAMMA study, a specimen of cultivated human lymphocytes (courtesy of

Prof. Bruch, Institute for Hygiene and Occupational Medicine, Gesamthochschule Essen) was

investigated, which for eight hours had been incubated i_n vitro with coal mine dust particles

(0.5 - 1 urn). Many of these particles had been taken up by phagocytosis and could be clearly identified i ntracel 1 ul arly at different sites in the cytoplasm. The aim of the preliminary study was to find out whether LAMMA could distinguish and, eventually, classify

the particles according to their chemical composition and, if so, whether or not lymphocytes would show preferential phagocytosis for particles of a specific composition.

The control analysis of 100 extracellular particles first revealed that roughly about

70 percent of the particles were mineral in nature (figure 12), whereas about 30 percent

consisted of pit coal (typical fragmentation pattern of polycarbonhydrates shown in figure

13); only a minor fraction of about 1.2 percent gave "mixed" mass spectra. The population

of the mineral particles could be further subdivided by a (somewhat arbitrary) subclas- sification in which particles were distinguished by the leading elements detected, which

were either Al , (Si), K, and Mn (class (a) in figure 12), or Na, Al , (Si), K, Mn, and Fe (class (b) in figure 13) or, finally, Na, (Si), K, and Mn with no Fe present (class (c) in figure 13). With respect to silicon, which is supposed to be one of the major constituents

of mineral coal mine dust particles, one must emphasize that signals related to silicon may either show up as 28 Si , 4

( S i 0 ), 6O (Si0 2 ) , 76 (Si0 3 ) , or in many other combinations with

Al or Mg (see also figures 6a and 6b). Since under the usual operating conditions of the LAMMA instrument (at laser irradiance about 3-5 times above threshold), the ionization

potential for Si is too high for a reasonable ion yield detection, detection limits in the positive ion spectrum are expected to be poor. The situation is further complicated by the fact that in the spectrum of positive ions 44 (Si0) may be obscured by 44 Ca, 44 (Co 2 ), and 44 (A10H) respectively.

jlai LjJj

li, ,1.

ijjJjjjjJljL

30 40 50 60 70 140 160 180 200 Figure 12. LAMMA spectra of positive ions obtained from (mineral) coal mine dust particles (size 1-2 urn), which had been administered to cultivated human

lymphocytes.

218
JLi k±JJ . ii I L

l ,

1 L !. fj I JLLulJLL^

lUjJlL

50 60 70 80 90 100 160 180 200

r igure 13. LAMMA spectra of positive ions obtained from organic (pit coal) coal mine dust particles (size 1-2 urn) which had been administered to cultivated human lymphocytes. Note reproducibility of fragmentation pattern.

As to the second question of preferential phagocytosis, it was demonstrated that pitcoal particles were found inside the lymphocytes twice as often as in the extracellular

particle population. This might be an interesting result with respect to the suggestion

that immunity mechanisms may be induced by some organic compounds of coal mine dust

particles (see Caplan, 1953 [14]; Parkes, 1974 [15]). Impurity Analysis in Particulate Residues of Solvents Monodispersive particles of well defined particle size and homogeneous particle

composition can be produced for the calibration of instruments such as optical counters,

impactors, or for other aerosol related studies. For this purpose particle generators as described by Berglund and Liu (1973) [17] are used. In such a device, a solution of a non-volatile solute of known concentration in a volatile solvent is sprayed through a vibrating orifice, generating droplets of controllable size with only a small spread of volume. The particles obtained after evaporation of the solvent represent the residue of

the non-volatile solute and, of course, are particles of uniform size, shape, and composition. However, if the solvent used already contains unknown amounts of dissolved

impurities or undissolved particles, their influence on the properties of the generated

particles becomes the more important the smaller their size. An attempt was undertaken to identify the nature of such impurities in a sample of analytical grade (p. a.) isopropanol.

In addition, the possibility was to be checked whether LAMMA might be used for a direct

trace contaminant analysis in liquid samples, including drinking water. Figure 14 shows an average spectrum (n = 9) of a LAMMA analysis performed in particulate residues (~1 urn size) of analytical grade isopropanol. Leading trace contaminants in this case were Na, K, and Ca. By reference to the droplet-to-residue volume ratio (= 10 5

) the total mass fraction of the residue can be estimated roughly to about 15 ppmw. Taking

219
f-!-H+ft-ht+

III., , I l.ll Jl.,1.1 . ,, , ,1 ,, , I H+l |

1 I I I |-H-++-}-HH+|-|-ff-h[--t-l II |I I 1 I { I I I I

| I l++fhH+| £ m £ I m/e

Figure 14. Average mass spectrum (positive ions) of residue particles from sprayed isopropanol (analytical grade); particles (size 1 urn) deposited on 500 A formvar

foil; n = 9. For computer evaluation and peak assignments see Table 5.

into account the specific LAMMA sensitivity factors (as they are determined at least for most of the alkaline and earth alkaline metals), a quantitative approximation of the impurity content of the investigated solvent is possible. A few of the particles in the above residue specimen of isopropanol had a completely different composition. They obviously had been already present as dust particles in the liquid sample and consisted

mainly of either a Cu-Sn alloy or showed larger signals of Na, Ca, Ba, and Pb. In similar

studies of particulate residues of drinking water (see figure 15), trace amounts of Pb could be detected down to a few ppbw with respect to its concentration in the investigated water sample. There was also a remarkable amount of Sr present in this particular

specimen.

; CO CO O) o

llii) uJjJl

Figure 15. LAMMA spectrum of positive ions as recorded from a residue particle (1 pm size) of a drinking water sample.
Table 5. Computer evaluation of average spectrum shown in figure 14. Assignment Area of Peak Standard Deviation Standard Deviation

(percent) (percent)

23 Na 28 Si 2939 K 40 Ca

41 K 4647

62

63

67

7172

818388

89

91

80.65 2. 9 480. 4 1 63. 47 34. 0 49. 1 28. 89 58.

1052.6 50. 74 4. 8 346.6 1 6. 97 4. 9 154.0 1 8. 28 11.9 47.30 9 . 5 8. 22 12.1 28.48 17.8

56. 70 11.5

123 9 19.59 15.8 163.0 1 6. 57 10.2

84. 0 1 1 . 96 14. 2 298.

55. 82 18. 7 134.5 29. 27 21.8

56. 8 9. 36 16.5 70.8 13.13 18.6 230.9 28. 16 12.2

57.

8.91 15.6

28.1 6.21 22.

43. 1 6.33 14.7 169.3 20.84 12.3 107.3 17.52 16.3

Crystalline Organic Particles

An unusual and unique feature of laser-induced microprobe mass analysis is the fact

that by control of the laser irradiance in the focus one obtains a variable at hand by which

the ionization process and the information contained in the mass spectra of crystalline

organic compounds can be easily adjusted to various desirable fragmentation levels. As already mentioned in the analysis of aerosol particles, one can go from "smooth desorption"

resulting in very simple and straightforward mass spectra to "full pyrolysis" inducing

complicated mass spectra of the highly fragmented organic compounds. Again the high yield

of negative ions provides complementary information under all instrumental conditions.

Furthermore, difficulties encountered in conventional mass spectrometers when ionizing

organic solid state materials of low vapor pressure are circumvented to a certain extent by laser-induced ionization. Finally, a few small particles of 1-10 pg each are sufficient

for a full mass spectrometric analysis. Figure 16 demonstrates the example of a fluorinated

heterocycl ic compound (4-(2 ' -tri f 1 uoromethyl )-2 ,6-di methyl -1 ,4-dihydropyridine-3,5-dicarboxylate) consisting of a pyridine-ri ng (ring II) and an aromatic (benzene) ring (ring I) bearing a CF 3 group. "Smooth laser irradiation" (0.2-1% transmission) results in mass

spectra of a few lines related merely to the two ring systems, whereas with increasing

221
4-(2'-trifluoromethyl)-2,6-

d i methyl -1,4- dihydropyrid ine- 3,5-dicarboxylate

CF3 | 1-I3UJUL LH3

! H3COOC CH, © Ions

Figure 16. LAMMA spectra of positive and negative ions obtained from microcrystal s (1-2 pm)

of a heterocyclic fluorinated compound. The 1, 5, and 50 percent labels indicate percent laser transmission and, hence, are a measure of the laser irradiance in the focus. See text for further explanation.

laser irradiance fragmentation comes up leading to mass spectra similar to those obtained

by electron impact or other conventional ion sources. Again the appearance of some of the larger fragments is rather unexpected according to the rules of classical ionization

methods. For instance, the signal at mass number 225 in the spectra of positive ions (related to the pyridine ring) is not easy to explain except for the occurrence of a radical

The support of this work by the Federal Ministry of Science and Technology is grateful ly acknowledged.

222
References

[1] Hinenkamp, F. , Unsold, R. , Kaufmann, R. , and Nitsche, R. , A High Sensitivity Laser Microprobe Mass Analyzer, Appl. Phys. 8, 341-348 (1975).

![2] Heinen, H. J., Wechsung, R. , Vogt, H. , Hillenkamp, F. , and Kaufmann, R. , Laser-Mi kroson- den-Massen-Analysator LAMMA, Biotechnische Umschau 2, 346-354 (1978).

[3] Wechsung, R. , Hillenkamp, F. , Kaufmann, R. , Nitsche, R. , Unsold, E. , Vogt, H. , LAMMA - A New Laser-Microprobe-Mass-Analyzer, Microscopica Acta, Suppl. 2, 281-296 (1978).

[4] Kaufmann, R. , Hillenkamp, F. , Wechsung, R. , Heinen, H. J., and Schurmann, M. , Laser Microprobe Mass Analysis, Achievements and Aspects, Proc. of Scanning Electron Microscopy, Washington, April 16-22 (1979).

[5] Burns-Bellhorn, M.S., Review of Secondary Ion Mass Spectrometry in Biological Research,

Adv. Techn. in Biomed. Electron Microscopy, Gennaro, J. (ed.), Masson et Cie (1978).

[6] Kupka, K. D. , Hillenkamp, F. , Schiller, Ch. , Ami nosa'ure-Massenspektren , gewonnen mit

einem Laser-Mi kromassenanalysator, Proc. Deutsche Physikl. Ges. Annual Meeting, March

5-9 (1979).

[7] McCrone, W. , and Del ly , J. G. , The Particle Atlas, Ann Arbor Science Publ. Ins. Mich.

(1975).

[8] Morton, R. R. A. , and McCarthey, C. , The Omnicon Pattern Analysis System, The Microscope

23, 239-260 (1975).

[9] Cadle, R. D. , The Measurement of Airborne Particles, John Wiley & Sons, New York, NY

(1975).

10] Mercer, T. T. , Aerosol Technology in Hazard Evaluation, Academic Press, London, New

York (1973).

£ ) ,11] Wieser, R. , Wurster, R. , and Seiler, H. , About the Identification of Airborne Particles

by Laser Induced Mass Spectroscopy, To be Published in Atmospheric Environment.

! 12] Zebel , G. , and Hochrainer, R. , Zur Messung der Grb'Benvertei 1 ung des Feinstaubes mit

einem verbesserten Spektral impaktor , Staub, Reinhaltung, Luft 3, 91-95 (1972).

13] Abraham, J. L. , Recent Advances in Pneumoconiosis - The Pathologist's Role in Etiologic

Diagnosis, IAP Monograph No. 19, The Williams & Wilkins Co., The International Academy

of Pathology (1978).

14] DeNee, P. B. , Abraham, J. L. , and Gelderman, A. H. , Scanning Electron Microscopy, 0m

Johari, and Corvin I (eds.), ITT Research Institute, Chicago, IL, 411-418 (1973).

15] Caplan, A., Thorax, 8, 27-29 (1953).

16] Parkes, W. R. , Occupational Lung Disorders, London, Butterworths (1974).

17] Berglund, R. N. , and Liu, B. Y. A., Generation of Monodisperse Aerosol Standards, Environmental Science & Technology 7, 141-153 (1973).

223

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1. PUBLICATION OR REPORT NO. NBS Spec. Publ . 533

2.Gov't Accession No. 3. Recipient's Accession No.

ITLE AND SUBTITLE Proceedings of the Particle Analysis Session of the

13th Annual Conference of the Microbeam Analysis

Society, held at Ann Arbor, Michigan, June 22, 1978

. Publication Date April 198i

6. Performing Organization Code

8. Performing Organ. Report No. Kurt F. J. Heinrich, Editor

ERFORMING ORGANIZATION NAME AND ADDRESS JATIONAL BUREAU OF STANDARDS

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! SUPPLEMENTARY NOTES Library cf Congress Catalog Card Number: 80-600033

i JJ Document describes a computer program; SF-185, FIPS Software Summary, is attached. ABSTRACT (A 200-word or less tactual summary ol most significant information. If document incl :ant bibliography o

This document contains a series of invited papers on the subject of Particle Characterization. Part of the material presented here was pre- sented orally at the Thirteenth Annual Conference of the Microbeam Analysis Society, at Ann Arbor, Michigan, on June 22, 1978. The publication

describes microscopic and analytical techniques for the characterization

of single microscopic particles. Applications of these techniques to pro- blems of general interest are also included.

KEY WORDS fsix to twelve entries; alphabetical order; capitalize only the first letter of the first key word unless a proper name;

separated by semicolons) Biological fluids; electron microscopy; electron microprobe; ion probe;

light microscopy; microanalysis; microdroplets; particles; particulate

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