NIST recommended

practice guide

960-19 National Institute of

Standards and Technology

U.S. Department of Commerce

Special

Publication

960-19

Measurement

Issues in Single Wall

Carbon Nanotubes

Stephen Freiman

Stephanie Hooker

Kalman Migler

Sivaram Arepalli
Special Publication 960-19

Measurement

Issues in Single Wall

Carbon Nanotubes

Edited by:

Stephen Freiman

Stephanie Hooker

Kalman Migler

NIST Materials Science and

Engineering Laboratory

and

Sivaram Arepalli

NASA-DSC

March 2008

U.S. Department of Commerce

Carlos M. Gutierrez, Secretary

National Institute of Standards and Technology

Dr. James M. Turner, Acting Director and Deputy Director

NIST Recommended Practice Guide
Certain equipment, instruments or materials are identifi ed in this paper in order 

to adequately specify the experimental details. Such identifi cation does not imply recommendation by the National Institute of Standards and Technology nor 

does it imply the materials are necessarily the best available for the purpose. 

 

Offi cial contribution of the National Institute of Standards and Technology; not 

subject to copyright in the United States.

_______________________________________

National Institute of Standards and Technology

Special Publication 960-19

Natl. Inst. Stand. Technol.

Spec. Publ. 960-19

78 pages (March 2008)

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iii

FORWORD

The NIST Recommended Practice Guide on Measurement Issues in Single Wall 

Carbon Nanotubes represents the output from the 2nd NASA-NIST workshop 

devoted to issues of nanotube purity, dispersion and measurement techniques 

held at NIST in 2005. In attendance were over 80 participants, representing 

private corporations, universities, and government laboratories. The primary 

purpose of the workshop was to bring together technical and business leaders 

in the fi eld of single wall carbon nanotubes (SWNTs) to discuss measurement 

priorities and aid in the development of measurement protocols. This guide 

lays out written protocols to enable product developers to more rapidly assess 

as-received materials, prepare quality nanotube dispersions, and ultimately 

achieve both repeatability and high performance in their resulting value-added 

devices. The technical chapters in this guide were written by leading practitioners in the fi eld and present standard methods currently used for characterization of single wall nanotubes in a straightforward fashion.

1. Introduction

2. Thermogravimetric Analysis by Sivaram Arepalli and Pavel Nikolaev, 

NASA JSC

3. Near-IR Spectroscopy by Robert Haddon and Mikhail Itkis, University 

of California, Riverside

4. Raman Spectroscopy by Anna Swan, Boston University

5. Optical, Electron, and Scanned Probe Microscopy by Cheol Park and 

Peter Lillehei, NASA Langley Research Center, Science and Technology 

Corporation Hampton, VA, and National Institute of Aerospace, VA

A free download of this Recommended Practice Guide and more Information 

on the SP 960 series can be found at: http://www.nist.gov/practiceguides. 

This web site includes a complete list of NIST Practice Guides and ordering 

information.
Table of Contents ♦

v

1. Introduction

2. Thermogravimetric Analysis (TGA)

 2.1. General Description

 2.2. Types of TGA Instruments

 2.3. Operating Principle and Defi nitions

 2.4. Sources of Uncertainty

 2.5. Practical Concerns

 2.5.1. Material Inhomogeneity

 2.5.2. Combustion 

 2.5.3. Heating Rate

 2.5.4. Sample Mass

 2.6. Suggested Protocol

 2.7. Appendix

 2.7.1. Protocol Development

 2.7.2. Material Inhomogeneity

 2.7.3. Heating Rate

 2.7.4. Sample Compaction

3. Near-Infrared (NIR) Spectroscopy

 3.1. Introduction

 3.2. Formulation of Method: Electronic Structure and Optical Spectroscopy 

of SWNTs

 3.3. Practical Procedure

 3.3.1. Choice of Spectrophotometer

 3.3.2. Sample Preparation

 3.3.3. Practical Example of Spectral Measurements and Relative 

Purity Calculations

 3.3.4. Most Common Source of Experimental Uncertainty: Distorted 

Baseline

 3.4. Characterization of NIR method

 3.4.1. Reproducibility of the Purity Evaluation

 3.4.2. Infl uence of Light Scattering

 3.4.3. Infl uence SWNT Concentration on Relative Purity Determination 

 3.5. Examples of the Application of NIR Purity Evaluation Procedure

 3.5.1. Optimization of SWNT Synthesis

 3.5.2. Evaluation of Effi ciency of Purifi cation and Optimization of 

Purifi cation

 3.6. Frequently Asked Questions about the Capabilities and limitations of 

the NIR
4. Raman Spectroscopy

 4.1. Resonant Raman Scattering in Carbon Nanotubes

 4.2. Raman-Active Modes in Carbon Nanotubes (RBM, D, G and G′)

 4.2.1. Radial breathing mode (RBM)

 4.2.2. The G band

 4.2.3. Second Order Raman Scattering, the D and G′ Modes (Zone 

Boundary Phonons)

 4.3. Width of the Resonance

 4.4. Strength of the Raman Signal; Electron–Phonon Coupling

 4.4.1. Depolarization and Selection Rules 

 4.5. Practical Considerations

 4.5.1. Measurement Setup

 4.5.2. Laser Power Heating Effects 

 4.5.3. Material Inhomogeneity 

 4.6. Appendix

 4.6.1. Illustration of Aggregation Effects

 4.6.2. Illustration of Heating Effects

 4.6.3. Measurements from One Individual Nanotube - 

“Nano-Slit Effect”

5. Optical, Electron and Probe Microscopy

 5.1. General Description

 5.2. Introduction

 5.3. Experimental Description

 5.3.1. Instrumentation

 5.3.2. Contrast generation

 5.4. Conclusions

6. Summary

♦ Table of Contents

vi
Introduction ♦

1

1 Introduction

Single-walled carbon nanotubes (SWNTs) are the most promising of all nanomaterials, with unique electronic and mechanical properties which lend themselves to a variety of applications, such as fi eld-emission displays, nanostructured composite materials, nanoscale sensors, and elements of new nanoscale 

logic circuits (1-5). In all cases the quality of the SWNT material is important, 

and for some applications it is paramount. Despite sustained efforts, all currently known SWNT synthetic techniques, generate signifi cant quantities of impurities, such as amorphous and graphitic forms of carbon and carbon encapsulated catalytic metal nanoparticles. The presence of such impurities necessitates 

the application of vigorous purifi cation procedures, which adds to the high cost 

of production and limits the application of these materials. 

Improvements in SWNT quality by optimization of the synthesis, as well as 

subsequent purifi cation steps is a multi-parametric task which requires the accurate and effi cient evaluation of small changes in the purity and yield of bulk 

quantities of the SWNT product as a function of the synthetic parameters and 

purifi cation protocol. Ideally, such a procedure should provide a rapid, convenient, and unambiguous measure of the bulk purity of standard SWNT samples 

with instrumentation that is routinely available in research laboratories. For 

customers and end users of SWNTs such an evaluation procedure is essential 

for the development of quality assurance measures which allow a comparison 

of commercial materials with customer determined specifi cations. 

While the reader may believe that this is a settled issue because many suppliers label their SWNT products with percentage purities, evaluation of such 

samples shows that in many cases the purity is overstated - some to a high 

degree (6). Progress in chemistry and material science has been marked by the 

ability to obtain pure substances: the isolation of the pure elements and the 

refi nements that have occurred in electronics grade silicon are obvious examples. While it may not be possible to obtain analytically pure SWNTs, the 

nanotechnology industry will benefi t greatly from a serious attempt to specify 

the quality of nanotube containing materials, both in the research and commercialization stages. 

In this Practice Guide we present a number of analytical techniques which 

are relevant to the evaluation of the purity of SWNT materials. There are two 

major forms of impurities in current SWNT preparations: the metal catalyst 

residue and the carbonaceous component which usually takes the form of 

amorphous carbon and nanographitic structures. Most of the analytical techniques discussed in this Guide are suited to the detection of only one of those 

fractions, and the choice of an analytical technique is critical(7). In special cas-
♦ Introduction

2

es, such as the comprehensive characterization of the highest purity reference 

materials for standards development, the application of a number of analytical 

techniques is required (8). 

In Chapter 2 we discuss Thermo-Gravimetric Analysis (TGA) which is the 

most effi cient tool for determining the metallic impurities in SWNT material. 

In certain special cases the TGA technique is also capable of providing information on the carbonaceous impurities as a result of differences in combustion 

temperatures. 

The evaluation of the purity of the carbonaceous component of SWNT material 

is a long-standing problem, which has traditionally been addressed at a local 

scale by Scanning Electron Microscopy (SEM) and Transmission Electron 

Microscopy (TEM) techniques. (7) Recently, Near Infrared (NIR) Spectroscopy has been advanced as an effi cient tool to measure the carbonaceous purity 

of bulk SWNT samples and is discussed in Chapter 3. The NIR technique takes 

advantage of the unique spectroscopic features resulting from the interband 

electronic transitions in SWNTs and it is most effi cient for SWNT samples 

with a narrow distribution of diameters; it is distinguished from other methods 

because it is quantitative and readily applicable to bulk samples. The power 

of this method is already established by published studies that document the 

improvements in synthetic parameters and purifi cation protocols that may be 

achieved by its application. 

Chapter 4 discusses the application of resonantly enhanced Raman spectroscopy for SWNT purity evaluation. The two most prominent features observed 

in the fi rst-order resonant Raman spectrum of SWNTs are the low frequency 

radial breathing mode (RBM) and the high frequency G-band; the D-band 

associated with disordered carbon provides a measure of the contribution 

of carbonaceous impurities. A comparison of the intensities of the RBM- or 

G-bands to the intensity and shape of the D-band provides information on the 

SWNT content of the sample. Due to the resonant nature of the SWNT Raman 

response, multiple excitation wavelengths must be utilized in order to allow for 

the contributions of SWNTs of different diameters. 

Chapter 5 discusses the application of optical, electron and scanning probe 

microscopy (SPM) for SWNT quality evaluation. TEM and SEM have traditionally been the most important techniques for the characterization of carbon 

nanotubes. Indeed, SWNTs were discovered in 1993 using TEM, and highresolution TEM remains a major analytical tool for the study of SWNT nucleation and growth. The SEM technique has been extensively used to monitor 

the effi ciency of the bulk scale production of SWNTs by a variety of synthetic 
Introduction ♦

3

techniques, and it has traditionally been the most popular tool to evaluate the 

quality of as-prepared SWNT soot. (7) Because a typical SEM frame visualizes 

less than 10-12 g of an inhomogeneous sample for which there is no published 

algorithm with which to quantify the SWNT content, the use of these techniques to assess the purity of bulk SWNT samples is not recommended.

Literature Cited

1. Zhou O, Shimoda H, Gao B, Oh SJ, Fleming L, Yue GZ. 2002. Accounts of 

Chemical Research 35:1045-53

2. Mamedov AA, Kotov NA, Prato M, Guldi DM, Wicksted JP, Hirsch A. 

2002. Nature Materials 1:257

3. Kong J, Franklin NR, Zhou CW, Chapline MG, Peng S et al. 2000. Science

287:622-5

4. Avouris P. 2002. Accounts of Chemical Research 35:1026-34

5. Dai HJ. 2002. Accounts of Chemical Research 35:1035-44

6. Giles J. 2004. Nature 432:791

7. Itkis ME, Perea DE, Niyogi S, Love J, Tang J et al. 2004. Journal of Physical Chemistry B 108:12770-5

8. Arepalli S, Nikolaev P, Gorelik O, Hadjiev VG, Bradlev HA et al. 2004. 

Carbon 42:1783-91
♦ Thermogravimetric Analysis (TGA)

4

2. THERMOGRAVIMETRIC ANALYSIS (TGA)

 Sivaram Arpalli and Pavel Nikolaev

 NASA-DSC 

2.1. General Description

Thermogravimetric analysis (TGA) is an analytical technique used to determine a material’s thermal stability and its fraction of volatile components by 

monitoring the change in mass that occurs as a specimen is heated [1-4]. The 

measurement is normally carried out in air or in an inert atmosphere, such as 

Helium or Argon, and the mass is recorded as a function of increasing temperature. Sometimes, the measurement is performed in a lean oxygen atmosphere 

((1 to 5) % O2

 in N2 or He) to slow down oxidation [5]. In addition to mass 

changes, some instruments also record the temperature difference between 

the specimen and one or more reference pans (differential thermal analysis, 

or DTA) or the heat fl ow into the specimen pan compared to that of the reference pan (differential scanning calorimetry, or DSC). The latter can be used 

to monitor the energy released or absorbed via chemical reactions during the 

heating process. In the particular case of carbon nanotubes, the mass change in 

an air atmosphere is typically a superposition of the mass loss due to oxidation 

of carbon into gaseous carbon dioxide and the mass gain due to oxidation of 

residual metal catalyst into solid oxides [6-8].

2.2. Types of TGA Instruments

TGA instruments can be divided into two general types: vertical and horizontal balance. Vertical balance instruments have a specimen pan hanging from 

the balance or located above the balance on a sample stem. It is necessary to 

calibrate these instruments in order to compensate for buoyancy effects due to 

the variation in the density of the purge gas with temperature, as well as the 

type of gas. Vertical balance instruments which do not have reference pans are 

incapable of true DTA or DSC measurements. Horizontal balance instruments 

normally have two pans (sample and reference) and can perform DTA and DSC 

measurements. They are considered free from buoyancy effects, but require 

calibration to compensate for differential thermal expansion of balance arms. 

One common instrument for general purpose use, the TA Instruments Model 

SDT 2790, is used as an example for the following description and discussion 

[2]. 

2.3. Operating Principle and Defi nitions

In most cases, TGA analysis is performed in an oxidative atmosphere (air or 

oxygen and inert gas mixtures) with a linear temperature ramp (temperature of 

sample, T). The maximum temperature is selected so that the specimen mass 
Thermogravimetric Analysis (TGA) ♦

5

is stable at the end of the experiment, implying that all chemical reactions are 

completed (i.e., all of the carbon is burnt off leaving behind metal oxides). 

This approach provides two important numerical pieces of information: ash 

content (residual mass, Mres) and oxidation temperature (To) (Figure 2.1). 

While the defi nition of ash content is unambiguous, oxidation temperature can 

be defi ned in many ways, including the temperature of the maximum in the 

mass loss rate (dm/dTmax) and the mass loss onset temperature (Tonset). The former refers to the temperature of the maximum rate of oxidation, while the latter 

refers to the temperature when oxidation just begins. The use of the former 

defi nition, To = dm/dTmax, is preferred for two reasons. First, due to the gradual 

initiation of transition (sometimes up to 100 °C, Figure 2.1) it may be diffi cult 

to determine Tonset precisely. Gradual onset is believed to be due to nanotubes 

being contaminated with amorphous carbon and other types of carbonaceous 

impurities that oxidize at temperatures lower than that of nanotubes. In these 

cases, Tonset describes the properties of the impurities rather than the nanotubes. 

Second, mass loss due to carbon oxidation is often superimposed on the mass 

increase due to catalyst oxidation at low temperatures [1]. In some cases this 

leads to an upward swing of the TGA curve prior to the bulk of the mass loss, 

which makes the defi nition of Tonset even more diffi cult and ambiguous. However, determining dm/dTmax is relatively straightforward. Therefore, oxidation 

temperature is herein defi ned as To = dm/dTmax.

TGA measurement of “as-produced” nanotube material in air usually produces 

only one peak in the dm/dT curve, as “fl uffy” raw nanotubes oxidize rapidly in 

an oxygen-rich environment. However, analysis of purifi ed nanotube material 

Figure 2.1: (a) TGA of purifi ed SWCNTs; 3 specimens sampled from the same batch. 

(b) Graph illustrating the ambiguity in determining Tonset. (Plots are generated by instrument software which report values in weight.)

(a) (b)
in air may produce more than one peak. These additional peaks are likely due 

to the fact that purifi ed material contains a fraction of nanotubes with damage 

and/or with functional groups (i.e., the material is oxidized at lower temperatures) or because purifi ed material is more compacted after drying. The position of each peak is also strongly affected by the amount and morphology of 

the metal catalyst particles and other carbon-based impurities, as well as their 

distribution within a specimen. A lean oxygen environment can be used to better separate these peaks. In addition, these peaks have also been attributed to 

various components in the nanotube material (amorphous carbon, nanotubes, 

graphitic particles), and it may be possible to quantify these components by 

deconvolution of peaks [5]. 

Oxidation temperature, is basically a measure of the thermal stability of 

nanotubes in air and depends on a number of parameters. For example, smaller 

diameter nanotubes are believed to oxidize at lower temperature due to a higher 

curvature strain. Defects and derivatization moiety in nanotube walls can also 

lower the thermal stability. Active metal particles present in the nanotube specimens may catalyze carbon oxidation, so the amount of metal impurity in the 

sample can have a considerable infl uence on the thermal stability. It is impossible to distinguish these contributions, but, nevertheless, thermal stability is a 

good measure of the overall quality of a given nanotube sample. Higher oxidation temperature is always associated with purer, less-defective samples [6].

2.4. Sources of Error

When performing TGA runs on especially clean nanotubes with minimal ash 

content (< 3 %), it should be noted that residual mass is sometimes negative. 

This happens even after fresh calibration of the instrument. The long-term 

stability of the instrument zero (over a 3 h run) is within (20 to 40) μg, which 

constitutes (1 to 2) % of the initial (2 to 4) mg sample. For samples with very 

small ash content, this amounts to a fairly large uncertainty. It is therefore 

necessary to weigh each ash residue independently using a microbalance. This 

way ash content measurement accuracy is greatly improved. Other instruments 

may have better long-term zero stability, but it is still preferable to check ash 

content occasionally by independent measurement. Additionally, there may be 

a time lag in the sample temperature and the oven temperature which can be 

reduced by lowering the ramp rates. Finally, temperature calibration should be 

done periodically according to the instrument manufacturer’s specifi cations.

2.5 Practical Concerns

2.5.1 Material Inhomogeneity

It has been noted that when TGA measurements are performed on several nanotube specimens sampled from the same batch, the TGA traces do not necessar-

♦ Thermogravimetric Analysis (TGA)

6
ily coincide (Figures 2.1 to 2.8). There is always some variation that exceeds 

the accuracy and repeatability of the instrument. This observation serves to emphasize that carbon nanotube batches are not pure chemicals and, therefore, are 

not as homogenous and uniform as is usually implied for pure chemicals. This 

means that values of Mres and To produced in one TGA run are not necessarily 

representative of the whole batch. The only reasonable approach to this problem is to perform TGA on at least three (or more) specimens sampled from the 

batch and calculate mean averages of Mres and To. Interestingly, this approach 

also allows one to calculate standard deviations of Mres and To

. It is obvious that 

standard deviations σMres and σTo can serve as a measure of the inhomogeneity 

of the nanotubes in the batch (See appendix for experimental data and discussion).

2.5.2 Combustion 

Sometimes a strange, and unexpected, effect is observed in the TGA results 

(Figure 2.2). The mass trace suddenly goes backwards along the abscissa and 

then continues forward as usual. This behavior becomes easily explainable if 

the mass trace and the temperature are plotted versus time. In this graph, it is 

evident that the event is accompanied by a sudden loss of a signifi cant fraction of the sample mass, as well as a large spike in the temperature difference 

(DTA) plot. At the same time, temperature goes up by (10 to 20) °C, and then 

comes down and continues along a linear ramp. We have estimated that the 

temperature increase rate reaches up to 50 °C/min during such events and is 

fairly independent of the nominal furnace heating rare. These are unambiguous 

signs of combustion (i.e., the sample starts burning and releases a considerable 

amount of heat very quickly, causing a sharp increase in temperature followed 

by heat dissipation and a subsequent temperature drop). This behavior is more 

often observed on as-produced unpurifi ed nanotubes that are “fl uffy” and have 

more metal catalyst. It is noticed that combustion decreases Mres and increases 

its standard deviation. This probably happens due to ejection of smoke particulates from the sample pan during rapid burning (i.e., there is some poorly 

controlled mass loss beyond oxidation of carbon). Therefore it is better to avoid 

conditions that cause combustion.

Thermogravimetric Analysis (TGA) ♦

7
♦ Thermogravimetric Analysis (TGA)

8

2.5.3 Heating Rate

Typical heating rates employed in TGA measurements of carbon nanotube 

specimens are in the (10 to 20) °C/min range. It has been noted that heating 

rate has a pronounced effect on the measured values of Mres and To

 and their 

standard deviations (see Appendix). The effect on To has been attributed in the 

literature to the limited rate of heat conduction into the sample. The effect on 

Mres is mostly related to combustion that higher ramp rates are more likely to 

produce. It is found that in as-produced unpurifi ed (“fl uffy”) samples, combustion is likely to occur at or above 5 °C/min. The conclusion is that heating rate 

must be constant in all measurements to avoid inconsistency in To

 measurement, and at or below 5 °C/min to avoid combustion. Selecting a heating rate 

of 5 °C/min is a reasonable compromise, considering that lowering the rate 

more causes unacceptably long experiments.

2.5.4 Sample Mass

When working with as-produced “fl uffy” nanotubes, it is diffi cult to place more 

than 2 to 4 mg of material into a typical 200 μL sample pan. Considering the 

stability of modern TGA instruments, this quantity of material is still acceptable, but should be an absolute minimum. Samples of appoximately 10 mg are 

recommended.

2.6 Suggested Protocol

Based on the discussion above and results of the study reported in the Appendix (Section 2.7), the following protocol for TGA measurements is proposed. 

Figure 2.2: Evidence of nanotube combustion in TGA. (a) Trace going “backward”. (b) 

Temperature spike caused by combustion. Note different abscissa units – temperature 

on (a) and time on (b).
Thermogravimetric Analysis (TGA) ♦

9

If this protocol is followed for each sample, it will produce results that can be 

cross-compared.

1. Heating rate 5 °C/min. in air. Maximum temperature suffi cient to stabilize 

sample mass (typically 800 °C). 

2. Sample size at least (2 to 4) mg, more if possible.

3. Three separate TGA runs on each sample.

4. Ash content measured independently on microbalance.

Mean values of To and Mres are representative of the sample oxidation temperature and ash content. Standard deviations of To

 and Mres are representative of 

the sample inhomogeneity.

2.7 Appendix

2.7.1 Protocol Development

All TGA experiments were performed using a TA Instruments SDT 2790 TGA 

with air as a purge gas at a fl ow rate of 10-4 m3

/min (100 sccm). Figures 2.1 to 

2.9 were generated by this instrument. All samples were from the same batch 

of as-produced (“fl uffy”) single-wall carbon nanotubes produced by a highpressure carbon monoxide process (HiPco). The inhomogeneity of the material, 

the heating rate, combustion, and their combined effect on the results of the 

TGA experiments were studied. In addition, we investigated the stability of the 

instrument zero and its implications in determining precise ash content.

2.7.2 Material Inhomogeneity

Each nanotube specimen was analyzed via TGA three times at each of following heating rates: (1, 2.5, 5, 10, 30 and 100) °C/min. TGA traces for these 

experiments are shown on Figures 3 through 8. One can observe that for any 

given set of experimental parameters, the shape of the TGA curve, as well as 

the oxidation temperature, To

, and ash content, Mres, vary in each run. Variations in To

 can exceed (10 to 20) °C, and variations in Mres can exceed 5 % of 

the initial sample mass (i.e., these variations are quite signifi cant and cannot 

be dismissed as an instrument error). These variations are likely due to the 

inhomogeneity of the starting material. Therefore, ash content and oxidation 

temperature of the nanotube batch as a whole are best described as a mean of 

results from at least three runs. As each run takes considerable time (≈ 3 h at 5 

°C/min heating rate) and consumes (2 to 4) mg of the sample, it is impractical 

to do more than three runs. A sample size of (2 to 4) mg is suffi cient to produce 

good data, but not too large as to consume a signifi cant fraction of the nanotube 

material available. It has also been noticed that nanotube materials of different properties have varying standard deviations of To

 (σT) and Mres (σM). This 
♦ Thermogravimetric Analysis (TGA)

10

result could also be due to the varying degree of inhomogeneity in different 

samples. For example, unpurifi ed and purifi ed nanotubes can have

σT ≈ 2.7 °C and σT ≈ 6.5 °C respectively (5 °C/min heating rate). Therefore, σM

and σT values can be used to describe inhomogeneity of the sample – the larger 

the standard deviation, the more inhomogeneous the sample. 

Figure 2.3: TGA graphs of an unpurifi ed SWCNT material; three specimens sampled 

from the same batch; 1 °C/min heating rate in air.

Figure 2.4: TGA graphs of an unpurifi ed SWCNT material; three specimens sampled 

from the same batch; 1 °C/min heating rate in air.
Thermogravimetric Analysis (TGA) ♦

11

Figure 2.5: TGA graphs of an unpurifi ed SWCNT material; three specimens sampled 

from the same batch; 5 °C/min heating rate in air.

Figure 2.6: TGA graphs of an unpurifi ed SWCNT material; three specimens sampled 

from the same batch; 10 °C/min heating rate in air.
♦ Thermogravimetric Analysis (TGA)

12

2.7.3 Heating Rate

Heating rates as high as 100 °C/min and as low as 1 °C/min are reported in the 

literature. As mentioned above, we have done experiments with the following heating rates: (1, 2.5, 5, 10, 30 and 100) °C/min. Figure 2.9 shows that the 

Figure 2.7: TGA graphs of an unpurifi ed SWCNT material; three specimens sampled 

from the same batch; 30 °C/min heating rate in air.

Figure 2.8: TGA graphs of an unpurifi ed SWCNT material; three specimens sampled 

from the same batch; 100 °C/min heating rate in air.

mean value of To increases gradually from (360 to 430) °C as the heating rate 

increases from 1 °C/min to 30 °C/min. It is diffi cult to reliably determine To

(and its standard deviation) for the experiment with a 100 °C/min heating rate 
Thermogravimetric Analysis (TGA) ♦

13

Figure 2.9: Heating rate dependence of oxidation temperature, To, and its standard 

deviation σTo (inset).

(Figure 2.8) due to the very broad transition with several peaks that are not reproducible (this will be discussed later). The origin of such a signifi cant change 

in To

 (70 °C) is usually attributed to the limited rate of heat conduction into 

the sample. It is important to emphasize that To

 depends on the heating rate, 

and, therefore, its values produced at different heating rates cannot be directly 

compared to each other. The inset in Figure 2.9 shows that the standard deviation of To

 also increases signifi cantly as the heating rate increases, varying from 

(1 to 13.5) °C. 

The value of Mres and its standard deviation are also dependent on the heating rate. Figure 2.10 shows that Mres for (1, 2.5 and 5) °C/min heating rates 

are well within one standard deviation (which is nearly constant), while above 

5 °C/min, Mres becomes signifi cantly smaller and its standard deviation sharply 

increases. This observation can be explained by spontaneous combustion of the 

nanotubes above 5°C/min heating rate (i.e., the heat released in the exothermic 

reaction is enough to sustain rapid burning of the sample). It is impossible to 

confi rm this by direct observation of the sample in the TGA furnace, but the 

observed behavior of To and Mres also points in this direction. Combustion, 

unlike slow oxidation, is an uncontrollable process, strongly dependent on the 

morphology and size of a particular specimen. Combustion releases particulate matter (smoke) from the sample in a relatively random fashion, therefore 

reducing residual mass, which is indeed observed above 5°C/min as discussed 

above (Figure 2.10). A large increase in the standard deviation of Mres is also 

consistent with this explanation, as the additional mass loss due to smoke release in a particular run can vary signifi cantly with the size and morphology of 

the specimen. In the absence of combustion, To

 must depend only on the properties of the nanotube specimen. On the other hand, when the heating rate is 
♦ Thermogravimetric Analysis (TGA)

14

fast enough to produce combustion, the peak in the dM/dt is always reached at 

the point where combustion begins; therefore, its position depends also on the 

morphology of the specimen. This will certainly produce larger standard deviations of the To

, which is consistent with our observations (Figure 2.9 inset). 

Figure 2.10: Heating rate dependence of the residual mass, Mres, and its standard 

deviation, σMres (inset).

 TGA traces obtained at 100 °C/min heating rate (Figure 2.8) do not exhibit 

signs of combustion. Instead, mass loss occurs rather gradually in the (400 to 

600) °C temperature range. Derivative mass loss curves do not have well-defi ned peaks and appear rather irreproducible, making it impossible to defi ne 

To

. As noted above, combustion increases with the specimen heating rate 

up to approximately 50 °C/min. So, in this case, the rate of the temperature 

increase in the TGA furnace is actually higher than the maximum heating rate 

of the specimen that can be achieved even with the help of combustion. This 

means that there has to be a signifi cant time lag between furnace and specimen 

temperatures, and that mass loss rate depends mostly on the morphology of the 

particular sample. This explains the gradual mass loss and poor reproducibility 

of the derivative mass curves.

TGA results obtained with higher heating rates (allowing combustion) become 

increasingly less reliable, with standard deviations of To

 and Mres rapidly increasing (resulting in a systematic decrease in the Mres values). Therefore, it is 

important to collect TGA data with heating rates that do not allow combustion. 

For the particular specimen used in this study, only heating rates of (1 and 2.5) 

°C/min preclude combustion. However, we have noticed that purifi ed samples 

that have much less active catalyst can be run at higher heating rates without 

combustion. 
Thermogravimetric Analysis (TGA) ♦

15

Selection of the heating rate is also of practical importance. Usually a sample 

has to be heated to at least 800 °C, which requires 13.3 h at a rate of 1 °C/min, 

compared to 8 min at 100 °C/min. Heating fast saves time, so the majority of 

researchers have used (10 – 20) °C/min rates. Based on the discussion above, 

we have selected 5 °C/min as a compromise, as each run takes less than 3 h and 

we avoid combustion for most types of samples.

2.7.4 Sample Compaction

There is a huge difference in the morphology of “as-is” nanotube material and 

material that has been processed into buckypaper (usually after purifi cation, 

but sometimes unpurifi ed material is processed into buckypaper by dispersing in a solvent, fi ltering, and drying). The apparent density of unprocessed, 

“as-is” “fl uffy” material can be (1 to 2) orders of magnitude smaller than that of 

processed material. It is diffi cult to place more than (2 to 4) mg of unprocessed 

material into the sample pan. As a result, some researchers have employed 

mechanical compaction as a means to increase apparent density and specimen 

size. 

We have compared TGA results of “as-is” material with material compacted in 

a standard KBr die of 7 mm diameter by applying (0.5, 1.2 and 2.6) GPa pressure in a hydraulic press. The values of Mres were essentially unaffected, while 

compacting at progressively higher pressure leads to a (10 to 20) °C decrease 

in the To values. However, changes in To do not follow a uniform trend. To

decreases from 417 °C to 395 °C as compacting pressure goes from (0 to 0.5) 

GPa and then increases to 403 °C as compacting pressure increases to 2.6 GPa. 

Compacting pressure does not affect the standard deviations of Mres and To

. The 

reasons for this behavior are not clear. We have noticed that combustion still 

occurs at a heating rate of 5 °C/min, which is probably related to the presence 

of a considerable amount of active Fe catalyst particles. 

We conclude that it is better to avoid compaction, as results are diffi cult to predict. Compaction may be necessary for some especially “fl uffy” materials, but 

then results should be considered with full understanding that To

 may have been 

affected. In these cases, smaller compaction pressure is preferable. Generally, 

it is advisable not to compact the material by any means, which places the (2 to 

4) mg limit on the sample size for unprocessed material. It may be preferable 

to use the same sample size for processed materials, as samples of dramatically 

different mass may behave differently. For example, a much larger sample may 

heat up slower due to its higher thermal capacity. 
♦ Thermogravimetric Analysis (TGA)

16

References

1. Sivaram Arepalli, Pavel Nikolaev, Olga Gorelik, Victor Hadjiev, Williams 

Holmes, Bradley Files and Leonard Yowell, Carbon 42, 1783 (2004).

2. “Applications Library on Thermal Analysis from TA Instruments”, http://

www.tainstruments.com/main.aspx?id=46&n=2&siteid=11

3. “Application Notes on Thermal Analysis by Perkin Elmer”, 

 http://las.perkinelmer.com/search/Search.htm?Ntt=thermal+analysis&Ne=1

5&N=72+33+64+16&tab=NONE

4. ASTM E1131 – Standard Test Method for Compositional Analysis by 

Thermogravimetry

5. W.E. Alvarez, B. Kitiyanan, A. Borgna, D.E. Resasco, Carbon 39, 547 

(2001).

6. A. G. Rinzler, J. Liu, H. Dai, P. Nikolaev, C. B. Huffman, F. J. RodriguezMacias, P. J. Boul, A. H. Lu, D. Heymann, D. T. Colbert, R. S. Lee, J. E. 

Fischer, A. M. Rao, P. C. Eklund and R. E. Smalley. Appl. Phys. A 67, 29 

(1998).

7. J. L. Bahr, J. P. Yang, D. V. Kosynkin, M. J. Bronikowski, R. E. Smalley 

and J. M. Tour. J. Amer. Chem. Soc. 123, 6536 (2001).

8. Frank Hennrich, Ralf Wellmann, Sharali Malik, Sergei Lebedkin and Manfred M. Kappes, Phys. Chem. Chem. Phys., 5, 178 (2003).
Near-Infrared (NIR) Spectroscopy ♦

17

3. Near-Infrared (NIR) Spectroscopy

 Robert Haddon and Mikhail Itkis

 University of California, Riverside

3.1 Introduction

Near-infrared (NIR) spectroscopy is an analytical technique which is ideally 

suited for the characterization of single-walled carbon nanotubes (SWNTs), 

because it allows the measurement of the absorption of light in the region of 

the interband electronic transitions. These electronic transitions are the characteristic signature of the SWNT electronic structure and may be observed in the 

solution or solid state as a function of photon energy. NIR transmission spectroscopy has been extensively used to detect SWNT interband transitions (1-8), 

to evaluate the effect of ionic and covalent chemistry on the band structure (7, 

9-13), and to compare the abundance and diameter distribution of the SWNTs 

produced by different synthetic techniques as a function of synthetic parameters and catalyst composition (14-17). 

Recently, NIR spectroscopy has been advanced as an effi cient tool to quantitatively evaluate the carbonaceous purity of bulk SWNT material (18-22). The 

procedure is extremely simple, can be effi ciently used by students and technical 

personnel and utilizes equipment that is routinely available in many research 

and educational laboratories. In this chapter we formulate the main principles 

of the NIR spectroscopy-based purity evaluation technique. We present examples of the practical use of this technique for optimization of SWNT synthesis 

and for improving the parameters of a purifi cation procedure. We provide an 

assessment of the advantages and potential limitations of this purity evaluation 

technique against other carbon nanotube purity assessment methods. 

3.2. Formulation of method: Electronic Structure and Optical 

Spectroscopy of SWNTs

The electronic structure of SWNT derives from that of a 2-D graphene sheet, 

but because of the radial confi nement of the wave function the continuous 

electronic density of states (DOS) in graphite divides into a series of spikes in 

SWNTs which are referred to as Van Hove singularities (Figure 3.1) (23-26). 
♦ Near-Infrared (NIR) Spectroscopy

18

Depending on helicity and diameter, these 1-D nanostructures may be metals or 

semiconductors(23-26).

Based on simple tight-binding theory, the semiconducting SWNTs give rise 

to a series of electronic transitions between the principal mirror spikes in the 

electronic density of states (DOS) starting with S11 = 2aβ/d and S22 = 4aβ/d, 

while the metallic SWNTs show their fi rst transition at M11 =6aβ/d, where a is 

carbon-carbon bond length (nm),  β is the transfer integral between pπ-orbitals 

(β ≈ 2.9 eV) and d is SWNT diameter (nm) (5, 23-26). Current synthetic techniques produce SWNTs with a range of chiralities and diameters, and in this 

case the S11, S22 and M11 features are simultaneously present in the electronic 

spectra of the bulk SWNT sample with individual features broadened due to the 

fi nite SWNT diameter distribution (2, 3, 5, 7, 8). NIR optical absorption spectroscopy can capture these specifi c features which typically occur between (0.5 

and 3) eV (2, 3, 5, 7, 8). The optical spectra of carbonaceous and graphitic impurities present in bulk SWNT samples give rise to a featureless monotonically 

increasing absorption in this spectral region (0.5 to 4) eV (18-20, 27, 28). These 

spectral characteristics provide a unique opportunity to distinguish between the 

SWNTs and impurities present in the sample using optical spectroscopy. 

Figure 3.2 shows a schematic of the absorption spectrum of a typical electric 

arc discharge (EA) produced SWNT sample in the spectral range between the 

far-IR and the ultra-violet (UV) (10 to 45 000) cm-1, with the absorptions due to 

SWNTs and carbonaceous impurities shown in different colors to illustrate the 

different components (although it is not yet possible to analytically separate 

these contributions) (19, 20). The high-energy part of the spectrum is dominatFigure 3.1: Electronic density of states (DOS ) of semiconducting and metallic SWNTs
Near-Infrared (NIR) Spectroscopy ♦

19

ed by the π-plasmon absorption from both SWNTs and carbonaceous impurities, and the tail of this peak extends into the far-IR part of the spectrum. The 

NIR - visible part of the spectrum from (4000 to 17 000) cm-1 exhibits characteristic absorption features, originating from the interband transitions between 

pairs of Van Hove singularities in semiconducting and metallic SWNTs, which 

ride on the top of the π-plasmon tail. It is intuitively understandable, that the 

strength of these characteristic features in comparison with the featureless 

baseline provides a measure of the purity of the SWNT material. 

While the S11 transition is the most prominent, we chose the second semiconducting transition (S22, inset to Figure 3.3), for the purity evaluation because the 

S22 transition is less susceptible to incidental doping and because it matches the 

Figure 3.2: Schematic illustration of the optical spectrum of typical SWNT sample produced by the electric arc method. Inset shows the region of the S22 interband transition 

utilized for NIR purity evaluation. In the diagram: AA(S) is the area of S22 spectral band 

after linear baseline correction; AA(T) is the total area of the S22 band including SWNT 

and carbonaceous impurity contributions. The NIR relative purity is given by RP = 

(AA(S)/AA(T))/0.141 (see text).
♦ Near-Infrared (NIR) Spectroscopy

20

transmission window for dimethylformamide (DMF) which is utilized for the 

solution (dispersion) phase NIR spectroscopy (18-20). It is known that DMF is 

one of the most effi cient solvents for dispersing both raw and purifi ed SWNT 

material, and we have found that DMF can partially compensate the incidental 

doping affecting the S22 interband transition (18-20). 

We have identifi ed the ratio AA(S)/AA(T) as the simplest possible metric of 

SWNT purity, where AA(S) is the area of the S22 interband transition after 

linear baseline subtraction (dark gray area in the inset to Figure 3.2), and 

AA(T) is the total area under the spectral curve, with both areas taken between 

the spectral cutoffs of (7750 and 11750) cm-1, which were chosen to capture 

the S22 interband electronic transitions of SWNTs of the diameter produced 

by the EA-process with Ni/Y catalysts (18-20). This ratio is then normalized 

by dividing by 0.141, the value of AA(S)/AA(T) obtained for an arbitrary 

high purity reference sample of AP-SWNTs (denoted R2), and this procedure 

therefore gives rise to a relative purity (RP) (18-20). Because a 100 % pure 

reference sample is not currently available, it is not possible to give an absolute 

determination of SWNT purity, although progress may be noted (27, 28). Nevertheless, through the joint efforts of the carbon nanotube community, and with 

sample exchanges between research groups it will be possible to further refi ne 

the choice of a reference sample and to asymptotically converge on a standard 

for the measurement of absolute purity. 

3.3 Practical Procedure

3.3.1 Choice of Spectrophotometer

Common FT-IR spectrometers cover the spectral range between (10 000 and 

400) cm-1, i.e. (1000 to 25 000) nm, whereas UV-Vis (Visible) spectrophotometers usually cover the range between (175 and 900) nm, i.e., (57 000 to 11 

000) cm-1. In order to cover the typical S22 and M11 interband transitions which 

are of interest in the purity evaluation of SWNTs produced by electric arc and 

laser ablation techniques, a spectral range of (7000 to19 000) cm-1 is required, 

so neither of these types of spectrophotometers encompass the required spectral 

range. Several commercial instruments combine the UV-Visible and NIR spectral ranges and are suitable for the NIR purity evaluation procedure.

3.3.2 Sample preparation

For accurate evaluation of bulk quantities of SWNT material (>10 g), special 

attention must be paid to the preparation of the NIR samples, because as-prepared SWNT (AP-SWNT) material is typically very inhomogeneous. Below 

we present a multi-step best practices procedure developed for large scale 

batches of inhomogeneous AP-SWNT material (18-20):
Near-Infrared (NIR) Spectroscopy ♦

21

Step 1. The AP-SWNT material is mechanically homogenized to give a dry 

powder. The use of a kitchen blender operated at low speed for 5 min leads to a 

fi ne homogeneous powder. 

Step 2. Homogenized AP-SWNT soot (50 mg) is dispersed in 100 mL of 

DMF by use of an Aquasonic 50T, 75T, or 550T ultrasonic bath or equivalent 

brand for (10 to 20) min. Mechanical stirring facilitates homogenization during 

this step which should lead to a homogeneous concentated slury of SWNTs in 

DMF. 

Step 3. A few drops of the concentrated SWNT slurry is collected by 

pipette from different regions of the sample and diluted to 10 mL with fresh 

DMF and sonicated for 10 min. By use of one or two additional 10 mL scale 

dilution-ultrasonication cycles the concentration is reduced to ≈ 0.01 mg/mL, 

which provides a stable, visually non-scattering dispersion with an optical density close to 0.2 at 12,000 cm-1 in a 10 mm path-length cell. 

This preparation procedure results in a test sample, which provides a reproducible and accurate representation of the carbonaceous purity of bulk AP-SWNT 

soot. Increasing the SWNT concentration in the fi nal test sample improves the 

signal-to-noise ratio of the experimental optical spectrum, but may destabilize 

the dispersion and lead to signifi cant light scattering and thereby compromise 

the results of the purity evaluation. 

For purifi ed SWNT samples the amount of material utilized for the purity 

evaluation test can be reduced to a few mg because the material is usually fairly 

well homogenized and less material is required to give a statistically representative sample. In order to assure homogenization we recommend the use of a 

standard coffee blender to convert purifi ed SWNT material into a fi ne powder. 

3.3.3 Practical example of spectral measurements and relative 

purity calculations

The SWNT sample should be ultrasonicated just before the spectral measurement in order to assure high quality dispersion, and the spectrometer should be 

turned on 30 min prior to the measurement to allow the baseline to stabilize. 

Spectra are usually taken in the range (7000 to 17 000) cm-1 for EA-produced 

SWNTs in order to visualize both the S22 and M11 interband transitions. Some 

spectrophotometers allow the collection of spectra only as a function of wavelength. For purity calculations we recommend processing the data as a function 

of frequency (energy) as shown in Figure 3.3, because the absorbance spectra 

as a function of wavelength (proportional to inverse energy) show signifi cantly 

more curvature and are more diffi cult to analyze. 
♦ Near-Infrared (NIR) Spectroscopy

22

In order to establish the baseline a tangent line is drawn to the minima of the 

absorption curve at the low and high energy sides of the S22 transition (Figure 

3.3a); in practice it is best to use 5 data-points on each side of the chosen S22 

spectral window (7750 to 11750 cm-1 for EA -SWNTs) for the linear fi tting 

routine. The absorption spectrum within the cutoffs is presented separately 

in Figure 3.3b with calculated total area AA(T) = 662. Figure 3.3c shows the 

spectrum of the S22 feature after linear baseline correction with integrated 

area AA(S)=40. The ratio AA(S)/AA(T) is divided by 0.141 to obtain a relative 

purity, RP against the P2 reference sample:(18-20) in the present case RP = 43 

% (Figure 3.3).

 

3.3.4 Most common source of experimental uncertainty: distorted 

baseline

Figure 3.4 presents a NIR spectrum of a SWNT dispersion in DMF exhibiting 

both of the two most common spectral distortions which occur in the vicinity 

of (8000 and 12 000) cm-1 (red arrows). The distortion just above 8000 cm1 is due to presence of traces of water in the solvent which gives very strong 

absorptions that in some cases can not be properly subtracted from the baseline 

by the pure solvent in the reference channel. 

Figure 3.3: Practical procedure for determination of relative purity (RP) of AP-SWNT 

sample: a)Solid line: spectrum of SWNT dispersion in DMF in the range (7000-17 000) 

cm-1, dashed line: linear baseline, dotted lines: spectral cutoffs for purity determination; 

b) Total area AA(T) (black + gray) in the region of the S22 interband transition, calculated 

integral AA(T)=662; c) Area of S22 feature AA(S)( gray) after linear baseline correction, 

integral AA(S)=40. RP = 43 %
Near-Infrared (NIR) Spectroscopy ♦

23

In the example given in Figure 3.4 this distortion produces a negative contribution to the integrated area thus reducing the relative purity because of the 

uncertainty in the baseline position at the low energy spectral cutoff. It is 

important to use dry solvent and to avoid admitting any traces of water to the 

solvent during the sample preparation procedure. 

The step in the trace in the vicinity of 12 000 cm-1 corresponds to the change 

from the NIR detector to the UV-Vis detector in the spectrophotometer and 

introduces uncertainties into spectrum and the linear baseline correction near 

the high-energy spectral cutoff. Possible baseline choices are shown by green 

and blue colors and this uncertainty serves to introduce uncertainties into the 

calculated RP. The jumps in the spectrum result from the change of the optical 

elements inside the spectrophotometer and can be minimized by careful alignment of spectrophotometer components by the manufacturer, optimum alignment of the sample positions in both optical channels, by modifying the ratio of 

spectral resolutions in the NIR and UV-Vis spectral ranges, and by stabilization 

of the spectrometer by utilizing an extended warm-up time. It is practically 

impossible to avoid such steps in the case of scattering samples such as poorly 

dispersed SWNTs or inhomogeneous or thick SWNT fi lms. 

Figure 3.4: Example of distortions in NIR spectra (red arrows) due to the presence of 

traces of water in the DMF and the change of optical elements in the spectrophotometer. (a) complete spectrum, (b)spectrum of S22 feature after linear baseline correction. 

Choice of baseline is uncertain (between blue and green dashed lines), which leads to 

uncertainties in the integrated areas AA(T) and AA(S) and in the calculated value of the 

relative purity.
♦ Near-Infrared (NIR) Spectroscopy

24

3.4 Characterization of NIR method 

3.4.1 Reproducibility of the purity evaluation

To test the reliability of the NIR technique and the reproducibility of the purity 

measurements we prepared fi ve independent 50 mg probe samples from the 

same mechanically homogenized 10 g batch of AP-SWNT material using the 

recommended procedure.(18-20) The results of the NIR relative purity measurements are presented in the Figure 3.5. The fi ve probe samples show an 

average relative purity of 46 % with a standard deviation of 3.0 %, which corresponds to relative uncertainty ~ 7 % in the measured RP value. 

Figure 3.5: Reproducibility test of NIR purity evaluation technique: a) Solution phase 

NIR spectra of fi ve independent probe samples obtained from 10 g AP-SWNT sample; 

b) Calculated purity of the fi ve probe samples

3.4.2 Infl uence of light scattering

The NIR purity evaluation method depends on the absorption of light, but the 

interaction of electromagnetic radiation with SWNTs may lead to scattering(19, 

20, 29). The occurrence of light scattering would be a complicating factor in 

the interpretation of the absorption spectra of SWNTs and might affect the 

accuracy of the purity evaluation by contributing to the level of the baseline 

(Figure 3.3), thus reducing the measured purity. The spectral contribution to 

light scattering (S) is controlled by the ratio of the characteristic dimension of 

the scattering particles (d) and the wavelength of the incident light (λ). In the 

present situation, we consider the SWNT length to be the characteristic dimension d, because the strongest interaction of light with SWNTs occurs when the 
Near-Infrared (NIR) Spectroscopy ♦

25

light is polarized along the SWNT axis. Most SWNT samples show a wide 

length distribution, which is typically concentrated in the range d = (0.5 to 3) 

μm and this is comparable with the wavelength of light in vicinity of the S22

interband transition (λ ≈ 1 μm) that is utilized for purity evaluation. In this 

circumstance (d ≈ λ) Mie scattering is expected to dominate,(19) and this scattering mechanism becomes more important as the particle size increases (d > λ) 

In the spectral range of interest there is a crossover between λ > d and λ < d, 

and this makes it diffi cult to theoretically estimate the infl uence of scattering on 

the NIR absorption spectra, especially in the case of SWNT solution samples 

which present themselves to the light beam as dynamic highly anisotropic 

particles. 

Figure 3.6: Solution phase absorption spectra of a SWNT sample collected with the 

spectrophotometer in regular transmission confi guration (gray curve) and using an integrating sphere (black curve) to collect the scattered light.

In order to experimentally address these questions, we made use of an integrating sphere in the sample compartment of the Cary 500 UV-Vis-NIR spectrophotometer utilized in our experiments,(20) as discussed previously (29). The 

integrating sphere recovers a signifi cant fraction of the scattered light normally 

lost with the narrow aperture of collection presented in a standard transmission experiment. Figure 3.6 shows the NIR absorption spectra of an AP-SWNT 

dispersion in DMF measured with regular and integrating sphere confi gurations 

for the collection of light (20). The introduction of the integrating sphere collection leads to a small decrease in the level of the baseline, and the calculated 
♦ Near-Infrared (NIR) Spectroscopy

26

relative purities were found to be RP = 63.8 % in regular, and RP = 61.7 % in 

the integrating sphere confi gurations; Table 1 shows a comparison for three 

AP-SWNT samples with relative purities between 20 and 60 % (20). If scattering were to be signifi cant, we would expect a reduction in the relative purity, 

when measured in the regular confi guration in comparison with the case of the 

integrating sphere technique. Table 1 shows the opposite trend, with a lower 

measured relative purity in the integrating sphere confi guration, although the 

deviations are within the experimental accuracy of our technique (18-20). This 

Sample Number 1 2 3

Regular Confi guration 20.5 % 38.5 % 63.8 %

Integrating Sphere 16.5 % 35.5 % 61.7 %

Table 1. Measured NIR Purity with Spectrophotometer in Regular and 

Integrating Sphere Confi guration

suggests, that in the case of properly dispersed SWNTs, scattering does not 

materially affect the NIR relative purity evaluation. Incompletely dispersed 

samples with large aggregates of SWNTs would be expected to affect the purity 

evaluation as a result of Mie scattering, and it was for this reason that we emphasized the importance of the sample preparation procedure and stressed the 

necessity of utilizing low SWNT solution concentrations (≤ 0.01 mg/mL) (18-

20). It proved to be more diffi cult to control scattering in the case of SWNT 

thin fi lms, and this was one factor which lead to our choice of solution phase 

(18-22) rather than thin fi lm (7, 14, 15, 17) transmission spectroscopy for the 

relative purity evaluation studies. 

3.4.3 Infl uence SWNT concentration on relative purity 

determination 

We previously recommended a concentration of 0.01 mg/mL for the SWNT 

purity evaluation;(18) higher SWNT concentrations are diffi cult to stabilize 

as non-scattering dispersions, while reducing the concentration decreases the 

signal to noise ratio of the NIR spectra. In order to evaluate the importance of 

the SWNT concentration for NIR spectroscopy-based purity evaluation technique we prepared a series of dispersions of AP-SWNTs with concentrations 

between 0.05 and 0.001 mg/mL.(20) Figure 3.7 shows the NIR relative purities obtained from the NIR spectra shown in the inset, as a function of SWNT 

concentration. 
Near-Infrared (NIR) Spectroscopy ♦

27

Figure 3.7 demonstrates that the NIR relative purity values are independent of 

the SWNT concentrations, which is a simple consequence of the applicability of Beers law to SWNT dispersions (27, 28). This confi rms that the relative 

purities determined by the NIR technique are internally consistent, and that the 

sample preparation procedure does not require exact matching of the concentrations. 

3.5 Examples of the application of NIR purity evaluation 

procedure

3.5.1 Optimization of SWNT synthesis

Figure 3.8 illustrates the use of the NIR-based purity evaluation technique for 

the study of the effect of the Y concentration on the large scale Ni/Y catalyzed 

EA-discharge Ni/Y production of SWNTs.(16) The bottom panels in Figure 

3.8(a-e) show the region of the solution phase NIR spectra in the range of 

(7750 to 11750) cm-1 corresponding to the S22 interband transition for fi ve Y 

concentrations between (0.25 and 8) atom % . 

Figure 3.7: NIR relative purity as a function of the concentration of the SWNT dispersion; inset shows experimental NIR solution phase spectra utilized for calculation of 

purity.
The top panels in Figures 3.8(a-e) show the corresponding S22 features extracted from the original spectra (bottom panel) by a linear baseline correction. 

High purity SWNT samples have a high ratio of the area of the S22 band (top 

panel) to the total area under the spectral curve (bottom panel). It is clear from 

Figure 3.8 that the highest ratio and therefore the highest purity occurs in the 

vicinity of Y concentrations of (0.5 and 1.5) atom % in agreement with prior 

work (30). Thus, the NIR technique provides an effi cient tool to visualize and 

analytically evaluate the effect of catalyst composition and other synthesis 

parameters on the purity of the AP-SWNT product (16, 21). 

3.5.2 Evaluation of effi ciency of purifi cation and optimization of 

purifi cation parameters

An important application of a purity evaluation technique is the ability to effi ciently monitor and optimize the parameters of purifi cation processes.(31-33) 

Figure 3.9 shows the NIR spectra of the starting AP-SWNT material and the 

fi nal purifi ed product obtained by oxidation of AP-SWNTs in air followed by 

treatment with hydrochloric acid. According to the NIR evaluation procedure 

Figure 3.8: Solution phase NIR spectra of EA-AP-SWNT soot produced with Ni-Y 

binary catalyst as a function of the Y concentration at a constant Ni concentration of 4 

atom %. Bottom panel: spectra in the range of S22 interband transition consisting of 

featureless background (gray area) and S22 SWNT feature (black area) separated by 

the linear baseline; Top panel: the enlarged S22 interband transition obtained after the 

linear baseline subtraction. The relative carbonaceous purity of the AP-SWNT soot (top 

panel) is determined from the ratio of the area under the spectral curve in the top panel 

to the total spectral area in the bottom panel.

♦ Near-Infrared (NIR) Spectroscopy

28
the carbonaceous relative purity increased from (50 to 93) % as a result of the 

purifi cation (Figure 3.9) and the amount of residual metal catalyst decreased 

from (30 to 8) %, as determined by TGA. 

It is convenient to introduce the purifi cation recovery factor PRF (31, 33), 

which takes into account both the increase of purity and the loss of product; for 

an ideal process the product is analytically pure and PRF = 1 (33). If Y is the 

yield of the process then we have shown that the PRF is given by (33): PRF = 

[RP(P-SWNT)/RP(AP-SWNT)] × Y, where RP(P-SWNT) and RP(AP-SWNT) 

are the relative purities of the as-prepared and purifi ed SWNTs. Because the 

NIR technique applies to the carbonaceous purity of the sample the measured 

yield must be corrected for changes in the metal content of the sample and 

in this case the yield is given by Y = [Mfi n × (1-METfi n)]/[Mst × (1-METst)], 

where Mst (Mfi n) and METst (METfi n) are the sample mass and the fraction of 

metal, respectively, in the starting material (fi nal product). For example, in 

the purifi cation procedure of AP-SWNTs illustrated in Figure 3.9, Mst =10 g, 

RP(AP-SWNT) = 50 % and METst = 0.3 (metal residue of 30 % determined by 

TGA); after purifi cation Mfi n = 2.5 g, RP(P-SWNT) = 93 % and METfi n = 0.092; 

leading to PRF = 0.61 for the process. Thus about 40 % of the SWNTs present 

in the starting sample were lost during the purifi cation process. Each step of a 

Figure 3.9: NIR evalution of effi ciency of purifi cation procedure. NIR spectra in the 

range of the SWNT S22 interband transition for: (a) starting (AP) sample (NIR RP=50 

%), (b) purifi ed (NIR RP=93 %) sample; bottom panel – full spectra, top panel - S22 

band after linear baseline subtraction.

Near-Infrared (NIR) Spectroscopy ♦

29
purifi cation procedure can be evaluated and optimized on the basis of NIR relative purity and PRF fi gure of merit (31-33) taking into account that the ideal 

purifi cation process results in a PRF = 1. 

3.6 Frequently asked questions about the capabilities and limitations of the NIR technique:

The NIR technique provides a value for the relative purity (RP) - what 

about the absolute purity? 

At the present moment it is not possible to provide an absolute value of the purity of SWNTs, but it is expected that the widespread adoption of the NIR purity evaluation technique supported by other analytical techniques presented in 

this guide will soon produce samples which cannot be further purifi ed and may 

thus be considered analytically pure. The joint efforts of the carbon nanotube 

community, and sample exchanges between research groups will be required to 

asymptotically converge on a standard for the measurement of absolute purity. Based on currently available samples, we expect analytically pure SWNT 

samples to be characterized by values of AA(S)/AA(T) ≈ 0.325 and RP ≈ 230 

% when evaluated against the original reference sample R2.(20, 28) 

To which types of SWNTs is the NIR purity evaluation technique applicable? 

The NIR purity evaluation technique was initially developed for electric arc 

produced SWNTs prepared with the Ni/Y catalyst, but it has already been successfully adapted to SWNTs produced by laser ablation (34). For the applicability of NIR technique it is important that the SWNTs have a relatively narrow 

diameter distribution without overlap between the S11, S22 and M11 bands (28). 

Is the NIR technique applicable to CVD produced SWNTs?

The chemical vapor deposition (CVD) technique usually produces SWNTs 

with an extremely wide diameter distribution. As a result, there is signifi cant 

overlap of the interband transitions in these preparations, and this obscures the 

NIR spectral features and severely complicates the application of the current 

procedure. Recently, much higher selectivity of SWNT diameters and chiralities was achieved by modifying the catalyst preparations used in the CVD 

technique (35) and by the application of separation procedures (36), and the 

technique is applicable to such samples. 

♦ Near-Infrared (NIR) Spectroscopy

30
Is NIR technique applicable to HiPco produced SWNT? 

The SWNT diameter distribution of HiPco SWNTs is wider than that of 

SWNTs produced by the electric arc and laser ablation techniques, but narrower than that of most CVD-produced SWNTs. In the optical spectra of HiPco 

material, the S11, S22 and M11 bands are partially overlapping, so the direct 

calculation of the AA(S)/AA(T) ratio results in an underestimated relative 

purity. Nevertheless, the utilization of the NIR technique can be very useful for 

the comparison of SWNT content from batch-to-batch for both manufacturers 

and end-users of HiPco SWNTs, so an internal HiPco reference standard should 

be developed. Currently, there is no algorithm available to compare the purity 

of the best laser produced material against the best HiPco produced sample, so 

the development of absolute purity standards for each production technique is 

very important (28). 

Why is the linear baseline approximation used in the NIR purity evaluation procedure when a non-linear baseline fi t might be more accurate?

We utilized the linear baseline approximation, because it provides a simple, 

easily applicable and consistent purity evaluation procedure without any fi tting 

parameters. More sophisticated non-linear baseline descriptions have been advanced (21, 22); however, these techniques require multiple fi tting parameters 

for the purity evaluation procedure. Near-IR absorption studies of a number of 

different forms of carbon, including the products of EA synthesis and commercially available carbon-based nanomaterials(27, 28), has shown that the shape 

of the baseline in the range of the S22 interband transition depends critically on 

the type of nanocarbon, and this compromises the transferability of the parameters from non-linear baseline fi tting procedures. 

The NIR purity evaluation procedure implicitly assumes that the extinction coeffi cients of the SWNTs and carbonaceous impurities are equal on a 

per carbon basis. How does this affect the results of purity evaluation? 

The ultimate goal of this work is the establishment of the absolute extinction 

coeffi cients which would remove this objection and allow measurement of the 

absolute purity of the samples (27, 28). The simple metric of purity adopted 

herein [AA(S)/AA(T)] assumes that the per carbon extinction coeffi cients of 

SWNTs and carbonaceous impurities are identical. If the extinction coeffi cient 

of the impurities is higher than that of the SWNTs, the AA(S)/AA(T) ratio 

would underestimate the purity, whereas the purity would be overestimated 

in the opposite case. Current research suggests that the extinction coeffi cient 

of SWNTs produced in the electric arc is higher than that of the carbonaceous 

impurities (27, 28).

Near-Infrared (NIR) Spectroscopy ♦

31
The NIR technique utilizes the semiconducting S22 interband transition 

for purity evaluation. What can be said about the metallic SWNTs?

The majority of known bulk synthetic techniques produce a statistical mixture 

of SWNTs, which corresponds to a 2:1 ratio between semiconducting and metallic SWNTs (16), although certain CVD techniques are chirality selective(35). 

Thus we assume the semiconducting S22 interband transition provides a measure of the purity of the whole SWNT sample. 

Is it possible to use other solvents instead of DMF?

DMF is a good solvent for the purity evaluation technique, because it is one of 

the best solvents for dispersing SWNTs, does not absorb NIR radiation in the 

range of the S22 band and reduces the incidental doping effect of the SWNTs. 

Other solvents are applicable for purity evaluation, but the AA(S)/AA(T) ratio 

varies among solvents. For example, we found that the AA(S)/AA(T) ratio in 

water is lower than in DMF not only for purifi ed (doped) material, but also for 

AP-SWNTs. Thus we recommend the use of a single solvent (even if not DMF) 

for the purity evaluation routine within a particular set of experiments. 

Is it possible to use thin fi lm instead of solution phase spectroscopy?

Thin fi lm spectroscopy has been extensively used in SWNT research. Some 

types of SWNTs are very diffi cult to disperse, especially long SWNTs or purifi ed SWNTs after high temperature annealing in vacuum. In this case some 

users of the NIR technique prefer to spray a thin fi lm of SWNTs on an optical 

substrate for use in NIR spectroscopy. This approach is entirely legitimate (14, 

37), but we found it more diffi cult to obtain reproducible AA(S)/AA(T) ratios, 

that the results were somewhat dependent on the thickness of the fi lm and that 

it is not trivial to obtain homogeneous non-scattering fi lms (29), as opposed to 

non-scattering dispersions (20). Similar to the case of different solvents, the 

ratio AA(S)/AA(T) can be different for a sample in the solution phase and as a 

thin fi lm, so it is important to be consistent in the use of either solution phase or 

thin fi lm spectroscopy during a set of experiments. 

How does debundling (rebundling) of SWNTs affect the results of the 

purity evaluation? 

It has been shown that debundling of the SWNTs or the separation of individual SWNTs leads to better resolved absorption spectra with narrow peaks 

corresponding to the interband transitions of SWNTs of particular chirality 

(38). Does such debundling affect the AA(S)/AA(T) ratio? To a fi rst approximation we do not expect that debundling and the resultant change of the 

♦ Near-Infrared (NIR) Spectroscopy

32
Near-Infrared (NIR) Spectroscopy ♦

33

shape of the spectra would affect the integral values AA(S) and AA(T) and the 

measured purity value. However, at the present time, there are no experimental 

data comparing optical spectra of the same ensemble of SWNTs in individual 

and bundled forms, so this point remains uncertain. 

How does the interpretation of the absorption features affect the results of 

the purity evaluation: Interband transitions versus excitons

In the past few years it has been proposed, that the observed S11, S22 and M11 

bands do not correspond to interband transitions between pairs of Van Hove 

singularities, but are rather exciton bands due to the strong coupling of electrons and holes in the 1D-system (39, 40). This issue is not fi nalized yet, but 

there are no obvious reasons to suggest that a change of interpretation of the 

SWNT absorption feature would preclude utilization of this optical transition 

for purity evaluation purposes. 

Acknowledgement. This work was supported by DOD/DARPA/DMEA under 

Awards No. DMEA90-02-2-0216 and H94003-04-2-0404.

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92: 077402

Near-Infrared (NIR) Spectroscopy ♦

35
4. Raman Spectroscopy

 Anna Swan, Boston University

Raman spectroscopy is a widely used tool to characterize material composition, 

sample temperature, and strain from analysis of the material-specifi c phonon 

mode energies (1, 2). It requires very little sample preparation and a rapid, 

non-destructive optical spectrum is easily achieved. 

Raman scattering is a weak interaction, and typically less than one in a million 

of the incoming photons exchanges energy with the phonons in bulk materials. The incoming light interacts with an electron that makes a virtual or real 

transition to a higher energy, where the electron interacts with a phonon (via 

electron-phonon coupling) before making a transition back to the electronic 

ground state. In this instantaneous process, energy and momenta are conserved 

so that Escattered= Elaser± hΩ for Stokes (-) and Anti-Stokes (+) scattering respectively, with Ω being the frequency of the particular phonon mode. The energy 

of the inelastically scattered light is measured with respect to the laser energy 

(in cm-1), and by convention, the stronger signal from the loss side (Stokes) is 

counted as positive. The choice of laser energy (typically in the visible or nearinfrared) does not affect the Raman shift, but if the laser energy is resonant 

with an electronic transition, the Raman intensity can be increased by many 

orders of magnitude. In a one-dimensional system such as carbon nanotubes 

where the density of states is strongly peaked, resonance Raman scattering 

dominates over non-resonant contributions. Hence, resonance Raman scattering from nanotubes gives information of the vibrational mode from the Raman 

shift, as well as of the optical transition energy since it is close to the energy of 

the laser.

This section is meant to give a brief background to resonant Raman scattering 

applied to carbon nanotubes and practical advice on how to do the measurements, while discussing some pitfalls to be aware of when interpreting data. 

While Raman scattering can be used for quantitative measurements, most standard measurements give relative and qualitative information that is best used 

for comparisons of similar samples in the same sample state (e.g., in ropes, 

powders, solution, polymers, etc.) 

The most prominent Raman active peaks in carbon nanotubes are the low frequency, radial breathing modes (RBM) and the higher frequency, D, G and G′

modes (to be defi ned in Section 2 of this chapter). While D, G, and G′ modes 

are also found in graphite, the RBM mode is a unique carbon nanotube mode. 

A study of the RBMs gives information regarding the distribution of nanotube 

diameters in a given sample. Due to the resonance behavior of the Raman 

intensity, several laser lines need to be used to determine the extent of the 

♦ Raman Spectroscopy

36
diameter distribution. The relative strength and width of the D band mode also 

gives a qualitative measurement of how large a fraction of graphitic material 

and nanotubes with defects are present in the sample. Figure 4.1 shows Raman spectra from a high-pressure carbon monoxide (HiPCo) produced powder 

where the RBM, D, G and G′ bands are shown.

Raman Spectroscopy ♦

37

4.1 Resonant Raman Scattering in Carbon Nanotubes

Electronic structure

One of the more intriguing aspects of carbon nanotubes is they can be either 

metallic or semiconducting with variable and direct bandgap. Depending on 

the chirality (n,m), the nanotubes are metallic when n-m = 3k (k=integer) and 

semiconducting otherwise. This essential feature of the electronic structure is 

readily obtained from considering the electronic structure of graphite and then 

applying chirality-dependent quantization of the allowed electron states in the 

confi ned directions. The one-dimensional electron bands lead to sharp peaks 

in the joint electronic density of states, the so-called van Hove singularities, 

which are labeled Eii with i=1,2,3,... numbering the valence and conduction 

sub-bands (3-6). The singularities provide for strong resonant enhancement of 

the otherwise weak Raman signal. The Eii is roughly proportional to 1/diameter 

and are often plotted against the nanotube diameter, in what is called a Kataura 

plot. 

Figure 4.1. Raman spectra of carbon nanotubes
♦ Raman Spectroscopy

38

Exciton versus band edge resonance

It has recently been demonstrated experimentally that optical transitions in 

nanotubes between the van Hove singularities are modifi ed by electron-hole 

interaction with very large binding energies (7, 8). As is typical for a 1D 

system, the entire optical oscillator strength gets transferred from the band 

edge absorption Eii to the exciton absorption energy, Eii- Ebinding. While this has 

far-reaching consequences for optically generated transport measurements, it 

does not signifi cantly affect the analysis of resonant Raman scattering (9). The 

main difference is that the resonance occurs with the associated lowest bright 

exciton rather than the band edge energy Eii. For simplicity, we will continue 

to refer to the optical transition energies as Eii rather than excitons. However, 

it is important to keep in mind that the excitonic resonance energies are dependent on the tube’s local environment. For example, screening effects change the 

energies for tubes in different environments, e.g., dry powder versus individual 

tubes in solution or in air. Other environmental changes such as heating or 

cooling, strain, etc., also tend to shift the resonance energies. The implication 

is that a tube can move in and out of resonance by changing the environmental 

surroundings of the tube. For example, Raman signal from the (10,2) species is 

observed with a 785 nm laser line for a nanotube bundle, but the signal disappears when the tubes are dispersed in solution. Hence, the Raman signal will 

originate from a different subset of an ensemble when the environment changes 

suffi ciently. Examples of how the resonance energy changes for individual 

tubes in solution and in bundles are shown in the appendix.

Resonance Raman profi le

Scanning the laser energy through an optical resonance gives the resonance 

excitation Raman profi le for a given carbon nanotube phonon mode. Unlike 

photoluminescence excitation profi les where the center of the profi le coincides 

with the optical transition Eii, the Raman excitation profi les have two contributions; electronic resonance with the incoming laser light, ( E laser= Eii), and 

electronic resonance with the scattered light, which is shifted by a phononenergy: Escattered= Elaser± hΩ = Eii . Hence, the center of the resonance profi le is 

Eii ± hΩ/2.
Raman Spectroscopy ♦

39

Figure 4.2. Resonance excitation profi le.The curves show the Stokes (red) and AntiStokes (blue) resonance excitation profi les for (9,4) individual nanotubes with RBM = 

257 cm-1 (15).

4.2 Raman-Active Modes in Carbon Nanotubes (RBM, D, G 

and G′)

Carbon nanotubes have a rich Raman spectrum, but here we will only discuss 

the most well-known bands. For an extensive review of the Raman scattering 

from nanotubes, see (10). The parent material to carbon nanotubes is graphite, 

which has several phonon modes that are Raman active. The most prominent 

modes are the G-band (G-graphite), the D-band (D-disorder) and the G′ band 

(second-order Raman scattering from D-band vibrations). In addition to the 

graphite modes, carbon nanotubes have a unique, prominent, phonon mode 

due to isotropic radial expansion of the tube, which is called the radial breathing mode (RBM). The RBM frequency is inversely proportional to the diameter of the tube, making it an important feature for determining the diameter 

distribution of a sample. Its absence in other graphitic forms makes it a useful 

diagnostic for confi rming the presence of nanotubes in a sample. Below, each 

Raman-active mode will be discussed further.
♦ Raman Spectroscopy

40

4.2.1 Radial Breathing Mode (RBM)

The RBM mode is the real signature of the presence of carbon nanotubes in 

a sample, since it is not present in graphite. The group theoretical notation is 

A1g and it is often called the “breathing” mode. The RBM frequency (ω) is 

inversely proportional to the nanotube diameter with the relation

ω(cm-1) = A/dia(nm) + B(cm-1)

where the constants A and B have been determined experimentally with A= 223 

cm-1/nm, B=10 cm-1. Several groups have found slightly different best fi ts of A 

and B, but for tube diameters between (0.8 to 1.3) nm, they give nearly identical frequency-diameter results. Most experimental systems that use a single 

grating spectrometer with a holographic notch fi lter for laser line rejection are 

limited to Raman frequencies larger than (100 to 120) cm-1, which restricts 

the range of diameters that can be measured to smaller than ≈ (2 to 2.5) nm. 

The use of multi-grating systems can lower the possible observed frequencies, 

thereby permitting larger tubes to be studied.

Several groups have mapped the transition energy versus radial breathing mode 

frequency (Energy vs. 1/diameter) to form the Raman equivalent of the Kataura 

plot (Energy vs. diameter) (11-14). Knowledge of the diameter and resonance 

energy Eii makes it possible to separate the RBM signatures of metallic tubes 

from semiconducting tubes using the Kataura plot (Eii vs diameter), and for 

Figure 4.3. Experimentally determined Kataura plot for SWNTs in sodium dodecyl 

sulfate (SDS) solution. The colored horizontal bars represent different common laser 

energies (blue: 488 nm, green: 514.5 nm, red: 632.8 nm, magenta: 785 nm). Data 

points are grouped according to common 2n+m = constant families, with the near zigzag terminus of each family identifi ed. For semiconducting tube types, circles represent 

chiralities with mod (n-m, 3) = -1, while triangles represent chiralities with mod (n-m, 3) 

= +1. Experimental data obtained from (11-14).
Raman Spectroscopy ♦

41

small diameter tubes where there are fewer chiralities / diameter, it may be 

possible to assign the chirality from resonant Raman spectra. Figure 4.2 shows 

an experimentally determined plot for individual nanotubes in solution for E11

and E22 semiconducting and E11 metallic transitions (15). While it is possible 

to pair RBM frequencies with Eii obtained from full Raman excitation profi les 

to arrive at a nearly unambiguous chirality assignment for a specifi c RBM, the 

Kataura plot may be used to help in assigning RBM features obtained in single 

excitation line spectra. The horizontal lines in Figure 4.3 show commonly 

used laser line energies: Ar-ion 488 nm (blue), 514.5 nm (green); HeNe 632.8 

nm (red); and Ti-Sapphire 785 nm (magenta). The resonance window, which 

determines which specifi c chiralities will appear in a RBM spectrum excited 

at a given excitation wavelength, will depend strongly on the environment and 

varies from tens of meV for a single nanotube to >140 meV for nanotubes in 

bundles. RBMs from nanotubes outside the resonance window of a selected 

excitation wavelength will not be observed. Furthermore, the resonance energies have been observed to shift depending on environment due to screening, 

with the highest resonance energies found for individual nanotubes in air, (10 

to 30) meV lower for individual nanotubes in solution and ≈ 100 meV lower 

for nanotubes in bundles.

4.2.2 The G Band

The G mode is a tangential shear mode of 

the carbon atoms. In graphite, there is one 

single G mode at ≈ 1580 cm-1. In carbon 

nanotubes, the single G band transforms into 

several modes due to the confi nement of 

wave-vectors along the circumference. For 

chiral tubes, the G-band is composed of six 

modes with symmetries A1g, E1g and E2g (two 

of each). The frequency of the higher energy branch, G+

 does not vary with diameter, 

while the low energy branch, G- gets softer 

for smaller diameter nanotubes. Examples 

of G-band structure from different carbonbased materials are shown in Figure 4.4, 

from (16).

Semiconducting nanotubes: The highest 

mode, G+

= (1590 to 1595) cm-1 is a longitudinal optical (LO) shear mode parallel to the axis of the nanotube. Transverse 

optical (TO) shear modes perpendicular to the tube axis, G-

 modes, are softened 

due to the curvature or smaller diameters, and the frequency depends on the 

Figure 4. 4. From (16). G bands 

for graphite (HOPG), multiwall 

CNTs (MWNT), semiconducting and 

metallic SWNTs.
♦ Raman Spectroscopy

42

tube diameter. The G band line shapes are Lorentzian and relatively narrow 

even in a bundle for defect-free nanotubes (FWHM ≈ 11 cm-1). 

Metallic nanotubes: The metallic tubes are easily recognized from the broad 

and asymmetric Breit-Wigner-Fano line-shape of the G-

 band. The frequency 

down shift of the G- is particularly strong for metallic nanotubes, with down 

shifts of the G-

 mode of ≈ 100 cm-1 for small diameter tubes. The G- energy 

decreases with decreasing diameter faster than for semiconducting nanotubes 

while the G+ remains essentially constant in frequency; see Figure 4.5 (17). 

The line-shape was initially attributed to coupling between the G- phonons with 

low-lying optical plasmon corresponding to the tangential motion of the electrons on the nanotube surface. Recent work instead suggests that the coupling 

is due to a resonance between phonons and electron-hole pairs and that the assignment of the axial and circumferential assignments are reversed for metallic 

tubes, i.e., that the lower energy G- is a LO (axial) phonon mode (18).

Figure 4.5. From (17) Measurements showing the diameter dependence of the G- band 

for metallic and semiconducting nanotubes

4.2.3 Second Order Raman scattering, the D and G′ Modes (Zone 

Boundary Phonons)

The D and G′ modes originate from longitudinal optical (LO) phonons from 

the vicinity of the K-point in the (graphene) Brillouin zone. The Raman D and 

G′ are second order processes that involve e-phonon scattering from k + q via 

the zone boundary LO phonon, and scatters back to the k state either elastically via a defect (D band) or inelastically via a second LO phonon, and emits a 

photon by recombining with a hole at a k state.
Raman Spectroscopy ♦

43

The D band: The D- band is called a defect mode because a defect is needed to 

elastically scatter in order for the process to conserve momentum. The second 

order scattering described above can either be due to phonon-defect or defectphonon scattering which yields two Raman peaks of slightly different energies. 

The quality of a sample is often evaluated by comparing the D to G band intensity, or the D to G′ intensity. For high-quality samples, without defects and 

amorphous carbon, the D/G ratio is often below a couple of percent. Examples 

of such low D/G ratios can be found in CVD-grown nanotubes (19) and in 

high-quality laser oven-grown nanotubes (20).

 

Since different nanotubes have different resonance energies, the D band frequency is not fi xed for different laser energies. Table 4.1 gives approximate 

values for four different laser lines. The D band is present in all carbon allotropes, including amorphous sp2

 and sp3 carbon. The D band signal can originate from nanotubes with defects and/or from non-SWNT carbon. One way to 

identify the different contributions is by the line-shape of the D-band, where a 

broad peak (≈ 100 cm-1) is indicative of amorphous carbon. The d-band width 

for nanotube ensembles are ≈ (10 to 20) cm-1.

Figure 4.10 (Section 6 of this Chapter) in the Appendix shows the D and G 

band in double wall carbon nanotube powder before and after optical heating. 

The heating has removed much of the defect-rich carbon nanotubes and amorphous carbon as is evidenced from reduction of the D band intensity.

Laser line (nm/eV) 785 / 1.58 633 / 1.96 514 / 2.41 488 / 2.54

D-band (cm-1) ≈ 1290 ≈ 1330 ≈ 1345 ≈ 1360

Table 4.1. Approximate values for D band Raman shift with different laser excitation 

energies.
♦ Raman Spectroscopy

44

The G′ Band: The G′ band at frequencies (2500 to 2900) cm-1 is the second 

order process from two zone boundary LO phonons with wave vectors q and 

-q, thus automatically preserving the momentum conservation constraint. 

Therefore, the G′ band is an intrinsic property of the nanotube and graphite, 

and present even in defect-free nanotubes where the D band is completely absent. The frequency of the G′ band is close to twice the D-band frequency. The 

dispersion of the G′ band is ωG’ ~ 2420 cm-1+105 cm-1/ Elaser (eV). 

Figure 4.6. a) 2 G′ peaks from a (15,7) nanotube where the incident EL = 2.41 eV and 

the scattered EL − EG =2.08 eV light. The resonant energies are E33 =2.19 eV and 

E44 =2.51 eV. From (21).

Incoming and Outgoing (Scattered) Resonances: The energy of a G′ band is 

substantial, (≈ 0.33 eV). In ensemble measurements, nanotubes can be resonant 

either with the incoming laser energy, or with the (lower) scattered energy, 

and both scattering events will contribute to the signal. Incoming and outgoing scattering resonances will result in G′ bands at different energies due to the 

energy dispersion of the G′ band. Sometimes, the incoming and scattered light 

matches a nanotube electronic structure so well that the incoming and scattered 

light can both be resonant with two different Eii’s from one particular nanotube. 

In this case, two G′ peaks at different energies are observed from the same 

nanotube, due to the energy dispersion of the phonon modes near the zone 

boundary as is illustrated in Figure 4.6 (21). 
Raman Spectroscopy ♦

45

4.3 Width of the Resonance

It is of interest to know the width of the resonance to determine how far away 

from a resonance it is possible to get a Raman RBM signal. The incoming 

resonance is peaked around Eii, and the outgoing resonance is a phonon energy 

higher (Stokes) or lower (anti-Stokes). The width of the resonance window is 

approximately the sum of the RBM energy + the resonance broadening γ.

Ensemble measurements (11-14)

• Solution: The broadening γ has been measured to be γ ≈ 60 meV for nanotubes dispersed in sodium dodecyl sulfate solution. 

• Bundles: For nanotubes in thick bundles the broadening is γ ≈ 120 meV.

Individual measurements (15)

• For (nearly) individual nanotube measurements suspended in air or on 

substrates, the width γ varies from γ = (10 to 40) meV. 

4.4 Strength of the Raman Signal; Electron–Phonon Coupling

Apart from the electronic resonance condition that controls the strength of the 

Raman signal, the peak intensity also depends on the electron-phonon (e-ph) 

coupling. This is an active area of research with constant updates in the literature. Both measurements and calculations agree that there is a strong chirality 

and diameter dependence of the e-ph coupling for the radial breathing modes as 

well as a dependence on which Eii is active. For semiconducting nanotubes, the 

Raman scattering cross-section is proportional to 

2

2

2

() () | | cos3 ii ii

e ph

t t

aE bE M

d d − = +ν θ

where the constants a and b depend on which electronic energy level Eii is 

excited, υ is the chiral index -1 or 1 (22). Hence, when determining chirality 

distributions from Raman RBM intensities one has to take into account the 

chirality dependent e-ph coupling strength (13, 15, 23, 24).
♦ Raman Spectroscopy

46

4.5 Depolarization and Selection Rules 

The largest Raman intensity will be generally observed for light polarized along 

the tube axes, and almost no signal will be observed for cross-polarized light. 

The intensity varies as cos4

θ, where θ is the relative angle between the electric 

fi eld, E, and the nanotube axis. The angular dependence can be used to measure 

the degree of alignment, e.g., carbon nanotubes dispersed in a polymer matrix.

The decrease in signal for polarization perpendicular to the nanotube axis is 

due to depolarization or the antenna effect. Light with an external electric fi eld 

vector parallel to the nanotube axis, E||, does not induce a polarization, and 

the total fi eld is equal to the external fi eld. On the other hand, an electric fi eld 

perpendicular to the nanotube axis, E┴, induces charges on the two opposing 

sides of the wall. The effect is a large opposing depolarization fi eld that reduces 

the external fi eld E┴. The antenna effect is a strong effect for narrow nanotubes 

<2 nm.

The resonance with the Eii transition for light polarized parallel to the nanotube 

axis is due to angular momentum conservation which requires ∆m=0 for E||

where m is the angular momentum quantum number. For a perpendicular fi eld 

E┴ the angular momentum conservation requires ∆m=±1, i.e., Eij with j= i±1. 

Due to the depolarization effect, Eii transitions are favored over Eij transitions.

4.5 Practical Considerations

4.5.1 Measurement Setup

A variety of commercial Raman instrumentation is available for characterization of nanotube samples. Instrumentation ranges from relatively inexpensive 

(≈ $10,000) fi xed wavelength benchtop systems with common excitation wavelengths of 532 nm, 633 nm, or 785 nm. Higher sensitivity single wavelength 

systems based on high-throughput spectrographs incorporating holographic 

diffraction gratings and notch fi lters are also available at higher cost. For studies of single nanotubes in very disperse samples, micro-Raman instrumentation 

is used which consists of a microscope coupled to a spectrometer with a CCD 

camera and one or more laser excitation sources.

More versatile scanning Raman systems may be assembled from commercially 

available triple spectrographs coupled to tunable excitation sources such as 

Ti:Sapphire and dye lasers. Similar excitation tunability may be coupled to 

micro-Raman systems.

In all systems, the spectrometer grating should be chosen to have a large 

throughput for the laser line(s) used, and to give the desired spectral resolution, 

preferably 3 cm-1 or better.
Raman Spectroscopy ♦

47

Calibration and Alignment

If several laser lines are used it is necessary to re-align optical paths and calibrate the frequencies after each line switch, and the practitioner should follow 

standard alignment procedures.

Before each set of measurements a quick check of alignment and calibration 

should be done:

Calibration of grating reading:

• Check that the Stokes and anti-Stokes peak frequencies are symmetric 

around the laser line for the test sample. 

• A general calibration is needed with well-known lamp lines, such as those 

from helium, neon or krypton for absolute frequency measurements and to 

assign the spectral resolution. These can be compared with known values 

found at http://physics.nist.gov/PhysRefData/ASD/lines_form.html . Other 

Raman shift standards such as acetamidophenol (Tylenol) or cyclohexane 

may also be effectively used for spectral calibration. See the McCreery 

group website: 

 http://www.chemistry.ohio-state.edu/~rmccreer/freqcorr/shift.html

• For tunable laser sources, an optical wavemeter 

can be used to calibrate the laser energy.

Optical path alignment for micro-Raman 

instruments:

• Adjust the excitation path so that the laser light 

goes straight through the objective: when adjusting the z-position in and out of focus, the laser 

spot should expand symmetrically. If not, the 

spectral calibration will be off and collection effi ciency lowered.

• Use a calibration sample with a strong and wellknown Raman line, e.g., the ≈ 521 cm-1 Raman 

line from polished silicon (100). Align the Si 

(110) direction with the laser polarization. Check 

that the Si Raman signal is maximized for a given 

wavelength, laser power and slit width. Record 

the signal per second for a specifi c power for 

comparison. 

Figure 4.7. G band 

from powder and from 

individual nanotube on 

substrate. Heating effects are clearly seen for 

the powder where the 

G band is down shifted 

23 cm-1 while the single 

tube is unaffected at 3 

times the power.
♦ Raman Spectroscopy

48

4.5.2 Laser Power Heating Effects 

It is relatively easy to unintentionally heat the sample by optical heating, 

especially when using a Raman microscope, in which the laser light is focused 

to a small focal volume with a resulting high power density. Optical heating 

of the sample could possibly damage the sample by burning, and also change 

the resonance energies which decrease with temperature. Therefore, suffi cient 

sample heating will result in resonance with a different subset of the sample, 

and yield different spectra at different temperatures. It is only when a (nearly) 

single nanotube is studied that one can determine the actual effect of heating 

on the Raman spectra. For bulk measurements, any change is convoluted by 

resonances with a different subset of nanotubes in the sample. The laser powers 

that can be safely used without signifi cant heating depend both on laser energy 

and on sample preparation as discussed below. More details are given on this 

topic in the Appendix (section 6 of this chapter).

Diagnostics

The G+

 mode frequency can be used as a thermometer. In the literature, frequency shifts of the G+

 mode with temperature from (-0.022 to -0.048) cm-1/K 

have been reported. To avoid excessive heating, the power should be lowered 

until the G+ stays constant in energy. 

The Stokes/anti-Stokes intensity ratio for the radial breathing modes is also an 

indictor of the temperature, and a change in this ratio with laser power is also 

an indication of excess laser heating. However, this ratio is more complex to 

interpret since the ratio depends both on temperature and the resonance energy. 

For example, if Elaser±Eii at T1

 and the temperature increased to T2, the change in 

resonance condition will tend to decrease the IAS/IS ratio while the Boltzmann 

factor favors an increase in the IAS/IS ratio with increasing temperature. 

Sample Type

The physical state of the sample (and the degree of impurities) plays a large 

role in choosing a suitable laser power. Samples with a higher degree of 

graphitic impurities heat more easily, presumably since the effective thermal 

conductivity of the graphitic impurities are not as high as for nanotubes, see 

Figure 4.7. 

Individual nanotubes dispersed in solution with a surfactant will heat signifi -

cantly less than a dry powder/ bundles in air, and individual nanotubes on a 

substrate are also effi cient in dissipating heat. The heating of nanotubes in a 

polymer matrix will depend on the degree of dispersion of the nanotubes and 

heat conductivity and heat capacity of the polymer. 
Raman Spectroscopy ♦

49

We recommend using < 3 x 105 W/cm2 for samples in solution and for individual nanotubes on a substrate, and <104

 W/cm2 for powders and dispersions 

in polymers and to check whether a decrease in power will further shift the G+

band frequency. 

4.5.3 Material Inhomogeneity 

Carbon nanotube powder varies in composition on a micrometer scale. Therefore it is recommended that several spectra are collected from different sample 

positions to get a statistically meaningful measurement. A second approach is 

to collect signal from a larger area.

Sample Preparation

Since environment and the degree of nanotube aggregation will infl uence 

excitation window, excitation energy and degree of heating, it is necessary to 

prepare samples that will be compared in the same way. Whether raw, dry material, or formed into a pellet, or dissolved into solution, or dispersed on fi lter 

paper, or isolated, each sample preparation brings its own unique features to the 

Raman spectra and therefore should be considered during analysis.

Solution preparation: Typical preparation of solution samples of nanotubes 

begins with high shear mixing of the nanotubes in a 1 % aqueous solution of 

surfactant. The suspension is then ultrasonicated at high power with tip or 

cuphorn sonicators (typically for 10 min). Samples are then ultracentrifuged. 

Four hour centrifuge times work well, with acceleration force chosen depending on nanotube production method. For HiPco nanotubes, an acceleration 

force of 110,000 g works well, while lower forces (60,000 to 70,0000) g work 

better for samples with small diameter distributions (such as those produced 

in the cobalt-molybdenum catalyst (CoMoCAT) based process. Centrifuged 

samples will show separation between pelleted aggregates (found at the bottom 

of the centrifuge tube) and individualized nanotubes, which are decanted off. 

Common surfactants are sodium dodecyl sulfate (SDS), sodium dodecylbenzene sulfate (SDBS), sodium cholate, and even direct suspension into single or 

double stranded DNA. SDBS is known to give the most blue-shifted excitation 

spectra of any of the listed surfactants. For large-diameter nanotubes, such as 

those produced in laser-oven methods, sodium cholate or polymeric surfactants 

(such as Triton-X 100 or Pluronic) may be most suitable for sample suspension. Solution spectra are readily obtained from samples contained in nuclear 

magnetic resonance or melting point capillary tubes.
♦ Raman Spectroscopy

50

4.6 Appendix

4.6.1 Illustration of Aggregation Effects

As noted above, sample state and environment will have a signifi cant effect on 

features observed in SWNT Raman spectra, particularly in the RBM region. 

These effects are primarily due to shifting and broadening of the electronic 

transitions. These effects are most pronounced in comparing solution to aggregated samples. Figure 4.8 illustrates the signifi cant red-shifting and broadening of excitation profi les for the (12,1) and (10,2) chiralities that occur upon 

nanotube bundling. As seen in Figure 4.9, such changes in excitation spectra 

can lead to very different features appearing in RBM spectra at a given excitation wavelength.

Such effects underscore the importance of understanding the effects of electronic perturbation on observed RBMs. This is particularly relevant to the use 

of Raman for characterization of separation processes. Care must be taken to 

ensure that observed changes in relative RBM intensities are not incorrectly 

attributed to changes in relative populations of their corresponding chiralities, 

when the cause may instead be a shift in electronic transition energies that 

Figure 4.8. Comparison of Raman 

excitation profi les of SDS solubilized and 

bundled nanotubes for the (12,1) and 

(10,2) chiralities. The vertical line represents the 785 nm excitation line position. Figure 4.9. Comparison of RBM spectra 

for SDS solubilized and bundled nanotubes at four specifi c excitation wavelengths.
Raman Spectroscopy ♦

51

brings a different set of chiralities into resonance with a specifi c excitation 

wavelength.

As illustrated in Figs. 4.8 and 4.9, the use of 785 nm excitation can be a 

practical means for probing the extent of nanotube aggregation. Bundling of 

nanotubes results in increased enhancement of the (10,2) RBM at 265 cm-1, 

relative to nearby RBMs (including the (12,1) mode at 236 cm-1), producing the 

so-called roping peak. Note that, while the (10,2) RBM at 265 cm-1 is strongly 

observed only in the bundled sample with 785 nm excitation, the (12,1) RBM 

at 236 cm-1 appears strongly enhanced in both sample types. This behavior 

results from the different resonant excitation conditions experienced by the 

two chiralities. As seen in Figure 4.8, 785 nm excitation is near the peak of 

the excitation profi le for the individualized (12,1) nanotubes, but is well away 

from the resonance window for the (10,2) in solution. Thus, the (12,1) RBM is 

observed but not the (10,2). Bundling-induced red-shifting places the 785 nm 

excitation near the peak of the (10,2) transition, while signifi cant intensity in 

the tail of the (12,1) profi le still remains. Therefore, for bundled samples, both 

the (12,1) and (10,2) chiralities will be observed.

4.6.2 Illustration of Heating Effects

Figure 4.10 shows the effects of optically heating a sample of double wall 

carbon nanotube powder. As the optical power is increased, the G band is 

Fig 4.10. Effect of optical heating of a powder sample. G band Raman shift indicative of 

optical heating of DWNT powder using 514 nm laser. 100 % power =8 mW with NA=0.8 

objective. A) Down-shift in the G+ mode as a function of optical power. The numbers 

indicate the time sequence of the measurements B) Raman spectra at low power (no 

heating) before and after thermal cycling shows the reduction of the D band intensity 

and line-width after heating.
♦ Raman Spectroscopy

52

dramatically shifted down in frequency due to heating. Here 100 % power 

corresponds to 8 mW optical power at 514 nm with a NA=0.8 objective (≈ 106

W/cm2

). The maximum shift of the G band corresponds to a sample temperature increase of ≈ 480 °C using the most conservative estimate of 0.048 cm-1/K. 

Subsequent cycles of increasing and decreasing the optical powers show a less 

marked heating than the fi rst increase, Fig 4.10 A. This behavior can be correlated to the removal of carbon impurities and nanotubes with defects shown in 

Fig. 4.10 B), which shows the reduction in the D-band intensity after the local 

optical heating.

The D-band disappears as the temperature is increased, and during subsequent power cycling the temperature increases less. These results illustrate 

that a sample with large D-band tends to heat more readily than a more ideal 

nanotube sample, and that heating can remove the defects, either by annealing 

defects or the physical “burn off” of the defective material.

 

4.6.3 Measurements from One Individual Nanotube - “Nano-Slit 

Effect”

In confocal microscopy, a pinhole is used in the image plane of the microscope 

system to limit the area and the depth from which the signal is collected from 

the sample. Confocal techniques are used for mapping an image at different 

depths (confocal sectioning), e.g., mapping nanotube composite depth profi les, 

although the penetration depth will limit the depth information that is possible 

to extract. When confocal microscopy is used from a sparse sample, the nanoscaled object will act as a “nano-slit”, and a slight displacement of the nanoparticle from the optical axis will lead to false shifts in the measured Raman 

frequency. 

Figure 4.11. A) from (15) False Raman shift as a function of horizontal displacement 

of a single nanotube (in red). B) Measurement of the optical beam profi le at the focal 

plane using a nanotube.
Raman Spectroscopy ♦

53

Knowing the resolution of the spectrometer, detector pixel size, and the overall magnifi cation from object plane to detector, this “pseudo-shift” is easily 

calculated for a given distance in the spectral direction of the emitter from the 

optical axis. 

The “nano-slit” effect is illustrated in Fig 4.11 A) by measuring the shift RBM 

frequency as a function of position stepping across the nanotube oriented 

parallel to the groove direction of the spectrometer grating. For comparison, 

the silicon 521 cm-1 Raman peak from the substrate is also shown. The silicon 

signal originates from all points illuminated by the beam spot and is unaffected 

by translation and consequently does not shift with sample position. 

The “nanoslit” confi guration also provides an elegant method for directly 

measuring the profi le of the beam intensity in the object plane. An example is 

shown in Fig. 4.11 B).

Acknowledgements

We would like to thank Angela Hight-Walker of NIST, Gaithersburg, Apparao 

Rao of Clemson University and Victor Hadjiev of University of Houston for 

critical reading of the manuscript. Special thanks to Sivaram Arepalli at NASAJohnson Space Center and Steve Freiman of NIST for coordinating the effort, 

and for their continuous support and advice. 

Literature Cited

1. Ferraro J. 2002. Introductory Raman Spectroscopy Academic Press

2. Smith E, Dent G. 2005. Modern Raman Spectroscopy Wiley

3. Dresselhaus MS, Dresselhaus G, Jorio A. 2004. Annual Review of Materials Research 34:247-78

4. Kataura H, Kumazawa Y, Maniwa Y, Umezu I, Suzuki S et al. 1999. Synthetic Metals 103:2555-8

5. Reich S, Thomsen C, Maultzsch J. 2004. Carbon Nanotubes: Basic Concepts and Physical Properties Wiley

6. Saito R, Dresselhaus G, Dresselhaus MS. 1998. Physical Properties of 

Carbon Nanotubes Imperial College Press

7. Maultzsch J, Pomraenke R, Reich S, Chang E, Prezzi D et al. 2005. Physical Review B 72:

8. Wang F, Dukovic G, Brus LE, Heinz TF. 2005. Science 308:838-41

9. Vamivakas AN, Walsh A, Yin Y, Unlu MS, Goldberg BB, Swan AK. 2006. 

Physical Review B 74:

10. Dresselhaus MS, Dresselhaus G, Saito R, Jorio A. 2005. Physics ReportsReview Section of Physics Letters 409:47-99
♦ Raman Spectroscopy

54

11. Doorn SK, Heller DA, Barone PW, Usrey ML, Strano MS. 2004. Applied 

Physics A-Materials Science & Processing 78:1147-55

12. Fantini C, Jorio A, Souza M, Strano MS, Dresselhaus MS, Pimenta MA. 

2004. Physical Review Letters 93:

13. Maultzsch J, Telg H, Reich S, Thomsen C. 2005. Physical Review B 72:

14. Telg H, Maultzsch J, Reich S, Thomsen C. 2006. Physical Review B 74:

15. Yin Y, Walsh AG, Vamivakas AN, Cronin SB, Stolyarov AM et al. 2006. 

Ieee Journal of Selected Topics in Quantum Electronics 12:1083-90

16. Jorio A, Pimenta MA, Souza AG, Saito R, Dresselhaus G, Dresselhaus 

MS. 2003. New Journal of Physics 5:

17. Jorio A, Souza AG, Dresselhaus G, Dresselhaus MS, Swan AK et al. 2002. 

Physical Review B 65:

18. Lazzeri M, Piscanec S, Mauri F, Ferrari AC, Robertson J. 2006. Physical 

Review B 73:

19. Doorn SK, Zheng LX, O’Connell MJ, Zhu YT, Huang SM, Liu J. 2005. 

Journal of Physical Chemistry B 109:3751-8

20. Dillon AC, Parilla PA, Alleman JL, Gennett T, Jones KM, Heben MJ. 

2005. Chemical Physics Letters 401:522-8

21. Souza AG, Jorio A, Swan AK, Unlu MS, Goldberg BB et al. 2002. Physical Review B 65:

22. Goupalov SV, Satishkumar BC, Doorn SK. 2006. Physical Review B 73:

23. Jorio A, Santos AP, Ribeiro HB, Fantini C, Souza M et al. 2005. Physical 

Review B 72:

24. Luo ZT, Papadimitrakopoulos F, Doorn SK. 2006. Applied Physics Letters

88:
Optical, Electron and Probe Microscopy ♦

55

5 Optical, Electron and Probe Microscopy

 Cheol Park and Peter Lillehei, NASA Langley Research 

Center, Science and Technology Corporation Hamption, VA, 

and National Institute of Aerospace, VA

5.1 General Description

The development of tools to assess the dispersion of nanotubes in polymer 

matrices is based on the premise that one cannot improve what cannot be 

measured. An accurate assessment of the dispersion is the most critical factor in correlating the behavior of the fi nal nanotube polymer composites to the 

nanostructure. This guide outlines the tools and the procedures used to assess 

the dispersion of nanotubes in a polymer matrix to allow for improvement and 

tailor-ability of the multifunctional properties of the composites.

5.2 Introduction

The biggest challenge in translating the multifunctional properties of nanotubes 

into improved composite structure performance is the diffi culty in achieving an 

effective dispersion of the nanotubes in a polymer matrix (1-7). A new set of 

characterization techniques is required to assess nanotube dispersion in polymer matrices. The work presented herein lays a foundation for the systematic 

characterization of carbon nanotube composites via optical, electron, and probe 

microscopy.

Spectroscopic tools such as UV-VIS, IR, and Raman aid characterization by 

providing information on tube structure, functionalization, charge transfer 

between the polymer and the nanotubes, and even alignment of the nanotubes 

within the matrix (8-10). However, these techniques are optically based and, 

thus, sample an ensemble of nanotubes because the minimum spot size is on 

the order of a few microns even in state-of-the-art instruments. While this 

information is useful and necessary to help understand the electrical, mechanical, and thermal data collected on the composites, additional information on 

how the nanotubes are actually being distributed within the polymer matrices 

is necessary to better understand the nanocomposite morphologies. This has 

led to the effort to develop these visual techniques to complement the optical 

spectroscopic techniques already commonly used to characterize nanotubes and 

nanocomposites.

The procedures used to assess dispersion of nanotubes in polymer matrices are 

outlined in Fig. 5.1. The sample is fi rst examined by optical microscopy to determine if any large-scale agglomerations are present. Figure 5.2 shows typical 

examples of optical micrographs of undesirable dispersion with SWNT aggre-
♦ Optical, Electron and Probe Microscopy

56

gates and desirable uniform dispersion. If the sample passes optical microscopy 

standards, it is characterized as being optically dispersed (Figure 5.2b) It is 

then suffi cient to state that the sample does not have any visual aggregation on 

the scale of approximately 1 μm or larger. To assess the aggregation, bundling, 

alignment, and local concentration gradients on a scale below 1 μm requires 

electron and probe microscopy techniques. These techniques include scanning 

electron microscopy (SEM), transmission electron microscopy (TEM), and 

scanning probe microscopy (SPM). Defi ning the quality of the dispersion on a 

scale below 1 μm is subjective. To suggest that a sample with 500 nm bundles 

is well dispersed would be misleading; therefore this guide outlines a procedure 

for the accurate assessment of bundle size, presence of agglomerations, and local concentration gradients on the scale below 1 μm. 

The following sections describe the procedures and data that can be gleaned 

from the analytical techniques used, with a discussion pertaining to the limits 

of data interpretation. This will serve as a foundation for a robust and quantifi -

able nanotube composite characterization and will establish the limits for each 

analytical method. 

5.3 Experimental Description

5.3.1 Instrumentation

Optical Microscopy 

The optical microscope typically employs the use of light in the visible spectrum to generate a micrograph. Illumination of the samples above or below the 

sample determines the imaging mode, either refl ection or transmission respectively. Ultraviolet illumination, polarizers, bright fi eld/dark fi eld imaging and 

optical fi lters enable enhanced imaging techniques. 

Scanning Electron Microscopy

A scanning electron microscope employs the use of high-energy electrons, 

rather than photons, to image a surface. The sample must have a moderate 

electrical conductivity and be stable in a high vacuum environment. Some new 

environmental scanning electron microscopes can handle low vacuum and high 

effi ciency in-lens detectors can handle low conductivity samples, but for the 

most part conductivity and high vacuum stability is a requirement. The primary 

electron beam is scanned over the surface generating secondary electrons (SE), 

backscattered electrons (BSE), and Auger electrons, in addition to x-rays. The 

Auger electrons and x-rays can be collected to give spectroscopic or chemi-
Optical, Electron and Probe Microscopy ♦

57

cal identifi cation. The SE are collected to generate the topographical images. 

BSE are used generate maps based on atomic number. As the primary beam is 

scanned its position is mapped with respect to the number of SE, BSE, Auger 

electrons and x-rays recorded at their respective detectors.

Transmission Electron Microscopy

Transmission electron microscopes use a much more intense electron beam 

when compared to the beam used in SEM. These can be in the range of (200 

to 300) keV for most commercial instruments. The collection of the SE, BSE, 

Auger electrons and x-rays can be achieved just as in SEM, but in addition the 

electron beam that passes entirely through the sample can be collected generating a transmission electron image. These electrons can be fi ltered based on how 

much energy was lost to the sample allowing for an additional spectroscopic 

technique. The scanning and transmission electron microscope’s use of an 

electron beam to image a sample is a much higher resolution technique, when 

compared to optical microscopy, due to the much smaller characteristic wavelength of the electrons compared to the wavelength of visible photons. TEM, 

being the highest resolution technique, is typically capable of imaging samples 

up to atomic resolution.

Scanning Probe Microscopy

Scanning probe microscopes are a family of microscopes that have the following m,odes of operation: scanning tunneling microscopy (STM), atomic 

force microscopy (AFM), magnetic force microscopy (MFM), electric force 

microscopy (EFM), tunneling AFM (TUNA), current sensing AFM (CSAFM) 

magnetic resonance force microscopy (MRFM), electron spin resonance STM 

(ESR-STM), near fi eld scanning optical microscopy (NSOM), and others. In 

all cases a small probe is scanned in close proximity to or in contact with a 

sample. Depending on the technique different aspects of the sample can be 

interrogated. STM uses an atomically sharp Pt or W probe in close proximity 

to a conductive sample under bais to record the tunneling current between the 

sample and the probe. AFM, MFM, EFM, TUNA and CSAFM use a MEMS 

based probe positioned in the near fi eld to record the topography, magnetic 

fi eld, electric fi eld and tunneling current and current fl ow respectively. Spectroscopic data can be recorded in the adfvanced techniques such as MRFM and 

ESR-STM. NSOM also uses a MEMS based probe but can collect optical and 

spectroscopic data simultaneously.
♦ Optical, Electron and Probe Microscopy

58

5.3.2 Contrast generation

To assess the dispersion of nanotubes within a polymer matrix requires a method of generating contrast between the SWNT and the various polymer matrices. 

Regardless of the techniques used at least one single attribute of the nanotubes 

that differs from the host polymer is exploited in a manner to generate contrast 

between the nanotubes and the matrix. Whether it is optical transparency, electrical conductivity, or some other physical property of the nanotubes that differ 

from the polymer, contrast is generated between the polymer and the tubes by 

mapping the variations in the composite based on these properties. 

Optical microscopy techniques are particularly valuable for assessing poor 

dispersion rapidly. Contrast is generated between the nanotubes and the polymer due to vastly different optical properties of the nanotubes and the host 

polymer. In either transmission or refl ection the dispersion of the nanotubes on 

a large scale greater than 1 μm is easily assessed. Dispersion of the SWNT into 

aggregates or bundles smaller than the diffraction limit in the visible light range 

generally requires the use of electron and probe microscopy. 

Contrast in SEM is due to the vastly different levels of conductivity of the 

SWNT and the polymer matrix. The composite builds up a charge from the 

primary electron beam and a stable electric fi eld is generated on the surface of 

the sample. If the nanotubes are part of an electrical percolation network, they 

will dissipate the charge and lower the fi eld to a less negative potential. If the 

electric fi eld is stable, the percolation network can be imaged. Nanotubes disrupt the fi eld in the surrounding polymer and appear as dark regions against the 

bright polymer matrix. Nanotubes at or near the surface, or penetrating into a 

cross-section, generate their own secondary electrons and appear as bright fi laments in the image. This is shown in Figure 5.3 where SWNTs penetrate into a 

fi lm and reverse contrast from bright to dark as they enter the polymer matrix; 

a few of these areas are highlighted by arrows in the Figure. If the local nanotube concentration is high enough, the electric fi eld artifact will be overlaid on 

the secondary electron image. This explanation is consistent with the theory of 

electric fi eld artifact imaging described by Goldstein et al. and others (11-14).

TEM studies were hindered by the weak contrast of the SWNTs within the 

composite, and two methods are used for contrast enhancement with some success. Image math and power spectrum fi ltering operations are used to enhance 

the periodicity contrast of the SWNT versus the polymer matrix. The adhesion 

and wetting of a polymer matrix on SWNT surfaces is assessed using energy 

fi ltered TEM (EFTEM) and electron energy loss spectroscopy (EELS) techniques (15).
Optical, Electron and Probe Microscopy ♦

59

In the SPM techniques contrast is generated by the paramagnetic and electrical 

behavior of the SWNTs (16). Direct imaging of SWNT bundles and even individual tubes is achieved with the SPM technique of magnetic force microscopy 

(MFM). The MFM technique is an interleaved atomic force microscopy (AFM) 

procedure using a cantilever coated with a ferromagnetic material, typically 

cobalt. The AFM probe records the sample topography in a standard intermittent contact mode, then the probe is lifted a fi xed distance above the recorded 

surface features and long range forces are measured as a phase shift on the 

freely oscillating cantilever. Tunneling AFM (TUNA) permits visualization 

of the percolation network by mapping local current fl ow from a sample and 

probe operating under a bias potential. This is similar to current sensing AFM 

(CAFM) but operates in the pA range.

5.4 Suggested Protocol

The investigation of 4 samples is described to illustrate the characterization procedure (see Table 5.1). It is important to note that the samples are all 

SWNT-polyimide composites made under various processing conditions or 

with varying concentrations of nanotubes. Details of sample preparation are 

documented elsewhere (1, 2, 3, 15).

Characterization of SWNT dispersion is performed in a top down approach. 

Optical microscopy is used as a screening tool for electron and probe microscopy. Table 5.1 shows an example of the optical microscopy images taken in 

transmission for each sample. 

The samples are each prepared for optical microscopy by either casting a fi lm 

or preparing a thin section. If the sample is transparent, transmission illumination is a very good and quick method to capture the large-scale bulk dispersion. 

For a uniformly dispersed composite, at least x200 magnifi cation is recommended. Agglomerations on a scale large than 1 μm are easily visible with this 

technique. If the sample is not transparent, illumination via refl ection does give 

some indication of the large-scale dispersion but the sample will need to be examined on the surface and in cross-section to assess the dispersion throughout 

the bulk of the sample. 

Sample 1 was processed in a direct mixing procedure and large-scale agglomerates could be clearly seen. The percent optical transmission of this sample 

is very low, on the order of 1 % at 500 nm. Sample 2 was made with the same 

formulation but the nanotubes were incorporated into the composite via an 

in-situ polymerization technique (1, 3). In contrast to the direct mixing technique, this sample has a 32 % transmission at 500 nm with the same thickness. 
♦ Optical, Electron and Probe Microscopy

60

Sample 2 is considered “optically dispersed.” If the composite does not need 

further optimization for the intended application, optical characterization is 

usually suffi cient. However, if optimization of mechanical, electrical, or thermal properties is required, a more in-depth analysis of the dispersion is needed. 

Samples 2, 3, and 4 illustrate the need for characterization beyond the optical 

microscope. These samples are all considered optically dispersed though they 

have different mechanical and electrical properties. It is rationalized that the 

resulting differences in mechanical and electrical properties are due to varying levels of dispersion of the SWNTs within the composite. Differences in 

samples 2, 3 and 4 are visible with optical microscopy but it is not clear what is 

the cause of the differences. Scratches, dust, entrapped air bubbles and catalyst 

particles along with nanotube agglomerates are visible in all the images. These 

defects are clearly visible with this technique and need to be recorded to give 

an overview of the nanotube distribution and the overall defect density. What is 

not clear is how the majority of the tubes are distributing themselves between 

these defects. 

To investigate the difference between samples 2, 3 and 4 beyond the optically 

dispersed limit requires an investigation of the nature of the dispersion below 

the 1 μm scale. The main tool employed in this investigation is the high resolution FE-SEM (HR-FESEM). This tool creates a stable electric fi eld in most 

polymers and generates a very high collection effi ciency of the secondary electrons, such that samples just exceeding the electrical percolation threshold are 

easily imaged without the typical thin metal coating. Figure 5.4 shows samples 

(1 to 4) normal to the fi lm surface and in cross-section. Aggregates and an 

inhomogeneous distribution are visible in the fi lm and cross-section of samples 

(1 to 3), whereas a uniform distribution with no visible aggregation is seen in 

sample 4. At this point it is important to note that the only difference between 

samples 3 (Figures 5.4e and 5.4f) and 4 (Figures 5.4g and 5.4h) is the SWNT 

manufacturing process. Sample 3 was made by the HiPco process and sample 4 

was made by a laser ablation technique. The HR-FESEM is powerful enough to 

detect the dispersion differences due only to the SWNT manufacturing process.

The electron microscopy investigations of these composites requires very little 

preparation. Samples are mounted on the specimen stage using a conductive 

adhesive, typically a silver paste. It is important that the imaging surface has at 

least a moderate conductivity (>10-8 S/cm). The samples are not coated with a 

conductive layer, but rather inserted directly into the specimen chamber without any additional preparation. The accelerating voltage of the primary electron 

beam is set to as low of a voltage as is practical for imaging the specimen. 
Optical, Electron and Probe Microscopy ♦

61

Typically this process begins somewhere around 0.5 keV and is brought up 

until a contrast is generated between the conductive nanotubes and the nonconducting host matrix. If contrast cannot be established, a variation in the scan 

rate may be necessary to establish the contrast. 

The ability to image a network of nanotubes is not limited to HR-FESEM. Conventional W-fi lament SEMs are more than capable of imaging such networks as 

shown in Figure 5.5. Typically, great efforts are employed to reduce the presence of such image artifacts, as those arising from a charge build-up that generates a large electric fi eld. However, for these studies the electric fi eld artifact is 

the tool exploited to image nanotubes that are part of the percolation network. 

Thus uncoated SWNT-polymer composite samples are directly inserted into 

the electron microscope and grounded to a sample stage with silver paste. With 

SEM, details on SWNT aggregation and distribution are easily determined and 

estimates of the bundle sizes can be made as well. 

More quantitative information on the size of individual tubes and how they 

bundle requires the use of the TEM. SWNT-polymer composite samples 

typically require microtoming or ion milling to create thin sections suitable 

for TEM imaging. Figure 5.6 shows a SWNT-polymer composite where the 

individual tubes in bundles are clearly visible in the polymer under high magnifi cation. It was observed that the tubes were not locked into a single rope-like 

confi guration, but pass from one bundle to the next.

Novel scanning probe techniques are shown in Figure 5.7. MFM characterized the dispersion of the SWNT in polymer composites by mapping the 

magnetic fi eld at a fi xed height above the sample (16). The TUNA technique 

was complementary to MFM, though much more straightforward. These SPM 

techniques are of particular interest because they are simple approaches that do 

not require an electron microscope. The distribution of SWNTs in the polymer 

matrix are clearly visible in both the MFM (Figure 5.7(b, d)) and TUNA images (Figure 5.7(c, e)) (21). 

The MFM requires the use of a Co/Cr coated AFM cantilever. Contrast is 

enhanced with the thicker Co coatings found on high moment MFM cantilevers (≈ 100 nm Co). These thick coatings increase the radius of the MFM tip 

and degrade the spatial resolution. Careful consideration of spatial resolution 

versus contrast generation needs to be balanced for the MFM imaging. Once a 

suitable cantilever that gives adequate contrast and spatial resolution is found, 

the MFM probe is magnetized by placing the probe over a strong magnet for 

several minutes. The sample is then placed on the scanner above a strong 

magnet. The paramagnetic nanotubes, which are a subset of the total nanotube 
♦ Optical, Electron and Probe Microscopy

62

population, disrupt the local magnetic fi eld from the strong magnet under the 

sample. These nanotubes are imaged with the MFM in an interleave mode. The 

sample topography is fi rst scanned and then the probe is raised a fi xed distance, 

typically (7 to 15) nm, above the surface and the magnetic fi eld gradient is 

then recorded. These small lift heights require that the sample be relatively fl at 

before imaging. Thin fi lms formed by spin casting or knife coating work best.

The TUNA procedure requires the use of a conductive AFM probe. The restrictions on the coatings are limited so long as the probe is conductive. As such 

the conductive probes can have a much sharper tip radius when compared to 

the MFM probes. The TUNA procedure is also a direct technique, not requiring an interleave or lift mode. The sample topography and tunneling current 

are recorded simultaneously at each pixel. Additionally, the bias voltage can 

be scanned to enhance or reduce contrast in the current image. This scanning 

of the bias voltage can even bring different portions of the network into view, 

allowing for a more detailed analysis of the network as a function of applied 

voltage.

5.5 Conclusions

The use of conventional microscopy techniques enables the investigation of 

carbon nanotube dispersions in polymer composites. Subtle differences at the 

nanoscale produce large changes in the composite and necessitate the closer examination of these materials by electron and probe microscopy. The end result 

is a method of SWNT composite investigation that involves examination by 

optical microscopy to fi rst determine if SWNT dispersion is poor. Second, the 

SEM is used on the composite surface and cross-section to determine bulk dispersion. If additional information is required beyond the degree of dispersion, 

then direct imaging of the nanotubes by TEM yields information on the size 

and packing of individual bundles. The use of FE-SEM over conventional SEM 

is not necessary to assess the dispersion, but it can be benefi cial for composites 

with limited conductivity or samples susceptible to signifi cant beam damage. 

Probe microscopy techniques are useful tools to investigate nanotube dispersion and provide complementary information to electron microscopy.

Acknowledgement

Park appreciates the NASA University Research, Engineering and Technology 

Institute on Bio Inspired Materials (BIMat) under award no. NCC-1-02037 for 

partial support.
Optical, Electron and Probe Microscopy ♦

63

Literature Cited

1. Park C, Ounaies Z, Watson KA, Pawlowski KJ, Lowther SE, Connell JW, 

Siochi EJ, Harrison JS and St. Clair TL 2002. NASA/CR 2002-211940 

2. Kumar S, Dang TD, Arnold FE, Bhattacharyya AR, Min BG, Zhang X, 

Vaia RA, Park C, Adams WW, Hauge RH, Smalley RE, Ramesh S and 

Willis P A 2002. Macromolecules 35: 9039

3. Ounaies Z, Park C, Wise KE, Siochi EJ and Harrison J S 2003. Composites 

Sci. and Technol. 63: 1637

4. Siochi EJ, Lillehei PT, Wise KE, Park C and Rouse JH 2003. SEM Annual 

Conference MEMS/NEMS

5. Siochi EJ, Working DC, Park C, Lillehei PT, Rouse JH, Topping CC, Bhattacharyya A and Kumar S 2004. Composites Part B 35: (5) 439

6. Smith J G Jr., Connell JW, Delozier DM, Lillehei PT, Watson KA, Lin Y, 

Zhou B and Sun Y-P 2004. Polymer 45: 825

7. Delozier DM, Tigelaar DM, Watson KA, Smith JG Jr., Lillehei PT and 

Connell J W 2004. SAMPE Symposium & Exhibition

8. Haggenmueller R, Gommans HH, Rinzler AG, Fischer JE and Winey KI 

2001. Chem. Phys. Lett. 330: 219

9. Thostensona ET, Renb Z and Choua T-W 2001. Composites Sci. and Technol. 61: 1899

10. Strano MS, Dyke CA, Usrey ML, Barone PW, Allen MJ, Shan H, Kittrell 

C, Hauge RH, Tour JM and Smalley RE 2003. Science 301: 1519

11. Knoll M 1941. Naturwissenschaften 29: 335

12. Kong J, Soh HT, Cassell AM, Quate CF and Dai H 1998. Nature 395: 878

13. Zhang Y, Chang A, Cao J, Wang Q, Kim W, Li Y, Morris N, Yenilmez E, 

Kong J and Dai H 2001. Appl. Phys. Lett. 79: 3155

14. Goldstein JI, Lyman C E, Newbury D E, Lifshin E, Echlin P, Sawyer L, 

Joy D C and Michael J R 2003. Scanning Electron Microscopy and X-Ray 

Microanalysis 3rd ed. Kluwer Academic/Plenum Publishers, New York 

Chapter 5.

15. Park C, Crooks RE, Siochi EJ, Harrison JS, Evans N, Kenik E 2003. Nanotechnology 14: L11–L14

16. Lillehei PT, Park C, Rouse JH and Siochi EJ 2002. Nano. Lett. 2: 827

17. Viswanathan R and Heaney MB 1995. Phys. Rev. Lett. 75: 4433

18. Simpson J, Ounaies Z and Fay C 1997. Mat. Res. Soc. Symp. Proc. 459: 53

19. Wise K E, Park C, Siochi EJ, Harrison J S 2004. Chem. Phys. Lett. 391: 207

20. St. Clair AK and St. Clair TL 1986. U.S. Patent 4,603,061

21. The topographical image and the MFM image were obtained simultaneously, while the TUNA image was taken on the same sample after the tip 

was exchanged. Thus the MFM and TUNA images are at slightly different 

locations on the sample.
♦ Optical, Electron and Probe Microscopy

64

Figures and Tables

Table 5.1. Optical microscopy images of samples 1-4.

Figure 5.1. Guide to assess the dispersion of SWNT in polymer matrices.

Figure 5.2. Optical micrographs: (a) undesirable dispersion with SWNT aggregates, (b) desirable uniform SWNT dispersion (optically dispersed) in a 

polyimide matrix. 

Figure 5.3. HR-FESEM images of a SWNT-CP2 composite in cross-section 

showing the SWNTs penetrating out of the fi lm. Nanotubes that are penetrating 

out of the cross-section generate their own secondary electrons and appear as 

bright fi laments in the image. The arrows highlight points where the nanotubes 

penetrate into the polymer and disrupt the electric fi eld in the surrounding polymer. The contrast is then reversed and the nanotubes appear as dark regions 

against the bright polymer matrix.

Figure 5.4. HR-FESEM images on the dispersion quality of samples 1-4. (a) 

Surface and (b) cross-section of sample 1 showing poor dispersion quality. 

Optical microscopy already showed this sample had a poor dispersion; shown 

here for comparison. (c) Surface and (d) cross-section of sample 2 showing improved dispersion over the direct mixing technique. (e) Surface and (f) crosssection of sample 3 showing an improved dispersion from using the β-CN 

polymer. Dispersion is still not ideal due to poor quality of SWNT. (g) Surface 

and (h) cross-section of sample 4 showing nearly 100 % dispersion, no visible 

aggregates, very small bundles, and no resin rich areas. 

Figure 5.5. SEM image of a SWNT-CP2 composite showing the same electric 

fi eld artifact contrast as seen with the HR-FESEM.

Figure 5.6. TEM of SWNT-CP2 directly showing individual tubes in the polymer matrix.

Figure 5.7. Scanning probe microscopy images complementary to electron 

microscopy of 2 SWNT-β-CN composites (a-c: 0.5% SWNT β-CN, d-f: 2% 

SWNT β-CN). (a,d)Topography, (b,e) MFM images and (c,f) TUNA images.
Optical, Electron and Probe Microscopy ♦

65

17

Figure 5.1

Composite preparation

Optical microscopy

Is the dispersion

acceptable?

Is the lack of dispersion due to:

1. Nanotube quality

2. Fabrication process

3. Polymer composition

No

Correct issue(s) causing

poor dispersion

Yes

Determine reason for

lack of dispersion. Use

microscopy,

spectroscopy, and other

necessary test methods.

No or Unknown

Is the reason for

lack of

dispersion now

known?

Is additional

microscopy needed

to determine reason

for lack of

dispersion?

Yes

No

No

Electron and

probe

microscopy on

surface and

cross-section

Yes,

optically dispersed

Does the

application

require a further

assessment of

the dispersion?

Yes

Process

improvement /

optimization

No

Yes

Assess the bundle size, presence of

agglomerates, and local concentration gradients

to fully characterize the dispersion

Is the level of

dispersion

sufficient for the

application?

Yes

Design experiments to

determine reason for lack

of dispersion

No

Does the

application

require further

optimization?

Yes

Done

No

Figure 5.1. Guide to assess the dispersion of SWNT in polymer matrices.
♦ Optical, Electron and Probe Microscopy

66

Lillehei et al.

Figure 5.2 

200m

(a)

100μm

(b)

Figure 5.2. Optical micrographs: (a) undesirable dispersion with SWNT aggregates, (b) 

desirable uniform SWNT dispersion (optically dispersed) in a polyimide matrix.
Optical, Electron and Probe Microscopy ♦

67

19

Figure 5.3 

(a) (b)

Figure 5.3. HR-FESEM images of a SWNT-CP2 composite in cross-section showing 

the SWNTs penetrating out of the fi lm. Nanotubes that are penetrating out of the crosssection generate their own secondary electrons and appear as bright fi laments in the 

image. The arrows highlight points where the nanotubes penetrate into the polymer and 

disrupt the electric fi eld in the surrounding polymer. The contrast is then reversed and 

the nanotubes appear as dark regions against the bright polymer matrix.
♦ Optical, Electron and Probe Microscopy

68

Table 5.1 

Sample Mixing 

Conditions

Optical Microscopy

Sample 1

1% SWNT 

CP2

Direct Mix

Sample 2

1% SWNT 

CP2

In-situ

polymerization 

under 

sonication

Sample 3

0.5% SWNT 

-CN

In-situ

polymerization 

with HiPco 

SWNT

Sample 4

0.5% SWNT 

-CN

In-situ

polymerization 

with laser 

ablation SWNT

Table 5.1. Optical microscopy images of samples 1-4.
Optical, Electron and Probe Microscopy ♦

69

Figure 5.4 

(c) (d)

(g) (h)

(e) (f)

(a) (b)

Figure 5.4. HR-FESEM images on the dispersion quality of samples 1-4. (a) Surface 

and (b) cross-section of sample 1 showing poor dispersion quality. Optical microscopy 

already showed this sample had a poor dispersion; shown here for comparison. (c) 

Surface and (d) cross-section of sample 2 showing improved dispersion over the direct 

mixing technique. (e) Surface and (f) cross-section of sample 3 showing an improved 

dispersion from using the β-CN polymer. Dispersion is still not ideal due to poor quality 

of SWNT. (g) Surface and (h) cross-section of sample 4 showing nearly 100 % dispersion, no visible aggregates, very small bundles, and no resin rich areas. 
♦ Optical, Electron and Probe Microscopy

70

22

Figure 5.5 

Figure 5.5. SEM image of a SWNT-CP2 composite showing the same electric fi eld artifact contrast as seen with the HR-FESEM.
Optical, Electron and Probe Microscopy ♦

71

23

Figure 5.6 

50 nm

SWNT bundles

Figure 5.6. TEM of SWNT-CP2 directly showing individual tubes in the polymer matrix.
♦ Optical, Electron and Probe Microscopy

72

24

Figure 5.7 

 

(a)

5 μm 5 μm

300 nm

150 nm

0 nm

(b) (c)

5 μm

5 μm 5 μm 5 μm

(d) (f) (e) 250 nm

125 nm

0 nm

Figure 5.7. Scanning probe microscopy images complementary to electron microscopy of 2 SWNT-β-CN composites (a-c: 0.5% SWNT β-CN, d-f: 2% SWNT β-CN). 

(a,d)Topography, (b,e) MFM images and (c,f) TUNA images.

March 2008