r a ctice guide NATL INST OF STAND & TECH 111

A111Q7 D17M0b

NtST

PUBLICATIONS

Measurement

Issues in Single Wall

Carbon Nanotubes

Stephen Freiman

Stephanie Hooker

Kalman Migler

Sivaram Arepalli

c. aNisnr

National Institute of Standards and Technology

U.S. Department of Commerce

Special

Publication

960-19

NIST Recommended Practice Guide

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

Carlos M. Gutierrez, Secretary

National Institute of Standards and Technology

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

U.S. Department of Commerce
Certain equipment, instruments or materials are identified in this paper in order

to adequately specify the experimental details. Such identification 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.

Official 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)

CODEN: NSPUE2

U.S. GOVERNMENT PRINTING OFFICE

WASHINGTON: 2001

For sale by the Superintendent of Documents

U.S. Government Printing Office

Internet: bookstore.gpo.gov Phone:(202)512-1800 Fax:(202) 512-2250

Mail: Stop SSOP, Washington, DC 20402-0001
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 field 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 practitio- ners in the field 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.

iii

1. Introduction

2. Thermogravimetric Analysis (TGA)

2.1. General Description

2.2. Types of TGA Instruments

2.3. Operating Principle and Definitions

2.4. Sources of Uncertainty

2.5. Practical Concerns

2.5.1. Material I nhomogeneity

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. Influence of Light Scattering

3.4.3. Influence 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 Efficiency of Purification and Optimization of

Purification

3.6. Frequently Asked Questions about the Capabilities and limitations of the NIR

V
Table of Contents

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 (Z

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
Introduction

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 field-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 cur- rently known SWNT synthetic techniques, generate significant 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 purification 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 purification steps is a multi-parametric task which requires the ac- curate and efficient evaluation of small changes in the purity and yield of bulk

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

purification 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 specifications.

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

refinements that have occurred in electronics grade silicon are obvious ex- amples. While it may not be possible to obtain analytically pure SWNTs, the

nanotechnology industry will benefit 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 casl
Introduction

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 efficient tool for determining the metallic impurities in SWNT material. In certain special cases the TGA technique is also capable of providing infor- mation 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 efficient 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 efficient for SWNT samples

with a naiTow 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 purification 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 first-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 tradi- tionally 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 efficiency of the bulk scale production of SWNTs by a variety of synthetic

2
Introducf

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 ofChemical 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 ofPhysical Chemistry B 108:12770-5

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

Carbon 42:1783-91

3
Thermogravimetric Analysis (TGA)

2. THERMOGRAVIMETRIC ANALYSIS (TGA)

Sivaram Arpalli and Pavel Nikolaev

NASA-DSC

2.1. General Description

Thermogravimetric analysis (TGA) is an analytical technique used to deter- mine 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) % 2 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 flow into the specimen pan compared to that of the refer- ence 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 Definitions

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

4
Thermogravimetric Analysis (TGA)

Figure 2.1: (a) TGA of purified SWCNTs; 3 specimens sampled from the same batch,

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

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 (T

o

) (Figure 2.1).

While the definition of ash content is unambiguous, oxidation temperature can

be defined in many ways, including the temperature of the maximum in the mass loss rate (dm/dT ) and the mass loss onset temperature (T ). The for- v max 7 r v onset 7 mer 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

definition, 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 difficult 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 definition of T even more difficult and ambiguous. How- onset °

ever, determining dm/dT is relatively straightforward. Therefore, oxidation

temperature is herein defined as T = dm/dT . 1 o max TGA measurement of "as-produced" nanotube material in air usually produces

only one peak in the dm/dT curve, as "fluffy" raw nanotubes oxidize rapidly in an oxygen-rich environment. However, analysis of purified nanotube material

5
Thermogravimetric Analysis (TGA)

in air may produce more than one peak. These additional peaks are likely due

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

and/or with functional groups (i.e., the material is oxidized at lower temperatures) or because purified 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 speci- mens may catalyze carbon oxidation, so the amount of metal impurity in the

sample can have a considerable influence 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) ug, 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 specifications.

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 necessar6
Thermogravimetric Analysis (TGA)

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 M and T . It is obvious that

res o standard deviations aMres and oTo 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 significant frac- tion 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 unpurified nanotubes that are "fluffy" and have more metal catalyst. It is noticed that combustion decreases M and increases J res 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.

7
Thermogravimetric Analysis (TGA)

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).

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 M and T and their 1 res o 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 unpurified ("fluffy") 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 "fluffy" nanotubes, it is difficult to place more

than 2 to 4 mg of material into a typical 200 uL 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.
Thermogravimetric Analysis (TGA)

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 sufficient 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 T and M are representative of the sample oxidation temperao res r r 1 ture and ash content. Standard deviations of T and M are representative of o res r 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 flow rate of 10 4 m3 /min (100 seem). Figures 2.1 to 2.9 were generated by this instrument. All samples were from the same batch

of as-produced ("fluffy") 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 fol- lowing 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, T , and ash content, Mres , vary in each run. Variations in T can exceed ( 1 to 20) °C, and variations in M can exceed 5 % of

the initial sample mass (i.e., these variations are quite significant 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 sufficient to produce

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

material available. It has also been noticed that nanotube materials of differ- ent properties have varying standard deviations of To (c

T

) and Mres (oM

). This

9
Thermogravimetric Analysis (TGA)

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

samples. For example, unpurified and purified nanotubes can have cT ~ 2.7 °C and aT ~ 6.5 °C respectively (5 °C/min heating rate). Therefore, aM and oT 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 unpurified SWCNT material; three specimens sampled

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

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

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

10
Thermogravimetric Analysis (TGA)

Figure 2.5: TGA graphs of an unpurified SWCNT material: three specimens sampled

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

Figure 2.6: TGA graphs of an unpurified SWCNT material: three specimens sampled

from the same batch: 10 c C/min heating rate in air.

11
Thermogravimetric Analysis (TGA)

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 unpurified SWCNT material; three specimens sampled

from the same batch; 30 °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 difficult to reliably determine To (and its standard deviation) for the experiment with a 1 00 °C/min heating rate

12
Thermogravimetric Analysis (TGA)

Figure 2.9: Heating rate dependence of oxidation temperature, To

, and its standard

deviation gTo (inset).

(Figure 2.8) due to the very broad transition with several peaks that are not re- producible (this will be discussed later). The origin of such a significant 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 significantly 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 significantly 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 confirm this by direct observation of the sample in the TGA furnace, but the

observed behavior of T and M also points in this direction. Combustion, o res r

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 re- lease in a particular run can vary significantly 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

13
Thermogravimetric Analysis (TGA)

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

* 111

|

a ' o

. *C la In

• •

i 1 1 5 1 15 20 25 30 Ramp rale, °C/m in

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

, and its standard

deviation, oMres (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-defined peaks and appear rather irreproducible, making it impossible to define

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 significant 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 in- creasing (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 purified samples

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

combustion.

14
Thermogravimetric Analysis (TGA)

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 purification,

but sometimes unpurified material is processed into buckypaper by dispersing in a solvent, filtering, and drying). The apparent density of unprocessed,

"as-is" "fluffy" material can be ( 1 to 2) orders of magnitude smaller than that of

processed material. It is difficult 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 pres- sure 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 T values. However, changes in T do not follow a uniform trend. T o ° o o 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 difficult to predict. Compaction may be necessary for some especially "fluffy" 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.

15
Thermogravimetric Analysis (TGA)

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= 1

1

3. "Application Notes on Thermal Analysis by Perkin Elmer",

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

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

4. ASTM E 1 1 3 1 - 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).

16
Near-Infrared (NIR) Spectroscopy

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 spec- troscopy 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 efficient tool to quantitatively evaluate the carbonaceous purity of bulk SWNT material (18-22). The

procedure is extremely simple, can be efficiently 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 purification 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 confinement 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).

17
Near-Infrared (NIR) Spectroscopy

Semiconducting SVWTs Metallic SV\NTs

DOS(au.) DOS(au.)

Figure 3.1: Electronic density of states (DOS ) of semiconducting and metallic SWNTs

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 S n = 2ap/d and S22 = 4ap/d,

while the metallic SWNTs show their first transition at Mn =6a(3/d, where a is carbon-carbon bond length (nm), p is the transfer integral between p7i-orbitals

(P ~ 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 SI 1, S22 and Mil features are simultaneously present in the electronic

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

finite SWNT diameter distribution (2, 3, 5, 7, 8). NIR optical absorption spec- troscopy can capture these specific 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 dominates
ed by the 7i-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 7i-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 S u transition is the most prominent, we chose the second semiconducting transition (S

22 , inset to Figure 3.3), for the purity evaluation because the

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

Frequency (cm ') 8000 9000 10000 11000

10 10000 20000 30000 40000 Frequency (cm"1

)

Figure 3.2: Schematic illustration of the optical spectrum of typical SWNT sample pro- duced 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).

19
Near-Infrared (NIR) Spectroscopy

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 efficient solvents for dispersing both raw and purified SWNT

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

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

We have identified 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 1 1750) cnr

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 ofAP-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 refine 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) cnr 1 . i.e. (1000 to 25 000) nm, whereas UV-Vis (Visible) spectropho- tometers 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 M;] 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 to 19 000) 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-pre- pared 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):

20
Near-infrared (NIR) Spectroscopy

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

fine 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 final test sample improves the

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

the dispersion and lead to significant light scattering and thereby compromise

the results of the purity evaluation.

For purified 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 purified SWNT material into a fine powder.

3.3.3 Practical example of spectral measurements and relative

purity calculations

The SWNT sample should be ultrasonicated just before the spectral measure- ment 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 Mn 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 significantly more curvature and are more difficult to analyze.

21
Near-Infrared (NIR) Spectroscopy

RP=(40/662)/0.141=43%

Figure 3.3: Practical procedure for determination of relative purity (RP) ofAP-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 %

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 fitting

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.

22
Near-Infrared (NIR) Spectroscopy

0.15 - 8000 9000 10000 11000 12000 Frequency (cm

1 )

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.

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 films.

23
Near-Infrared (NIR) Spectroscopy

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 five independent 50 mg probe samples from the same mechanically homogenized 10 g batch ofAP-SWNT material using the

recommended procedure. ( 18-20) The results of the NIR relative purity measurements are presented in the Figure 3.5. The five probe samples show an average relative purity of 46 % with a standard deviation of 3.0 %, which cor- responds 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 five independent probe samples obtained from 10 g AP-SWNT sample;

b) Calculated purity of the five probe samples

3.4.2 Influence 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 (k). 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

24
Near-Infrared (NIR) Spectroscopy

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)

um and this is comparable with the wavelength of light in vicinity of the S22 interband transition (X ~ 1 um) that is utilized for purity evaluation. In this circumstance (d ~ X) Mie scattering is expected to dominate,(19) and this scat- tering mechanism becomes more important as the particle size increases (d > X) In the spectral range of interest there is a crossover between X > d and X < d,

and this makes it difficult to theoretically estimate the influence 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.

o.o 8000 12000 16000

Frequency (cm 1 ) Figure 3.6: Solution phase absorption spectra of a SWNT sample collected with the spectrophotometer in regular transmission configuration (gray curve) and using an inte- grating 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 significant 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 configurations

for the collection of light (20). The introduction of the integrating sphere col- lection leads to a small decrease in the level of the baseline, and the calculated

25
Near-Infrared (NIR) Spectroscopy

relative purities were found to be RP = 63.8 % in regular, and RP = 61 .7 % in the integrating sphere configurations; Table 1 shows a comparison for three

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

when measured in the regular configuration 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 configuration, although the

deviations are within the experimental accuracy of our technique (1 8-20). This

Table 1. Measured NIR Purity with Spectrophotometer in Regular and

Integrating Sphere Configuration

Sample Number 1 2 3

Regular Configuration 20.5 % 38.5 % 63.8 %

Integrating Sphere 16.5 % 35.5 % 61.7 %

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 fcr 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 difficult to control scattering in the case of SWNT

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

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

relative purity evaluation studies.

3.4.3 Influence 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 difficult 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 ofAP-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.

26
Near-Infrared (NIR) Spectroscopy

0.02 0.04 Concentration (mg/mL)

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.

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 confirms 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 five Y

concentrations between (0.25 and 8) atom % .

27
Near-Infrared (NIR) Spectroscopy

0.02 wCD 0.00

CDo

(5 0.2

0.1

0.0L

(d)

Y =0.25 at% Y =0.5 at% Y =1.5 at% Y =4.0 at%

Ni=4.0at% Ni=4.0at% Ni=4.0at% Ni=4.0at%

8000 10000 8000 10000 8000 10000 Frequency (cm

1 )

8000 10000 8000 10000

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.

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 efficient 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 efficiency of purification and optimization of

purification parameters

An important application of a purity evaluation technique is the ability to ef- ficiently monitor and optimize the parameters of purification processes. (3 1-33)

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

final purified product obtained by oxidation ofAP-SWNTs in air followed by

treatment with hydrochloric acid. According to the NIR evaluation procedure

28
Near-Infrared (NIR) Spectroscopy

0.05 8

c o.oo

03 _Q^ 0.2

0.1

0.0

(a)

AP-SWNTs

8000 9000 10000 11000 8000 9000 10000 11000 Frequency (cm"

1 )

Figure 3.9: NIR evalution of efficiency of purification procedure. NIR spectra in the range of the SWNT S22 interband transition for: (a) starting (AP) sample (NIR RP=50

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

band after linear baseline subtraction.

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

purification (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 purification 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)] x Y, where RP(P-SWNT) and RP(AP-SWNT)

are the relative purities of the as-prepared and purified 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 = [Mfin x (l-METfin )]/[M

st x (1-METJ],

where Mst (Mfin ) and MET t (METfin ) are the sample mass and the fraction of

metal, respectively, in the starting material (final product). For example, in the purification procedure ofAP-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 purification Mfin = 2.5 g, RP(P-SWNT) = 93 % and METfin = 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 purification process. Each step of a

29
Near-Infrared (NIR) Spectroscopy

purification procedure can be evaluated and optimized on the basis of NIR rela- tive purity and PRF figure of merit (31-33) taking into account that the ideal purification 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 purified 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 S

n , S22 and Mu 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 significant

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.

30
Near-Infrared (NIR) Spectroscopy

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 nar- rower than that of most CVD-produced SWNTs. In the optical spectra of HiPco

material, the S

n , S20 and Mn 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 fit might be more accurate?

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

easily applicable and consistent purity evaluation procedure without any fitting

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

The NIR purity evaluation procedure implicitly assumes that the extinction coefficients 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

coefficients 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 coefficients of

SWNTs and carbonaceous impurities are identical. If the extinction coefficient

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 coefficient

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

impurities (27, 28).

31
Near-Infrared (NIR) Spectroscopy

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 S

22 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 purified (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 film instead of solution phase spectroscopy?

Thin film spectroscopy has been extensively used in SWNT research. Some

types of SWNTs are very difficult to disperse, especially long SWNTs or purified SWNTs after high temperature annealing in vacuum. In this case some

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

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

37), but we found it more difficult to obtain reproducible AA(S)/AA(T) ratios, that the results were somewhat dependent on the thickness of the film and that

it is not trivial to obtain homogeneous non-scattering films (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 film, so it is important to be consistent in the use of either solution phase or

thin film 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 indi- vidual 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 first ap- proximation we do not expect that debundling and the resultant change of the

32
Near-Infrared (NIR) Spectroscopy

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 Sll, S22 and Mil

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

singularities, but are rather exciton bands due to the strong coupling of elec- trons and holes in the ID-system (39, 40). This issue is not finalized 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.

References

1. Chen J, Hamon MA, Hu H, Chen Y, Rao AM, et al. 1998. Science 282: 95-8

2. Kataura H, Kumazawa Y, Maniwa Y, Umezu I, Suzuki S, et al. 1999.

Synth. Met. 103: 2555-8

3. Petit P, Mathis C, Journet C, Bernier P. 1999. Chem. Phys. Lett. 305: 370-4

4. Chen J, Rao AM, Lyuksyutov S, Itkis ME, Hamon MA, et al. 200 1 . J. Phys. Chem. B 105: 2525-8

5. Hamon MA, Itkis ME, Niyogi S, Alvaraez T, Kuper C, et al. 2001 . J. Am.

Chem. Soc. 123: 11292-3

6. Niyogi S, Hamon MA, Hu H, Zhao B, Bhowmik P, et al. 2002. Acc. Chem.

Res. 35: 1105-13

7. Itkis ME, Niyogi S, Meng M, Hamon M, Hu H, Haddon RC. 2002. NanoLett. 2: 155-9

8. Hennrich F, Lebedkin S, Malik S, Tracy J, Barczewski M, et al. 2002.

Phys. Chem. Chem. Phys. 4: 2273-7

9. Kazaoui S, Minami N, Jacquemin R, Kataura H, Achiba Y. 1999. Phys.

Rev. £60: 13339-42

10. Kazaoui S, Minami N, Matsuda N, Kataura H, Achiba Y. 2001. App. Phys.

Lett. 78: 3433-5

1 1 . Hennrich F, Wellmann R, Malik S, Lebedkin S, Kappes MM. 2003. Phys.

Chem. Chem. Phys. 5: 178-83

33
Near-Infrared (NIR) Spectroscopy

12. Kamaras K, Itkis ME, Hu H, Zhao B, Haddon RC. 2003. Science 301

:

1501

13. Hu H, Zhao B, Hamon MA, Kamaras K, Itkis ME, Haddon RC. 2003. J. Am. Chem. Soc. 125: 14893-900

14. Jost O, Gorbunov AA, Pompe W, Pichler T, Friedlein R, et al. 1 999. App.

Phys. Lett. 75: 2217-9

15. Jost O, Gorbunov AA, Moller J, Pompe W, Lui X, et al. 2002. J. Phys.

Chem. B 106: 2875-83

16. Itkis ME, Perea D, Niyogi S, Love J, Tang J, et al. 2004. J. Phys. Chem. B

108: 12770-5

17. Jost O, Gorbunov AA, Liu X, Pompe W, Fink J. 2004. J. Nanosci. Nanotech. 4: 433-40

18. Itkis ME, Perea D, Niyogi S, Rickard S, Hamon M, et al. 2003. Nano Lett. 3:309-14

19. Haddon RC, Sippel J, Rinzler AG, Papadimitrakopoulos F. 2004. MRS Bulletin 29: 252-9

20. Itkis ME, Perea D, Jung R, Niyogi S, Haddon RC. 2005. J. Am. Chem. Soc. 127: 3439-48

21. Krestinin AV, Kislov MB, Ryabenko AG. 2004. J. Nanosci. Nanotech. 4: 390-7

22. Ryabenko AG, Dorofeeva TV, Zvereva GI. 2004. Carbon 42: 1523-35

23. Saito R, Fujita M, Dresselhaus G, Dresselhaus MS. 1992. Phys. Rev. B 46:

1804-11

24. Mintmire JW, Dunlap BI, White CT. 1992. Phys. Rev. Lett. 68: 631-4

25. HamadaN, Sawada SI, Oshiyama A. 1992. Phys. Rev. Lett. 68: 1579-81

26. Dresselhaus MS, Dresselhaus G, Eklund PC. 1996. Science ofFullerenes

and Carbon Nanotubes. San Diego: Academic

27. Zhao B, Itkis ME, Niyogi S, Hu H, Zhang J, Haddon RC. 2004. J. Phys.

Chem. B 108: 8136-41

28. Zhao B, Itkis ME, Niyogi S, Hu H, Perea D, Haddon RC. 2004. J. Nanosci.

Nanotech. 4: 995-1004

29. Lebedkin S, Hennrich F, Skipa T, Kappes M. 2003. J. Phys. Chem. B 107: 1949-56

30. Journet C, Maser WK, Bernier P, Loiseau A, Lamy de la Chappelle M, et

al. 1997. Nature 388: 756-8

31. Sen R, Rickard SM, Itkis ME, Haddon RC. 2004. Near-IR Spectroscopy

as a Tool to Monitor the Purification ofSingle-Walled Carbon Nanotube

Films by Thermal Oxidation. Presented at Proceedings of the NATO

Advanced Study Institute on Organic Conductors, Superconductors and

Magnets: From Synthesis to Molecular Electronics, Corfu, Greece

32. Hu H, Zhao B, Itkis ME, Haddon RC. 2003. J. Phys. Chem. B 107: 13838-

42

34
Near-Infrared (NIR) Spectroscopy

33. Hu H, Yu A, Kim E, Zhao B, Itkis ME, et al. 2005. J. Phys. Chem. B 109:

11520-4

34. Kim Y, Luzzi DE. 2005. J. Phys. Chem. B ASAP

35. Resasco DE, Herrera JE, Balzano L. 2004. J. Nanosci. Nanotech. 4: 398-

407

36. Zheng M, Jagota A, Strano MS, Santos AP, Barone P, et al. 2003. Science

302: 1545-8

37. Sen R, Rickard SM, Itkis ME, Haddon RC. 2003. Chem. Mater. 15: 4273-9

38. O'Connell MJ, Bachilo SM, Huffman CB, Moore VC, Strano MS, et al. 2002. Science 297: 593-6

39. Ando T. 1997. J. Phys. Soc. Japan 66: 1066-73

40. Spataru CD, Ismail-Beigi S, Benedict LX, Louie SG. 2004. Phys. Rev. Lett. 92: 077402

35
Raman Spectroscopy

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-specific phonon

mode energies (1,2). It requires very little sample preparation and a rapidnon-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= E]ase ± hf2 for Stokes (-) and Anti-Stokes (+) scattering respectively, with Q. 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 scatter- ing 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 stan- dard 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 1owt fre- quency, radial breathing modes (RBM) and the higher frequency, D, G and G'

modes (to be defined 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

36
Raman Spectroscopy

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.

Figure 4.1. Raman spectra of carbon nanotubes

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

confined 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 E. with i=l,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 E.. is roughly proportional to 1 /diameter

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

plot.

37
Raman Spectroscopy

Exciton versus band edge resonance

It has recently been demonstrated experimentally that optical transitions in nanotubes between the van Hove singularities are modified by electron-hole

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

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

edge absorption E.. to the exciton absorption energy, E..- Ebindjng

. While this has

far-reaching consequences for optically generated transport measurements, it does not significantly 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 E... For simplicity, we will continue

to refer to the optical transition energies as E.. 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

sufficiently. Examples of how the resonance energy changes for individual

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

Resonance Raman profile

Scanning the laser energy through an optical resonance gives the resonance

excitation Raman profile for a given carbon nanotube phonon mode. Unlike

photoluminescence excitation profiles where the center of the profile coincides

with the optical transition E..5 the Raman excitation profiles have two contributions; electronic resonance with the incoming laser light, ( E laser= E..), and

electronic resonance with the scattered light, which is shifted by a phononenergy: E = E, ± hQ. = E . Hence, the center of the resonance profile is lDJ scattered laser 11 r

E.. ± hQ/2.

38
Raman Spectroscopy

Excitation energy (eV)

Figure 4.2. Resonance excitation profile. The curves show the Stokes (red) and Anti- Stokes (blue) resonance excitation profiles for (9,4) individual nanotubes with RBM = 257cm-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 confirming the presence of nanotubes in a sample. Below, each

Raman-active mode will be discussed further.

39
Raman Spectroscopy

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 Aj and it is often called the "breathing" mode. The RBM frequency (©) is inversely proportional to the nanotube diameter with the relation

©(cm 1 ) = ^/dia(nm) + ^(cm' 1 ) where the constants A and B have been determined experimentally with A= 223

cm'Vnm, B=10 cm 1. Several groups have found slightly different best fits of A

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

grating spectrometer with a holographic notch filter 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) (1 1-14). Knowledge of the diameter and resonance energy E.. makes it possible to separate the RBM signatures of metallic tubes

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

65 2 00

180 200 220 240 260 280 300 320 340 360 380 RBM Frequency (cm 1 ) 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 identified. 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). 40
Raman Spectroscopy

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 E

and E„ semiconducting and En metallic transitions (15). While it is possible

to pair RBM frequencies with E. obtained from full Raman excitation profiles

to arrive at a nearly unambiguous chirality assignment for a specific 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 specific 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 confinement of

wave-vectors along the circumference. For

chiral tubes, the G-band is composed of six modes with symmetries A]a , E] and E2 (two

of each). The frequency of the higher en- ergy 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

HOPG J

^1582

\ 1582 MWNT

SWNT

semicond. 1570 Gr

j\l592 G

+

metallic SWNT

' G"

1550

I\1587

\ G+

1450 1550 1650 Frequency < cm" > Figure 4. 4. From (16). G bands

for graphite (HOPG), multiwall CNTs (MWNT), semiconducting and

metallic SWNTs.

41
Raman Spectroscopy

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

even in a bundle for defect-free nanotubes (FWHM ~ 1 1 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 elec- trons 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 as- signment 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).

1600

1580 £

1560

1540

cr

<Di_ LL 1520

1500

!'!'!'

• n :

Jfi. metallic ! \/

semiconducting 0.2 0.4 0.6 0.8

1/d

t (1/nm)

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 elasti- cally 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.

42
Raman Spectroscopy

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 fre- quency is not fixed for different laser energies. Table 4. 1 gives approximate

values for four different laser lines. The D band is present in all carbon allo- tropes, including amorphous sp

2 and sp3 carbon. The D band signal can origi- nate 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 amor- phous 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.

43
Raman Spectroscopy

The G' Band: The G' band at frequencies (2500 to 2900) cnr 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 coG

. ~ 2420 cm '+105 cm 1 / E)aser (eV).

2600 2700 2800

Raman shift (cm

-1

) 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 E..'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).

44
Raman Spectroscopy

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 E.., 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 y. Ensemble measurements (11-14)

Solution: The broadening y has been measured to be y ~ 60 meV for nanotubes dispersed in sodium dodecyl sulfate solution.

• Bundles: For nanotubes in thick bundles the broadening is y ~ 120 meV.

Individual measurements (15)

For (nearly) individual nanotube measurements suspended in air or on

substrates, the width y varies from y = ( 1 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 litera- ture. 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 E.. is active. For semiconducting nanotubes, the

Raman scattering cross-section is proportional to

where the constants a and b depend on which electronic energy level E.. is excited, u 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).

+n ——^cos 3q

d; d.

45
Raman Spectroscopy

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 cos

4 9, where 6 is the relative angle between the electric

field, 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 field vector parallel to the nanotube axis, E , does not induce a polarization, and

the total field is equal to the external field. On the other hand, an electric field perpendicular to the nanotube axis, Ejl, induces charges on the two opposing

sides of the wall. The effect is a large opposing depolarization field that reduces

the external field Ex. The antenna effect is a strong effect for narrow nanotubes

<2 nm. The resonance with the E.. transition for light polarized parallel to the nanotube

axis is due to angular momentum conservation which requires Am=0 for E

where m is the angular momentum quantum number. For a perpendicular field E± the angular momentum conservation requires Am=±l, i.e., E.. with j= i±l. Due to the depolarization effect, E transitions are favored over E transitions. r ' 11 ij 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) fixed 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 filters 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. 46
Raman Spectroscopy

Calibration and Alignment

If several laser lines are used it is necessary to re-align optical paths and cali- brate 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 ef- ficiency 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 specific power for comparison.

1200 1300 1400 1500 1600 1700 Raman Sift (cm1 ) Figure 4. 7. G band

from powder and from

individual nanotube on

substrate. Heating ef- fects 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.

47
Raman Spectroscopy

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, sufficient 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 significant 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, fre- quency shifts of the G

+ mode with temperature from (-0.022 to -0.048) cnrVK

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 Elase ±E.. at Tj 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/I

S 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 significantly less than a dry powder/ bundles in air, and individual nanotubes on a

substrate are also efficient 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.

48
Raman Spectroscopy

We recommend using < 3 x 105 W/cm2 for samples in solution and for indi- vidual 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 influence

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 filter 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 1 10,000 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 dodecylben- zene 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.

49
Raman Spectroscopy

- 11500 12000 12500| 13000 13500 14000 14500

Excitation Energy (cm1 ) Figure 4.8. Comparison of Raman

excitation profiles of SDS solubilized and

bundled nanotubes for the (12,1) and

(10,2) chiralities. The vertical line repre- sents the 785 nm excitation line position.

Solution Roped

Raman Shift (cnr 1 ) Figure 4.9. Comparison of RBM spectra

for SDS solubilized and bundled nanotubes at four specific excitation wavelengths.

4.6 Appendix

4.6.1 Illustration of Aggregation Effects

As noted above, sample state and environment will have a significant effect on

features observed in SWNT Raman spectra, particularly in the RBM region.

These effects are primarily due to shirting and broadening of the electronic

transitions. These effects are most pronounced in comparing solution to ag- gregated samples. Figure 4.8 illustrates the significant red-shifting and broadening of excitation profiles 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 elec- tronic 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

50
Raman Spectroscopy

brings a different set of chiralities into resonance with a specific 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 profile 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 significant intensity in the tail of the (12,1) profile 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.

51
Raman Spectroscopy

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 cnr'/K.

Subsequent cycles of increasing and decreasing the optical powers show a less marked heating than the first 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 profiles,

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.

< Position Along Trench (jirni Position Along Trench (jam) 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 profile at the focal plane using a nanotube.

52
Raman Spectroscopy

Knowing the resolution of the spectrometer, detector pixel size, and the overall magnification 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 4.1 1 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" configuration also provides an elegant method for directly

measuring the profile 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 ofMaterials 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 ofPhysics Letters 409:47-99

53
Raman Spectroscopy

1 1 . Doom SK, Heller DA, Barone PW, Usrey ML, Strano MS. 2004. Applied

Physics A-Materials Science & Processing 78: 1 147-55

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 ofSelected Topics in Quantum Electronics 12:1083-90

16. Jorio A, Pimenta MA, Souza AG, Saito R, Dresselhaus G, Dresselhaus

MS. 2003. New Journal ofPhysics 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. Doom SK, Zheng LX, O'Connell MJ, Zhu YT, Huang SM, Liu J. 2005.

Journal ofPhysical 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

2 1 . Souza AG, Jorio A, Swan AK, Unlu MS, Goldberg BB et al. 2002. Physical Review B 65:

22. Goupalov SV, Satishkumar BC, Doom 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, Doom SK. 2006. Applied Physics Letters

88:

54
Optical, Electron and Probe Microscopy

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 final nanotube polymer composites to the nanostructure. This guide outlines the tools and the procedures used to assess

the dispersion of nanorubes 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 nanorubes

into improved composite structure performance is the difficulty 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 poly- mer 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 first 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 aggre55
Optical, Electron and Probe Microscopy

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 sufficient to state that the sample does not have any visual aggregation on

the scale of approximately 1 um or larger. To assess the aggregation, bundling,

alignment, and local concentration gradients on a scale below 1 um requires

electron and probe microscopy techniques. These techniques include scanning

electron microscopy (SEM), transmission electron microscopy (TEM), and

scanning probe microscopy (SPM). Defining the quality of the dispersion on a

scale below 1 um 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 lo- cal concentration gradients on the scale below 1 um. 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 quantifiable 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 spec- trum to generate a micrograph. Illumination of the samples above or below the

sample determines the imaging mode, either reflection or transmission respectively. Ultraviolet illumination, polarizers, bright field/dark field imaging and

optical filters 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

efficiency 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 chemi56
Optical, Electron and Probe Microscopy

cal identification. 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 filtered 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 fol- lowing 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 field 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 field to record the topography, magnetic

field, electric field and tunneling current and current flow 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.

57
Optical, Electron and Probe Microscopy

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 poly- mer due to vastly different optical properties of the nanotubes and the host

polymer. In either transmission or reflection the dispersion of the nanotubes on

a large scale greater than 1 urn 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 field 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 field to a less negative potential. If the

electric field is stable, the percolation network can be imaged. Nanotubes dis- rupt the field 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 fila- ments in the image. This is shown in Figure 5.3 where SWNTs penetrate into a film 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 field artifact will be overlaid on

the secondary electron image. This explanation is consistent with the theory of

electric field 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 filtering 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

filtered TEM (EFTEM) and electron energy loss spectroscopy (EELS) techniques (15).

58
Optical, Electron and Probe Microscopy

In the SPM techniques contrast is generated by the paramagnetic and electrical behavior of the SWNTs (16). Direct imaging of SWNT bundles and even indi- vidual 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 fixed 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 flow 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 film 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 magnification is recom- mended. Agglomerations on a scale large than 1 urn are easily visible with this technique. If the sample is not transparent, illumination via reflection does give some indication of the large-scale dispersion but the sample will need to be ex- amined 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.

59
Optical, Electron and Probe Microscopy

Sample 2 is considered "optically dispersed." If the composite does not need

further optimization for the intended application, optical characterization is usually sufficient. However, if optimization of mechanical, electrical, or ther- mal 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 jim scale. The main tool employed in this investigation is the high resolution FE-SEM (HR-FESEM). This tool creates a stable electric field in most

polymers and generates a very high collection efficiency 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 film surface and in cross-section. Aggregates and an inhomogeneous distribution are visible in the film 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 with- out 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.

60
Optical, Electron and Probe Microscopy

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-filament SEMs are more than capable of imaging such networks as shown in Figure 5.5. Typically, great efforts are employed to reduce the pres- ence of such image artifacts, as those arising from a charge build-up that generates a large electric field. However, for these studies the electric field 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 magnification. It was observed that the tubes were not locked into a single rope-like

configuration, 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 field at a fixed 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 cantile- vers (~ 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

61
Optical, Electron and Probe Microscopy

population, disrupt the local magnetic field from the strong magnet under the

sample. These nanotubes are imaged with the MFM in an interleave mode. The

sample topography is first scanned and then the probe is raised a fixed distance,

typically (7 to 15) nm, above the surface and the magnetic field gradient is then recorded. These small lift heights require that the sample be relatively flat before imaging. Thin films formed by spin casting or knife coating work best. The TUNA procedure requires the use of a conductive AFM probe. The restric- tions 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 ex- amination 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 first determine if SWNT dispersion is poor. Second, the

SEM is used on the composite surface and cross-section to determine bulk dis- persion. 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 beneficial for composites

with limited conductivity or samples susceptible to significant 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- 1-0203 7 for

partial support.

62
Optical, Electron and Probe Microscopy

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 2002-21 1940

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 PA 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. SEMAnnual

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 andX-Ray

Microanalysis 3

rd 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.

63
Optical, Electron and Probe Microscopy

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 film. Nanotubes that are penetrating out of the cross-section generate their own secondary electrons and appear as bright filaments in the image. The arrows highlight points where the nanotubes

penetrate into the polymer and disrupt the electric field in the surrounding poly- mer. 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) cross- section of sample 3 showing an improved dispersion from using the (3-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

field artifact contrast as seen with the HR-FESEM.

Figure 5.6. TEM of SWNT-CP2 directly showing individual tubes in the poly- mer matrix.

Figure 5.7. Scanning probe microscopy images complementary to electron

microscopy of 2 SWNT-0-CN composites (a-c: 0.5% SWNT (3-CN, d-f: 2%

SWNT P-CN). (a,d)Topography, (b,e) MFM images and (c,f) TUNA images.

64
Optical, Electron and Probe Microscopy

Figure 5.1 Composite preparation

Process improvement / optimization

Optical microscopy Correct issue(s) causing poor dispersion

No or Unknown

Electron and

probe

microscopy on

surface and

cross-section

Determine reason for lack of dispersion. Use

microscopy,

spectroscopy, and other necessary test methods.

£

Assess the bundle size, presence of

igglomerates, and local concentration gradients

to fully characterize the dispersion

Yes

Yes

Design experiments to determine reason for lack of dispersion

Figure 5.1. Guide to assess the dispersion of SWNT in polymer matrices.

65
Optical, Electron and Probe Microscopy

Figure 5.2

Figure 5.2. Optical micrographs: (a) undesirable dispersion with SWNT aggregates, (b) desirable uniform SWNT dispersion (optically dispersed) in a polyimide matrix.

66
Optical, Electron and Probe Microscopy *

Figure 5.3. HR-FESEM images of a SWNT-CP2 composite in cross-section showing

the SWNTs penetrating out of the film. Nanotubes that are penetrating out of the cross- section generate their own secondary electrons and appear as bright filaments in the image. The arrows highlight points where the nanotubes penetrate into the polymer and

disrupt the electric field in the surrounding polymer. The contrast is then reversed and

the nanotubes appear as dark regions against the bright polymer matrix.

67
Optical, Electron and Probe Microscopy

Table 5.1 Sample

Sample 1 1% SWNT

CP2

Sample 2 1% SWNT

CP2

Sample 3 0.5% SWNT

|3-CN

Sample 4 0.5% SWNT

|3-CN

Mixing

Conditions

Direct Mix

In-situ polymerization under

sonication

In-situ polymerization

with HiPco

SWNT

In-situ polymerization

with laser ablation SWNT

Optical Microscopy

Table 5.1. Optical microscopy images of samples 1-4.

68
Optical, Electron and Probe Microscopy

Figure 5.4

^^T^ff"liyT!?^T5JMBMlllE?Slll

S-52O0 1 .»V0.1mmx5(X» SE 8/2&03 lOOum

J

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 fi-CN polymer. Dispersion is still not ideal due to poor quality

ofSWNT. (g) Surface and (h) cross-section of sample 4 showing nearly 100 % dispersion, no visible aggregates, very small bundles, and no resin rich areas.

69
Optical, Electron and Probe Microscopy

Figure 5.5

1.8kU XI, 09.0 10Mm 0800 JSM-5600

Figure 5.5. SEM image of a SWNT-CP2 composite showing the same electric field arti- fact contrast as seen with the HR-FESEM.

70
Optical, Electron and Probe Microscopy
Optical, Electron and Probe Microscopy

Figure 5.7

Figure 5. 7. Scanning probe microscopy images complementary to electron microscopy of 2 SWNT-P-CN composites (a-c: 0.5% SWNT (3-CN, d-f: 2% SWNT(S-CN). (a,d)Topography (b,e) MFM images and (c,f) TUNA images.

72



March 2008