International Journal of Hydrogen Energy 29 (2004) 1487–1491www.elsevier.com/locate/ijhydene

A quantitative method for characterization of carbon nanotubesfor hydrogen storage

Arindam Sarkar, Rangan Banerjee∗

Energy Systems Engineering, Indian Institute of Technology, Mumbai 400076, India

Accepted 3 February 2004

Abstract

Carbon nanotubes are considered to be a promising option for hydrogen storage. However, there is a wide variation in thehydrogen storage capacity of CNT’s reported by di5erent researchers. Hydrogen storage depends on many factors, the diameterbeing one of them. Also for repeatability and development of a viable storage system, control of diameter is necessary duringthe formation process. A technique involving digital image processing has been developed that can be used to determine thedistribution of diameter of carbon nanotubes. The nature shows a distribution similar to a random distribution that may helpin characterizing nanotube samples. The use of image processing and statistical analysis can help in developing better CNTs.? 2004 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved.

Keywords: Carbon nanotube; Characterization; Hydrogen storage

1. Introduction

Carbon nanotubes have generated a lot of interest as ameans to store hydrogen. However, the experimental resultsreported by di5erent researchers show wide variation andpoor repeatability [1]. One of the possible reasons for thismay be improper characterization of nanotubes. The hydro-gen storage capacity of carbon nanotubes depends upon pa-rameters like the diameter of tubes, spacing between tubes,whether they are multi walled or single walled and thealignment. Most of the carbon nanotube samples reportedin literature generally contain a mixture of open and closedsingle-walled and multi-walled tubes with various diame-ters and include other forms of carbon like amorphous car-bon nano-?bers, etc. and catalyst particles. It is di@cult toseparate out the impacts of di5erent parameters from theresults. One parameter that a5ects the hydrogen storage ca-pacity is the tube diameter. Visual inspection of the SEMand TEM images is normally used to determine the type of

∗ Corresponding author. Tel.: +91-22-2572-2545; fax: +91-22-2572-6875.

E-mail address: rangan@me.iitb.ac.in (R. Banerjee).

nanotubes and to verify the structure. This paper proposes aquantitative methodology to analyze the distribution of di-ameter from the SEM and TEM images using image process-ing and statistical analysis. This method is illustrated usingfew case studies from literature. It is expected that adoptionof the proposed method will help in a better understandingof carbon nanotubes and their hydrogen storage capability.

2. Literature review

Since the discovery of carbon nanotubes by Iijima [2],it has found applications in various ?elds. Dillon et al.[3] reported for the ?rst time excellent storage capacityof single-walled carbon nanotubes (SWNT). The nanotubesamples were prepared by co-evaporation of Co (cobalt)and graphite in an electric arc. The hydrogen capacity wasmeasured by temperature programmed desorption and thestorage capacity was reported to be between 5% and 10%at room temperature. However, the sample contained onlyabout 0.2% SWNT by mass with the remaining being amor-phous carbon, carbon nano-particles and catalyst particlesthat were considered inert to hydrogen adsorption.

0360-3199/$ 30.00 ? 2004 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved.doi:10.1016/j.ijhydene.2004.02.003

1488 A. Sarkar, R. Banerjee / International Journal of Hydrogen Energy 29 (2004) 1487–1491

Liu et al. [4] reported a storage capacity of 4.2% bymass for SWNT (50% pure) prepared by arc discharge ofwhich almost 80% is recoverable at 298 K and 12 MPapressure.

Chen et al. [5] reported a storage value of 20% by mass at200–400 K and pressure of 0:1 MPa for Li(lithium) dopedmulti-walled carbon nanotubes (MWNT) and 14% at 300 Kand 0:1 MPa for K (potassium) doped MWNT. However,Yang [6] concluded that the abnormally high values obtainedare due to the presence of moisture in hydrogen that formedhydroxides and estimated the correct values to be 2.5% and1.8%, respectively, for Li- and K-doped nanotubes, respec-tively. He further concluded that for the purpose of storinghydrogen, alkali-doped nanotubes are better than undopedones.

Li et al. [7] prepared MWNT samples both by Moatingcatalyst and seeded catalyst and found that the storage ca-pacity of samples prepared by heat treated Moating catalystmethod is higher than the seeded catalyst samples by a factorof ?ve. Ritschel et al. [8] tested di5erent nanotubes samplesand reported a value of 0:63 wt% at 300 K and 4:2 MPa forSWNT samples of 90% purity. For MWNT they reported avalue of 0.05% at 300 K and 45 MPa.

Zuttel et al. [9] tested di5erent commercially availablesamples of SWNT and MWNT and found the maximumvalue of 0.9% for 50% pure SWNT samples and 0.13% forMWNT. They also observed that di5erent batches of sam-ples from the same manufacturer showed signi?cant di5er-ences in their adsorption capacity.

Wu et al. [10] found that the size of nanotubes can becontrolled by adjusting the composition of the catalyst.They prepared nanotubes by catalytic decomposition of CO(carbon monoxide) and CH4 (methane). The catalyst usedwas a mixture of Co and La (lanthanum). The adsorptioncapacity for nanotubes prepared from CO was found tobe 0.26%.

The wide variation of hydrogen storage capacity high-lights the need for a robust characterization technique thatcan capture some physical parameters. Characterization ofnanotubes is inherently di@cult because the interpretation ofSEM or the TEM images is mainly subjective. Also, therecan be several characterizing techniques based on di5erentparameters. The paper presents a characterization techniquebased on diameter.

3. Proposed methodology

Hydrogen storage capacity is a function of several param-eters like the tube diameter, alignment, length of nanotubes,and structure (multi-walled or single-walled, open or closedtubes). If the variation of storage capacity with di5erent pa-rameters can be quanti?ed it would help in predicting thestorage capacity and remove some of the ambiguities in theexperimental results.

Fig. 1. Proposed methodology for image processing of nanotubeimages.

Since the formation of nanotubes is a complex processand depends on many factors, it is expected that in any pro-cess the nanotubes produced will have a range of diameters.However, if the process parameters like the catalyst particlesize and operating variables are controlled, most of the nan-otubes are likely to be within a narrow range of diameters.The distribution of diameters is expected to reMect this. Ahigh-purity sample is expected to have a narrow range ofdiameters. Further, it is expected that the mean and rangeof the distribution will depend on the operating conditions.SEM and TEM pictures can serve as a good tool to ?nd thediameter distribution.

To analyze the SEM and TEM images and to get thedistribution of diameters, a semi-automated digital imageprocessing techniques have been used. The technique ofdigital image processing is routinely used to determine thedistribution of particle sizes [11]. Fig. 1 shows the basicmethodology.

Since there is a change in the gray scale values at theboundary of nanotubes, two such successive changes canhelp determine the diameter. Generally a SEM of TEM im-age has various distortions and noises that can be removedby ?ltering the image. To remove random noises a median?lter, that works best for such noises, was used. Further,to enhance the boundaries and sharpen the image Laplacian?lter was used. The diameters were determined by obtain-ing the distance between the coordinates of the pixels thatde?ne the boundary. Finally, histogram plotting was done.The programming was done in MATLAB.

It may be noted that digital image process is a powerfultechnique and can be used to ?nd other parameters as well.

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Some of the parameters that can be determined are

(1) The average length.(2) The fraction of area covered by nanotubes of the area

of the image or the density of nanotubes.(3) The alignment and the orientation.

All of them may have a bearing on hydrogen storagecapacity. This paper illustrates diameter distributions.Similar techniques could be developed for the otherparameters.

4. Results

Figs. 2 and 3 show, respectively, the TEM image andthe diameter distribution for nanotube samples preparedby Wu et al. [10]. These were prepared by the catalyticdecomposition of CH4 over a mixture of Co and Lacatalyst.

Figs. 4 and 5 show the diameter distribution of nanotubeprepared by the same researchers but varying the catalystcomposition [10].

Figs. 6–9 show the nanotube prepared by Hernadi et al.[12] with Co on silica and zeolite, respectively, along withtheir diameter distribution.

The mean diameters of the samples chosen for our anal-ysis are in the range of 5–10 nm (Figs. 4 and 6) and 15–20 nm (Figs. 2 and 8). These samples have higher diam-eters than some of the CNTs reported in the literature (2–5 nm) [2].

Fig. 2. TEM image [10].

0 10 20 30 40 50 600

5

10

15

20

25

Standard deviation (σ ) =3.8595 nm

Mean (µ ) =16.3674 nm

Ratio (σ/µ) =0.23581

Distribution

Per

cent

age

of n

anot

ubes

Diameters in nm

Fig. 3. The diameter distribution of Fig. 2.

Fig. 4. TEM image [10].

5. Conclusions

From studying the distributions following conclusionsmay be drawn.

(1) There is a range in which nanotubes seem to be formingthat may be because of the catalyst or the operating

1490 A. Sarkar, R. Banerjee / International Journal of Hydrogen Energy 29 (2004) 1487–1491

0 10 20 30 40 50 600

5

10

15

20

25

30

35

40

45

Standard deviation (σ ) =1.4635 nm

Mean (µ ) =6.4293 nm

Ratio (σ/µ) =0.22763

Distribution

Per

cent

age

of n

anot

ubes

Diameters in nm

Fig. 5. The diameter distribution of Fig. 4.

Fig. 6. TEM image [12].

variables like pressure, temperature and the precursorused.

(2) Most of the nanotubes seem to be forming in a narrowrange as denoted by the peaks of the histogram. One ofthe ways to study the spread is to obtain the �=� values.

0 10 20 30 40 50 600

5

10

15

20

25

30

Standard deviation (σ ) =2.1146 nm

Mean (µ ) =9.8649 nm

Ratio (σ/µ) =0.21436

Distribution

Per

cent

age

of n

anot

ubes

Diameters in nm

Fig. 7. The diameter distribution of Fig. 6.

Fig. 8. TEM image [12].

It will reMect the purity and the control on operatingparameters. The distribution can also help determine theaverage nanotube diameter of the sample.

(3) The e5ect of variation of operating parameters,the precursor used, the support and the e5ect of

A. Sarkar, R. Banerjee / International Journal of Hydrogen Energy 29 (2004) 1487–1491 1491

0 10 20 30 40 50 600

2

4

6

8

10

12

14

16

18

Standard deviation (σ ) =4.2953 nm

Mean (µ ) =16.1667 nm

Ratio (σ/µ) =0.26569

Distribution

Per

cent

age

of n

anot

ubes

Diameters in nm

Fig. 9. The diameter distribution of Fig. 8.

catalyst on average nanotube diameter can be furtherstudied.

(4) By studying the hydrogen storage capacity of a numberof nanotube samples the optimum diameter required formaximum storage can be found.

It is expected that the methodology outlined will be helpfulin removing some of the ambiguities in the experimental re-sults. It is recommended that along with the TEM and SEMimages the diameter distributions must also be included tosupplement visual inspection. The e5ect of catalyst size, thecomposition of catalyst, process and the operating conditionon the distribution need to be studied. Quantitative analysis

of physical parameters of carbon nanotubes is essential toensure repeatability and will help in the development ofbetter nanotubes for hydrogen storage. Image processingtechniques and statistical analysis will provide insights thatcan help CNT development. The methodology representedin this paper provides a step in this direction.

References

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