Nano Res

1

Raman microscopy mapping for the purity assessment

of chirality enriched carbon nanotube networks in thin

film transistors

Zhao Li (), Jianfu Ding, Paul Finnie, Jacques Lefebvre, Fuyong Cheng, Christopher T. Kingston, Patrick

R. L. Malenfant ( )

Nano Res., Just Accepted Manuscript • DOI 10.1007/s12274-015-0725-y

http://www.thenanoresearch.com on January 28, 2015

© Tsinghua University Press 2015

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Nano Research

DOI 10.1007/s12274-015-0725-y

TABLE OF CONTENTS (TOC)

Raman microscopy mapping for the purity

assessment of chirality enriched carbon nanotube

networks in thin film transistors

Zhao Li,* Jianfu Ding, Paul Finnie, Jacques Lefebvre,

Fuyong Cheng, Christopher T. Kingston, Patrick R. L.

Malenfant*

Security and Disruptive Technologies Portfolio,

National Research Council Canada, 1200 Montreal

Road, Ottawa, Ontario, K1A 0R6, Canada

SWCNT network

Purity and density

Via Raman Mapping

-8

-7

-6

-5

-4

-3

-2

-10 -5 0 5 10

Log

(ISD

)

VG (V)

2.5 um

5 um

Raman microscopy mapping can be a powerful characterization tool to

quantify residual metallic carbon nanotubes in high density networks of

enriched semiconducting single walled carbon nanotubes.

www.nrc.ca

Raman microscopy mapping for the purity assessment

of chirality enriched carbon nanotube networks in thin

film transistors

Zhao Li (), Jianfu Ding, Paul Finnie, Jacques Lefebvre, Fuyong Cheng, Christopher T. Kingston, Patrick

R. L. Malenfant ( )

Received: day month year

Revised: day month year

Accepted: day month year

(automatically inserted by

the publisher)

© Tsinghua University Press

and Springer-Verlag Berlin

Heidelberg 2014

KEYWORDS

Raman spectroscopy,

Carbon nanotubes, Thin

film transistors,

Microscopy mapping,

purity assessment.

ABSTRACT

With recent improvements in carbon nanotube separation methods, the

accurate determination of residual metallic carbon nanotubes in a purified

nanotube sample is important, particularly for those interested in using

semi-conducting single walled carbon nanotubes (SWCNT) in electronic device

applications such as thin film transistors (TFT). This work demonstrates that

Raman microscopy mapping is a powerful characterization tool to quantify

residual metallic carbon nanotubes present in highly enriched semiconducting

nanotube networks. Raman mapping correlates well with absorption

spectroscopy, yet provides greater differentiation in purity. Electrical data from

TFTs with channel lengths of 2.5 and 5 microns demonstrate the utility of the

method in a device context. By comparing samples with nominal purities of

99.0% and 99.8%, a clear differentiation can be made when evaluating the

current on/off ratio as a function of channel length and as such, the Raman

mapping method provides a means to guide device fabrication by correlating

SWCNT network density and purity with TFT channel scaling.

Nano Research

DOI (automatically inserted by the publisher)

Research Article

Address correspondence to Zhao Li, zhao.li@nrc.ca; Patrick R. L. Malenfant, patrick.malenfant@nrc.ca

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2 Nano Res.

As prepared SWCNT raw materials contain bundles

of nanotubes with a 2:1 semiconducting (sc-) to

metallic (m-) ratio and other impurities such as

catalyst and amorphous carbon [1-3]. For electrical

devices, these raw materials must be debundled,

purified and enriched [4-11]. It has been

demonstrated that for network thin film transistors

(TFT), the m-tube content should be less than 2% [3].

For more demanding applications, such as high

frequency logic circuits and display backplanes, the

m-tube content should be less than a few ppm given

the need for high mobility and current on/off ratios

[12]. In recent years, multiple efforts have led to

significant progress in solution based enrichment

techniques, with sc-SWCNT purity in excess of 99%

routinely achieved. This leap, however, has now

started to reveal the limits of common

characterization methods and other tools are

required to provide accurate purity assessment

[13,14].

Typically, the purity of enriched sc-SWCNT is

estimated from the UV absorption spectrum by

comparing the peak areas associated with the m- or

sc- species [12, 15-17]. This method works well for

samples when these peaks are well defined and

background absorption is not dominant. However, as

the sc-purity increases, the features associated with

m-tube absorption will gradually disappear and the

precise subtraction of the background absorption will

dramatically influence the calculated results and

introduce uncertainty [18]. As an alternative, we have

previously used a different purity metric, denoted φ,

which is based on the ratio of the sc-peak area over

the total absorption background from the metallic

(M11) and semiconducting (S22) absorption bands [16].

While we presume φ correlates well with purity for

highly pure samples, it does not provide a

quantitative assessment. Furthermore, a solution

sample is not necessarily representative of the

deposited networks on a solid substrate, such as a

transistor channel, where selective adsorption may

occur [19]. There is currently a need for a quick and

reliable method to quantitatively characterize a

SWCNT network for its residual m-SWCNT content

in fabricated TFTs in order to better understand

device performance as a function of SWCNT network

density and purity.

Methods for the measurement of m-SWCNT content

can be divided into bulk sample techniques and

counting-based techniques. Counting-based

techniques more accurately enumerate m- and

sc-nanotubes and typically rely on their electrical

and/or optical performance [20-29]. Although these

methods give relatively accurate results, they involve

tedious fabrication processes and costly instruments.

Furthermore, most of these methods are only

applicable to sparse SWCNT networks (<1 tube/µm2),

which is significantly below the typical tube network

density used in TFTs (10-40 tubes/µm2).

Raman spectroscopy is commonly used to

characterize SWCNT ensembles [30-36] and can also

be used for individual nanotubes due to its high

sensitivity and chirality selective resonance with

laser irradiation wavelength [37-39]. Raman

spectroscopy not only discriminates m- and sc- tubes,

but also enables the assignment of specific chiralities

to individual tubes [40-42]. Raman spectroscopy,

especially in the G band region, can be very sensitive

to metallic SWCNT contamination, and it is useful

for the purity assessment of highly pure SWCNT

samples [36]. Herein, we will demonstrate that

Raman microscopy mapping is an efficient and

effective characterization method for large area, high

density, high sc purity SWCNT networks in TFTs

[43-45].

SWCNT networks were formed on Si/SiO2 substrates

by soaking the later in toluene dispersions [16].

Networks formed by soaking are random in terms of

position and orientation of nanotubes. This type of

network produces TFTs with good performance (high

current density and current on/off ratio) and are

accessible using scalable fabrication processes.

Although the Raman mapping method presented

here will be proven with random nanotube networks,

it should be equally applicable to aligned nanotubes.

Raman microscopy was performed by raster

scanning a defined area. While scanning we can

monitor each spectrum and record the position of

interest to determine tube type and the validity of the

signal to eliminate false positives. Finally, a map or

image can be built by selecting specific Raman

peaks/bands. Figure 1 shows the Raman spectra and

mapping images of the network under 514 nm laser

excitation. According to the Kataura plot, a 514 nm

laser is resonant mainly with sc-nanotubes for the

range of tube diameters used here (~1.3 nm) [46-47].

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3 Nano Res.

The dark area at the top of the images is the

evaporated TFT electrode. Figure 1(b) and 1(d) show

the intensity mapping of the G+ band from 1581 to

1602 cm-1 and RBM band from 140 to 208 cm-1,

respectively (all Raman mapping images have been

processed and raw data can be found in the ESM).

These two maps show similar intensity patterns,

confirming these two bands come from the resonance

of tubes at the same position. Several representative

spectra covering D and G bands extracted at the

marked spots in Figure 1(b) are shown in Fig. 1(a),

which are typical sc-tube Raman spectra [30-36].

Figure 1(c) shows the RBM bands of these spots and

the peaks centered at 190 cm-1 correspond to 1.30 nm

diameter (10, 9) sc-tubes, agreeing well with the

result from PLE mapping [16].

Figure 1 Raman spectra and maps for excitation at 514 nm. (a) G

band spectra; (b) G+ map obtained from integrated intensities in the 1581-1602 cm-1 range; (c) RBM band spectra and (d) RBM map obtained from integrated intensities in the 140-208 cm-1 range. Circles in (b) and (d) highlight positions from which

spectra were taken in (a) and (c). Scanned area was 16×16 μm2 and scale bar is 2 µm. The concentration of the SWCNT solution was 7.6 mg/L and the networks were prepared by submerging the substrate for 10 min in the SWCNT solution.

The purpose of this work is to quantitatively assess

the minority m-SWCNT species buried in the

sc-SWCNT network. Given the diameter distribution

of the sample used here, 633 nm laser excitation

matches well with the M11 absorption resonance.

Figure 2(a) compares the Raman spectra in the 1200

to 1700 cm-1 region under 514 and 633 nm laser

excitation spatially averaged over the whole scanned

area. The spectrum from 633 nm excitation has a

clear metallic signature with a broad G- band

(Breit-Wigner-Fano lineshape), in contrast with the

sharper G- seen at 514 nm [30-36, 49-50]. Since the

sample is highly sc-enriched, the off resonance

contribution from sc-tubes at 633 nm is

non-negligible, especially for the spatially averaged

spectra as in Figure 2(a). However, individual spectra

generated from 1 µm2 defined pixels will be

dominated by m-SWCNTs resonant under 633 nm

excitation considering their much higher scattering

cross-section.

Figure 2 633 nm Raman spectra and maps taken from the same area as in Fig. 1. (a) Spatially averaged Raman spectra covering

the whole area (normalized to G+ band); (b) G+ and (d) G- map obtained from integrated intensities in the 1581-1602 and

1507-1547 cm-1 range; (c) G band spectra; (e) RBM band spectra and (f) RBM map obtained from integrated intensities in the

149-210 cm-1 range. Circles in (b), (d) and (f) highlight positions from which spectra were taken in (c) and (e). Scanned area was 16×16 μm2 and scale bar is 2 µm.

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4 Nano Res.

The Raman intensity mapping of the G+ band under

633 nm laser excitation in Fig. 2(b) shows different

patterns compared to 514 nm laser excitation (Fig.

1(b)), meaning Raman signals originated from

different tube species. Figure 2(d) shows the G- band

intensity mapping covering 1507 to 1547 cm-1, where

bright spots correspond only to m-SWCNTs in this

area. By analyzing the raw spectra for each pixel, we

found 21 locations in the scanned area having typical

m-SWCNT G- band signals with the Raman spectra

shown on Fig. 2(c).

We count one metallic tube if the spectrum has a

strong (signal visually well above noise floor; for a

signal:noise ratio of approximately 3:1) and broad G-

peak at 1530-1560 cm-1. Variation in intensity from

pixel to pixel can be related to tube chirality, length

and its overlap with the laser spot [30-37]. For strong

G- signals that extend over several contiguous pixels,

the spectra were analyzed to determine if each spot

contained one or more m-tubes. Given an average

tube length of 1.2 μm and given that a 0.5 m raster

increment was used to assess each pixel, if identical

spectra were collected over multiple adjacent pixels,

only a single m-tube was counted (it is statistically

improbable that two metallic tubes are situated in

adjacent pixels).

Most of the RBM bands of these pixels (Fig. 2(e))

show only one peak, meaning no more than one

diameter of m-SWCNT per pixel were found. In such

cases, we assumed that only one nanotube was

present at that location. Only one RBM band (green

trace in Fig. 2(e)) displays two peaks at 170.8 and

185.0 cm-1, indicating two m-SWCNTs within that

pixel. The diameter of these two m-SWCNTs are

calculated to be 1.45 and 1.34 nm and they are

assigned to (15, 6) or (16, 4) and (14, 5) respectively,

considering their resonance with 633 nm irradiation

[30-36].

In order to calculate the purity in the SWCNT

networks, we use SEM charge contrast imaging to

obtain an accurate measure of the nanotube network

density of the same area (a 4 µm2 area was used to

count tubes at high magnification). For the sample in

Fig. 1-2, a density of 40 nanotubes/μm2 was

measured, which amounts to 104 nanotubes for the

16×16 µm2 area. (Fig. S1). As a result, the residual

m-SWCNT content is estimated to be 0.2%. Note that

this method may underestimate m-SWCNT content

due to off resonance or no G- contribution from

armchair SWCNT [51]. Armchair SWCNTs have

unique Raman spectra and we did not observe any in

our networks [51]. Statistically speaking, only 3

armchair tubes species would be expected given the

diameter range of the enriched SC-SWCNTs we have

isolated [(9,9); (10,10); (11,11)]. Assuming an even

distribution of chiralities in the unsorted starting

material, armchair tubes in our diameter regime

would represent less than 10% of all metallic tubes, a

negligible contribution to the underestimation.

Figure 3 Calibration of G+ band intensity versus carbon nanotube

coverage determined by SEM. The scanned area was 16×16 µm2. The intensity for both wavelengths was normalized for easy comparison.

To expedite the method, a Raman mapping

calibration curve that obviates the need for repeated

SEM was established. Networks with tube densities

ranging from 2 to 100 tubes/µm2 were made using

different SWCNT solution concentrations and

analyzed by SEM (Fig. S2). Figure 3 shows the G+

peak intensity at 1591 cm-1 averaged over a 16×16

µm2 area under 514 nm or 633 nm laser excitation vs

SEM tube network density. Good linearity is found

for network densities up to 40 tubes/µm2. We should

emphasize that at higher tube coverage it becomes

increasingly difficult to accurately count tubes using

charge contrast SEM imaging as evidenced by the

outlying data point observed in Figure 3 (~80

nanotubes/m2). As a result, it is possible to estimate

both the tube network density and sc purity using

exclusively Raman microscopy mapping (vide infra).

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5 Nano Res.

0

200

400

600

800

1000

1200 1300 1400 1500 1600 1700 1800

Inte

nsi

ty

Raman Shift (cm-1)

SC1

SC2

SC1, 633 nm (G-) SC2, 633 nm (G-)

0

5

10

15

20

25

Mo

bili

ty (

cm2/V

s)

Channel Length (µm)2.5 5.0

SC1 SC1SC1

2.5 5.0

SC2

1E+0

1E+1

1E+2

1E+3

1E+4

1E+5

1E+6

1E+7

1E+8

On

/off

rat

io

Channel Length (µm)2.5 5.0

SC1 SC2

2.5 5.0

0

0.2

0.4

0.6

0.8

1

400 800 1200 1600 2000

Ab

sorp

tio

n (a

.u.)

Wavelength (nm)

SC1

SC2

(a) (b)

(d)

(f)

(c)

(e)

Figure 4 (a) UV absorption spectra of enriched sc-tube samples

SC1 and SC2 in solution. (b) Raman spectra averaged from 20×20 µm2 area for networks prepared from SC1 and SC2 for

excitation at 633 nm. (c) and (d) G- maps obtained from integrated intensities in the 1507-1547 cm-1 range for networks prepared from SC1 and SC2 respectively. (e) Mobility and (f) current on/off ratio of thin film transistors prepared from SC1

and SC2. The channel width is 2000 µm. Transfer curves can be found in Figure S3 in the ESM.

The validity of the Raman mapping method for the

sc-purity evaluation was further confirmed using two

conjugated polymer enriched sc-SWCNT samples

(SC1 and SC2). As shown in Fig. 4(a), the UV-vis

absorption curve of SC2 (ɸ=0.40) has a much deeper

valley centered at 630 nm than that from SC1 (ɸ=0.33),

and the Raman spectrum of the SC2 network has a

lower intensity of G- band at 1540 cm-1 (Fig. 4(b)).

Although both data indicate higher m-SWCNT

content in SC1, we only have qualitative information

[5]. We then scanned an area 20×20 µm2 using 633 nm

laser excitation for each network and intensity

mapping was done using a G- window spanning 1507

to 1547 cm-1 (Fig. 4(c) and 4(d)). We counted 135 and

20 m-SWCNT signals for SC1 and SC2 networks

respectively. Using the calibration curve in Figure 3,

the tube density of these two networks was

calculated to be ~ 30 tubes/µm2. As a result, the

m-SWCNT content was estimated to be 1.0% and

0.2%, thus the sc-nanotube purity was estimated at

99.0% and 99.8% for SC1 and SC2, respectively.

In order to assess the correlation between SC purity

and channel length, samples SC1 and SC2 were

further compared as the semiconducting channel

material in thin film transistors. A SWCNT network

was combined with a bottom gate, bottom contact

device configuration with interdigitated S/D

electrodes having a 2000 µm channel width [16].

Devices were prepared under identical conditions

with regards to solution concentration and TFT

performance data are summarized in Fig. 4(e) and

4(d). At 5 µm channel lengths the TFTs have very

similar mobility values of 20±2 cm2/Vs and excellent

current on/off ratios, reaching as high as 1x107.

However, devices with 2.5 µm channel lengths

clearly reveal the purity difference between SC1 and

SC2 even though similar mobility values of 16±1

cm2/Vs were obtained. In a representative sampling

of four devices, all four 2.5 µm channel length TFTs

from SC1 had on/off ratios < 1x104, with three devices

< 1x103 while three TFTs from SC2 had on/off ratios >

1x106 and only one device had an on/off ratio

between 103 and 104. The TFT data at 2.5 µm channel

lengths agrees with the purity differentiation

obtained by Raman mapping, further substantiating

the ability of the method to discriminate between

highly enriched sc-SWCNT samples. A statistical

model was used to determine the probability of a

percolation path to form (see ESM for calculations).

For TFTs with a channel length of 2.5 m, we expect 1

metallic path every 290 μm for a network with 0.2%

metallic tube content (SC2) or every 5 μm for 1%

metallic tube content (SC1). Given that our channel

width is 2000 m, a few short circuits, if any, are

expected for the higher purity sample, while short

circuits should be fairly abundant in the lower purity

sample. Given that the on currents are of the order of

several mA, and with several short circuits

contributing current of the order of 1 μA in the off

state, on-off ratios of the order of 103 are expected for

the lower purity sample (SC1), consistent with our

purity assessment.

In summary, Raman mapping has been shown to be

an efficient and effective method to quantitatively

evaluate sc-purity and SWCNT network density

directly in fabricated TFT devices. The accuracy of

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6 Nano Res.

the method was further validated by sc-SWCNT

network TFT device performance at short channel

lengths. The advantage of using networks of

SC-SWCNT over aligned tubes [52-55] for the active

channel in TFTs is the favorable trade-off between

targeted performance and ease of fabrication [56-58].

Such TFTs will find utility in low cost display driver

and logic circuit elements fabricated using scalable

deposition techniques such as dip-coating, ink-jet or

gravure printing [59-66]. This work bridges the gap

between separation methods that yield high purity

sc-SWCNTs and available characterization tools for

purity assessment thus providing a framework for

device design that considers TFT channel scaling

with SWCNT density and purity.

Acknowledgements

The authors would like to thank Jeff Fraser for SEM

imaging.

Electronic Supplementary Material: Supplementary

material (Materials, SWCNT film preparation, TFT

device fabrication and testing, resonance Raman

spectra mapping method and representative SEM

images) is available in the online version of this

article at http://dx.doi.org/10.1007/s12274-***-****-*

(automatically inserted by the publisher). References

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