Conductivity Enhancement of Transparent 2D Carbon Nanotube

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C: Physical Processes in Nanomaterials and Nanostructures

Conductivity Enhancement of Transparent 2D Carbon Nanotube Networks Occurs by Resistance Reduction in All Junctions Avigail Stern, Suzanna Azoubel, Ela Sachyani, Gideon I Livshits, Dvir Rotem, Shlomo Magdassi, and Danny Porath J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.8b01215 • Publication Date (Web): 05 Jun 2018 Downloaded from http://pubs.acs.org on June 5, 2018

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The Journal of Physical Chemistry

Conductivity Enhancement of Transparent 2D Carbon Nanotube Networks Occurs by Resistance Reduction in All Junctions Avigail Stern a‡, Suzanna Azoubel a‡, Ela Sachyani a, Gideon I. Livshits a,b, Dvir Rotem a, Shlomo Magdassi a* and Danny Porath a* a. Institute of Chemistry and The Center for Nanoscience and Nanotechnology, The Hebrew University of Jerusalem, Jerusalem 91904, Israel b. Present address: Department of Chemistry, Graduate School of Science, Osaka University, Osaka 560-0043, Japan ‡ These authors contributed equally * Corresponding authors: [email protected], [email protected].

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ABSTRACT: Transparent conductive networks are important for flexible electronics and solar cells. Often inter-wire (junction) conductivity is the limiting factor for network conductivity and can be improved by various treatments. The conductivity of individual junctions was measured by conductive atomic force microscopy before and after exposure to nitric acid. The measurements show that this exposure improves the conductivity of each one of the junctions within the network. Our results suggest that the acid improves the conductivity by p-type charge transfer doping and by surfactant degradation.


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INTRODUCTION Conductive and transparent surfaces are a central component for flexible transparent electronics and solar cells. These surfaces are often made of networks, which are mostly composed of conductive nanowires, such as metallic nanowires,1 conducting polymers,2 or carbon nanotubes (CNTs).3 Optimal function of the networks requires high values of two entangled properties: conductivity and optical transparency. Often, however, improvement of one parameter degrades the other one. For example, the more material is deposited the higher the conductivity but the lower the transparency and vice versa. While the network’s transparency is dependent on the material that is used and its quantity, the network conductivity is limited by inter-wire junctions.4 Therefore, the key to optimizing network performance while minimizing the amount of material is to improve the junction conductivity. In this work, we used a single walled carbon nanotube (SWCNT) network as a model system for a conductive transparent surface. CNT networks have attracted much attention recently as transparent, conductive and flexible thin films for various applications.5-8 CNTs have relatively low electrical resistance (of kΩ order at room temperature)9 along with good mechanical flexibility.5 The limiting factor of CNT network conductivity is charge injection from tube to tube (or bundle to bundle) at junction interfaces within the network and not the electrical conductivity of the CNTs themselves.4 Various alterations have been implemented on such networks in order to improve their electric conductivity. Such alterations include, e.g., integration of polymers in the CNT network,10 decorating the CNTs with metallic nanoparticles,11 heating of the CNT network,12 and acid treatment of the CNT networks.13-14 3 ACS Paragon Plus Environment


Nitric acid (HNO3) treatment is known to improve the charge transport through macroscopic SWCNT networks without significantly changing the network transparency.13, 15 The effect of HNO3 on CNT networks was researched by various methods with an emphasis on revealing the mechanism by which it improves the network conductivity.13 Atomic force microscopy (AFM) studies showed that the improvement in network conductivity was primarily due to improvement in junction conductivity.16-17 A few mechanisms for the acid effect on the junctions were proposed. These include removal of insulating surfactant from the junction;13, 18 removal of amorphous carbon;19 reduction of Schottky barriers (conductivity barriers at metallic-semiconducting junctions)20 between metallic and semiconducting SWCNTs 21 and chemical p-type doping. The doping is believed to result from intercalation of nitric acid molecules at interfaces between SWCNTs and charge transfer from the CNTs to acid adsorbates.22-23 Previous cAFM reports on acid-treated SWCNT networks have focused on measuring the average change in conductivity over many different junctions before and after acid treatment and thereby established only the effect of acid on the junction’s mean conductivity.16-17 In contrast, we used cAFM to perform direct resistance measurements of the same individual junction before and after acid treatment on multiple junctions. Our measurements monitor the change in conductivity for each measured junction. Analyzing the change in conductivity of individual junctions following HNO3 treatment allowed us to test whether the acid treatment improved the conductivity of only certain percolation paths in the network or of all junctions. Consequently, conclusions were reached as to the possible mechanisms by which HNO3 improves the junction’s conductivity.


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EXPERIMENTAL METHODS Sample Preparation: 0.1 wt % Hanos ASP 100F single wall carbon nanotubes (SWCNT, Hanwha, Korea) were dispersed in 0.5 wt % Triton X100 aqueous solution by tip sonication. After diluting the dispersion 1:10 with water, air spray was utilized for deposition of sparse SWCNT networks on freshly cleaved grade V1, 9.9 mm diameter mica discs (Ted Pella), followed by 1 min rinsing in ethanol bath for surfactant removal. The samples were scanned by AFM to measure the surface coverage. AFM scanning was performed with a Smart-AIST AFM in AC (tapping) mode with 100 µm long silicon nitride cantilevers (Olympus, OMCL-RC800PSA-W) with a nominal resonance frequency of 70 kHz. The samples were then mounted under a stencil mask, placed on a sample and mask holder and transferred to a thermal evaporator (modified Edwards E306). Evaporation of a gold electrode was then performed as described previously by us in Livshits et al.24 Electrical Measurements: cAFM measurements were performed with SmartAIST cAFM system, before and after exposing the sample to acid fumes. Cr/Pt coated silicon tips were used (Budget Sensors, Multi75E-G). The samples were scanned in AC (tapping) mode to locate the measurement areas. Measurements were performed within chosen areas at 20 nm resolution by contacting each measurement point with the AFM tip at ~100 nN contact force, and sweeping the voltage from -50 mV to +50 mV and back again while measuring current every 0.5 mV with a sweep time of 200 msec (see Figure 2). The tip was shifted from one measurement point to the next in non-contact mode. Since the measured resistance did not change along the SWCNT branches between adjacent junctions, the resistance values were attributed to each branch. These 5 ACS Paragon Plus Environment


values were calculated based on averaging the 3-5 lowest resistance I-V curves that were measured on the branch. We calculated the resistance of junctions connecting two branches by subtracting the resistance measured on the lower resistance branch from the resistance measured on the higher resistance branch (see Figure 1c). The electrical measurements were done at the exact same locations on the network before and after acid treatment (see below). Acid Treatment: To perform the acid treatment, the sample was placed in a 15 cm diameter glass petri dish along with an open 6 cm diameter petri dish filled with acid solution (97% HNO3 or 38% HCl in water). The large petri dish was placed in a pumped hood and covered. After 30 sec incubation the large petri dish was opened and the sample was immediately removed from the petri dish. The sample was then left in the pumped hood until it was completely dry before insertion to the AFM system for further measurements.

RESULTS AND DISCUSSION Sparse SWCNT networks were deposited on a mica surface and measured. SWCNTs appeared in the network both in single form (~1.5 nm apparent height) and as bundles (up to ~20 nm apparent height) (Figure S1). The distance between junctions within the network was between ~100 nm and ~1 µm, and the length of individual bundles was over 5 µm. A gold electrode was evaporated over the network under conditions that produced a very sharp border between the gold electrode and the clean mica as illustrated in Figure 1a and shown in Figure 1b. AFM topography imaging along the gold border shows SWCNT networks on the mica protruding from beneath the sharp gold border (Figure 6 ACS Paragon Plus Environment

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1b). Electrical measurements were performed on the networks with a cAFM tip serving as a second mobile electrode at distances between tens and thousands of nanometers from the electrode border (see Figure 1a). The junctions that were measured were mostly junctions between bundles of SWCNTs, most likely containing a mixture of metallic SWCNTs and semi-conducting SWCNTs.

Figure 1. (a) Illustration of our measurement setup which is comprised of a CNT network (grey) deposited on an insulating mica surface (blue) and a gold electrode (yellow) with a sharp border evaporated on top. cAFM is used to contact selected locations on the CNT networks and perform conductivity measurements. (b) AFM scan of CNT network on mica surface protruding from gold electrode on left. Inset shows cross section demonstrating sharpness of gold border. Scale bar = 1 µm. (c) Schematic of measurement method and junction types. cAFM measurements on different branches give branch resistances. Subtracting one branch resistance from the other gives junction resistance. Three junction types are illustrated- X, Y and I. cAFM measurements were performed on selected areas. The tip was moved on a predefined grid within the chosen measurement areas from one measurement point to the next, and at each grid point the tip was brought into contact with the surface, a currentvoltage (I-V) measurement was acquired and the tip was retracted from the surface. By 7 ACS Paragon Plus Environment


using this method, grids of I-V curves within the chosen measurement areas were obtained. This measurement technique enabled mapping of SWCNT network areas on the sample (see for example Figure 2) and performing electrical measurements at the same precise locations before and after exposing the sample to acid fumes.

Figure 2. I-V measurements on single branches before and after exposure of the sample to HNO3 fumes show reduction in the resistance measured on each branch and a reduction in resistance of the individual junctions. (a) A 5 X 5 µm2 AFM scan of SWCNT network protruding from gold border. The area marked by red square is enlarged in (b) and (c). Measurements were performed within the area marked by yellow polygon as shown in (b) and (c). scale bar = 1 µm. (b), (c) Conductive AFM measurements before (b) and after (c) exposing the sample to HNO3 overlaid on AFM scan of the area. Two branches were measured with an X junction between them. The color scale represents the current measured at each point at 1 mV bias between the tip and the sample. Representative I-V curves from each of the branches are presented. The measured resistance is reduced


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following HNO3 treatment. In addition, the junction resistance is reduced from ~30 MΩ to ~3 MΩ following HNO3 treatment. scale bars = 200 nm. Electrical measurements were obtained at multiple points on the SWCNT network and gave linear I-V characteristics, thus enabling calculation of resistance values at each point (Figure 2). It is important to note, that though the SWCNTs composing the network were a mixture of metallic and semi-conducting, the I-Vs that were measured were all linear. This is probably due to the metallic SWCNTs that are present in the various bundles that were measured, and due to the measurements being performed at room temperature where many semi-conducting SWCNTs also show linear I-V characteristics.25 I-V measurements on the bare mica surface gave no current for all areas that were measured. Plotting resistance vs. distance along chosen paths within the SWCNT network (Figure 3) shows constant resistance along SWCNTs, also where SWCNTs or individual bundles bend and curve, with sudden jumps at various locations. The jumps were attributed to the presence of junctions at these locations. These junctions could be morphologically grouped into three types according to their configuration, as illustrated in Figure 1c. Some junctions were formed by two SWCNTs or bundles crossing each other in an X configuration (see junction marked X in Figure 1c). Other junctions were formed by a bundle of SWCNTs splitting into two smaller bundles or individual SWCNTs in a Y configuration (see junction marked Y in Figure 1c).17 A third type of junction was formed by the end of one SWCNT or bundle attached to the beginning of a second SWCNT or bundle to form a longer structure (see junction marked I in Figure 1c).



The resistance of junctions connecting two branches was calculated by subtracting the resistance measured on the lower resistance branch from the resistance measured on the higher resistance branch (see Figure 1c). Due to the very large distribution of junction resistances that were measured (between 10 kΩ and 500 MΩ), statistical treatment of the junction resistances was performed in the logarithmic scale. When performing statistical analysis, the junctions were all treated as a single population. The junctions were not segregated by the groups described above (X, Y and I) or by semiconducting/metallic behavior, as no grouping could be recognized in the conductivity data that was measured. No correlations were found between junction resistance and the junction angle (Figure S2) or between junction resistance and the thickness of the bundles composing the junctions (Figure S3).

Figure 3. An example of measured resistance values plotted along a given path through an X type junction (a) An AFM scan of the measured path. The path through the junction along which the resistance was measured is marked by dotted arrows, the branch preceding the junction in blue, and the branch after the junction in red. Scale bar = 200 nm. (b) A plot of resistance vs. distance along the path marked in panel (a) before (dark blue and dark red) 10 ACS Paragon Plus Environment

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and after (pale blue and pale red) exposure to HNO3 fumes. A jump in resistance is seen at the junction. The magnitude of this jump is the junction resistance which is reduced significantly after exposure to HNO3 fumes. AFM scans at individual locations within the SWCNT network before and after exposure to HNO3 showed some removal of contamination following acid treatment (see for example Figure S4). Conductivity measurements that were performed at chosen locations before and after exposing the sample to HNO3 fumes show an overall reduction in measured resistances following the HNO3 treatment (see for example Figure 2, and Figure S5). Furthermore, measurement of the resistance along a single path through a junction, before and after exposing the sample to HNO3 fumes, shows a significant reduction in junction resistance but no significant difference in the change in resistance along a single branch (Figure 3). The resistance of each one of the junctions was reduced about 10-fold on average after treatment with HNO3 (from 107.1±0.7 Ω on average to 106.0±0.6 Ω as geometrically averaged over 33 junctions, Figure 4a and 4b), whereas no significant change was observed upon HCl treatment on a different network (107±1 Ω on average both before and after HCl treatment as geometrically averaged over 34 junctions, Figure S6 and Figure 4b). Therefore, we conclude that the reduction in macroscopic sheet resistance following HNO3 treatment is the outcome of improvement in the conductivity of all the junctions within the network and consequently of every one of the possible conductive paths and not only of certain individual percolation paths.



Figure 4. (a) Histograms in logarithmic scale of junction resistance before (blue) and after (red) exposure to HNO3 fumes show a shift to lower values following the acid treatment. This shift indicates a reduction in average junction resistance due to exposure to HNO 3 fumes. (b) Histograms in logarithmic scale of the change in junction resistance for individual junctions following HNO3 (green) and HCl (yellow) treatment. The resistance of junctions that were exposed to HNO3 fumes decreased 10 fold on average, and the resistance of junctions that were exposed to HCl fumes did not change significantly on average. Gaussian fits are shown for each of the distributions as guides to the eye. The mechanism by which HNO3 treatment improves the conductivity of SWCNT junctions is one that affects all the junctions, and is specific to HNO3 as opposed to HCl. Though the mechanism may differ for metallic-metallic, metallic-semiconducting or semiconducting-semiconducting junctions, in the networks that were measured the junctions were mainly between bundles, most likely including both metallic and semiconducting SWCNTs. Furthermore, we do not recognize different behaviors of junction conductivity improvement for these separate groups and therefore cannot supply separate analysis.


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P-type charge transfer doping is believed to occur by intercalation of HNO3 molecules in voids that form within SWCNT bundles or other junctions between SWCNTs.23 This mechanism is, therefore, likely to affect most or all the junctions within a network which is exposed to HNO3, as observed in our results. Furthermore, this mechanism is specific to HNO3 acid and may take place to a significantly lesser extent under exposure to HCl, as suggested previously26 and in accordance with our results. In addition it is probable that surfactants are present in most or all junctions due to their role in dispersing the nanotubes in aqueous solution, and their elimination from the junctions is likely to affect most, or all, the junctions within the network. Improvement in conductivity due to surfactant removal from the junctions, in our system, could not be by washing the surfactant away, as the acid treatment was done by exposure to fumes and not in solution. Surfactant removal could however take place by chemical oxidation of the surfactant by HNO3 resulting in a smaller conductivity barrier between CNTs. Contamination removal from the sample surface following exposure to HNO3, as shown in Figure S4, supports the possibility of surfactant degradation by the acid. HCl, which we show does not improve junction conductivity, has been shown to be less effective at degrading surfactants within CNT networks.14 Other proposed mechanisms are in disagreement with our results. Reduction in Schottky barrier at semiconducting-metallic junctions is a mechanism that can affect only some of the junctions (only metallicsemiconducting junctions) and therefore unlikely to be the main mechanism in this system. Similarly, residual contaminations from CNT synthesis, such as amorphous carbon, seems unlikely to be present in every one of the junctions and therefore their elimination is also not expected to reduce the resistance of all the junctions. Charge



transfer doping, as described above, and surfactant degradation are therefore the only mechanisms that remains likely to be most effective in our system.

CONCLUSIONS We demonstrate the effect of chemical treatment on the resistance of specific individual junctions in SWCNT networks. We show that HNO3 treatment improves the conductivity of every one of the junctions within the network and not only of certain percolation paths. We, therefore, conclude that the main mechanisms by which HNO3 affects the conductivity of SWCNT networks are by charge transfer doping of the network and by surfactant degradation. This work demonstrates the importance of understanding the conductivity of individual junctions within conductive networks and their role in defining the overall network conductivity. This understanding may assist in improving the conductivity of different two dimensional networks for various applications, particularly for transparent electronics and solar cells.

Acknowledgments This research was supported by the Israel National Nanotechnology initiative-FTA program, and by the National Research Foundation, Prime Minister’s Office, Singapore, under its Campus for Research Excellence and Technological Enterprise (CREATE) NEW program. DP is supported by the Israel Science Foundation (ISF grant 1589/14) and by the Minerva Centre for bio-hybrid complex systems. D.P. thanks the Etta and Paul Schankerman Chair of Molecular Biomedicine.


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Conductivity Enhancement of Transparent 2D Carbon Nanotube

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