Ultralow Percolation Threshold in Nanoconfined Domains - ACS Nano

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Ultra-Low Percolation Threshold in Nano-Confined Domains David R. Barbero, and Nicolas Boulanger ACS Nano, Just Accepted Manuscript • DOI: 10.1021/acsnano.7b03851 • Publication Date (Web): 26 Sep 2017 Downloaded from http://pubs.acs.org on September 28, 2017

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Ultra-Low Percolation Threshold in Nano-Confined Domains David R. Barbero∗ and Nicolas Boulanger Nano-Engineered Materials and Organic Electronics Laboratory, Umeå Universitet, Umeå 90187, Sweden E-mail: [email protected]

Abstract Self-assembled percolated networks play an important role in many advanced electronic materials and devices. In nano-carbon composites, decreasing the percolation threshold φc is of paramount importance to reduce nanotube bundling, minimize materials resources and costs, and to enhance charge transport. Here we demonstrate that 3-dimensional (3D) nano-confinement in single wall carbon nanotube (SWNT)/ polymer nanocomposites produces a strong reduction in φc , reaching the lowest value ever reported in this system of φc ≈ 1.8 · 10−5 wt.%, and 4–5 orders of magnitude lower than the theoretical statistical percolation threshold φstat . Moreover, a change in network resistivity and electrical conduction was observed with increased confinement, and a simple resistive model is used to accurately estimate the difference in φc in the confined networks. These results are explained in terms of networks’ size, confinement and tube orientation as determined by atomic force microscopy, electrical conductivity measurements, and polarized Raman spectroscopy. Our findings provide important insight into nanoscale percolated networks, and should find application in electronic nano-composites and devices. ∗

To whom correspondence should be addressed

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KEYWORDS: carbon nanotubes, percolation, nanoconfinement, organic electronics, charge transport

Percolation is of paramount importance in electrically active nano-carbon composites and hybrid electronic devices where single walled carbon nanotubes (SWNT) and graphene enable charge transport across the network. 1,2 Examples of the importance of such percolated networks can be found in flexible electrodes, field-effect transistors, hybrid photovoltaic solar cells and flexible supercapacitors. 2–5 The minimum amount of interconnected sub-units necessary to form a percolated network which enable transport of electricity across the system is called the percolation threshold, φc . 6–8 A central question in percolated systems is how to lower φc in order to reduce the amount of materials, to ease processing, and to enhance electrical properties by minimizing bundle formation. 9,10 Recently, it was found that reducing the nanotube loading in bulk heterojunction photovoltaic solar cells enabled a decrease in series resistance, and an overall enhancement in power conversion efficiency due to better charge transport and extraction. 11 Moreover, a growing number of applications require device miniaturization, formation of nanostructured domains, and the use of highly purified and expensive to produce semiconducting nanotubes to prevent electrical shorts or exciton quenching, e.g. in photovoltaic devices. 11–13 This poses new questions regarding percolation in confined and nanoscale domains. It is therefore important to better understand how nano-confinement affects percolation in such systems, and to find new ways to reduce φc . In carbon nanotube composites, the aspect ratio of the nanotubes, the dispersion method, and the interaction between the matrix and the nanotubes has been shown to strongly affect the network formation and φc . 14–16 Large variations in percolation threshold from φc ≈ 0.005 to 5 wt% have been reported for SWNTs mixed in polymer matrices such as polystyrene, P3HT, polyvinylidene difluoride, and polymethylmethacrylate. 17–21 A nanotube concentration of 0.11 wt% was used to produce conductive nanoscale networks made of SWNTs in polystyrene, however no investigation of the percolation threshold has been performed in

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such systems. 22 Interest in 3-dimensional nanoscale networks is becoming more intense due to the recent trend towards nanostructuring of nano-materials and devices. 12 It was moreover recently shown that confined nanoscale percolated networks could enhance charge transport in carbon nanotube nanocomposites, and in graphene polymer composites for supercapacitor and sensing applications. 22–24 However, despite the strong interest in electrical nanocomposites for various application, there is still very little known about how the network’s size and confinement affect the percolation threshold in nanoscale systems. Here, we investigated how nano-confinement affects φc and the network resistivity in self-assembled SWNT/polymer nano-composites. Our results show that the formation of nanoscale networks is accompanied by a strong reduction in percolation threshold, reaching the lowest value reported to date of φc ≈ 1.8 · 10−5 wt.%. Electrical conductivity measurements at various loadings indicate that confined domains form percolated networks at much lower filler concentrations than larger 2-dimensional and random networks. Polarized Raman spectroscopy revealed a higher degree of tube alignment in the direction of current flow in the confined domains. Moreover, a simple resistive model accurately estimates the difference in tube loading in the confined networks near percolation. These results are explained in terms of networks’ size, dimensionality, and confinement during network formation by directed self-assembly. This is, to the best of our knowledge, the first report of an ultra-low percolation threshold induced by nanoscale confinement. It demonstrates the possibility to strongly reduce nanotube loadings in nanocomposites by forming nanoscale domains, which is also appealing to cut on materials cost and to enhance the performance of electronic devices.

RESULTS Confined Networks In order to investigate φc in nano-confined domains, we produced three different types of SWNT networks in an insulating polystyrene matrix: 1) a 2 dimensional film produced by

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spin-coating and refereed to as either a random network or a 2D network due to the 2D geometry of the film, as shown schematically in Figure 1a; 2) a micro-confined network made of micron-sized pillars, and 3) a nano-confined network made of nano-sized pillars. The confined networks were produced by nanoimprinting by a soft mold 22,25 as shown schematically in Figure 1b, and resulted in regular arrays of networks with well defined dimensions, as measured by atomic force microscopy and scanning electron microscopy (Figure 1c,d). The micro-sized networks were ≈4.0 µm in diameter and ≈1.0 µm high, whereas the nanonetworks were ≈350 nm in diameter and ≈320 nm high, both arranged in a periodic arrays with a periodicity of ≈6 µm and 780 nm respectively. These are also referred to as 3D micro and 3D nano networks due to the 3-dimensional geometry of the patterns in which the networks are confined. The concentration of nanotubes was varied over a large range of values from φ ≈ 5 · 10−6 wt.% to 0.5 wt.%, and φc was experimentally determined in each type of network by measuring the electrical conductivity vs. the nanotube concentration, as described thereafter.

Electrical Conductivity and Percolation Threshold Electrical conductivity was measured in the out of plane direction by applying a voltage bias between the conducting silicon substrate (bottom electrode) and a top electrode. The top electrode was made of a slightly flexible gold coated polydimethylsiloxane (PDMS) slab in order to make conformable contact with the top surface of the films and patterns, as explained in detail elsewhere 26 and as shown in Figure 2b. Under an applied voltage bias, the resulting electrical current was measured and the electrical conductivity σ was calculated as follows: σ=

I t · U A

(1)

where U is the applied voltage difference, I is the measured current, t is the distance between the electrodes (thickness of the network), and A is the contact area between the top electrode

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and the top of the composite. The contact area is the same as the area of the electrode for the macroscale 2D network, whereas for the patterned composites it is calculated as 2

π · D4 A = Aelectrode · p2

(2)

where Aelectrode is the electrode contact area, D is the pillar diameter and p is the periodicity between patterns. The electrical conductivity σ measured at different nanotube loadings φ is presented in Figure 2 for the three types of networks. A percolation threshold φc was observed in each case, and σ was fitted by the following equation as a function of φ: 27 σ = σ0 (φ − φc )t

(3)

where σ0 is related to the conductivity of the network, φ is the volume fraction of nanotubes in the matrix, and t is the critical exponent which depends on the dimensionality of the network. In the above equation both φ and φc were expressed in volume fractions. Values of σ0 , φc and t were estimated by fitting the experimental data with equation 3, using an implementation of the Levenberg-Marquardt method. 28 The reference random network gave a percolation threshold φc ≈ 2.5 · 10−2 wt.% (Figure 2b), whereas in the 3D confined networks values of φc ≈ 1.2 · 10−4 wt.% (Figure 2c) in the micro-networks, and φc ≈ 1.8 · 10−5 wt.% in the nano-networks (Figure 2d) were measured. This represents a reduction in φc by ≈ 1400 times compared to the random network. Percolation thresholds of 0.28 wt.% and 0.01 wt.% have been reported elsewhere for SWNT/polystyrene and SWNT/epoxy composites, 29,30 however the ultra-low φc measured here is, to the best of our knowledge, the lowest value ever reported in a carbon nanotube composite material.

Nanotubes Orientation Inside the Networks Polarized Raman spectroscopy has been previously used to assess the degree of alignment of nanotubes inside a composite. 31–33 Because of the different geometries (2D planar vs 3D 6


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pattern) and the very different degree of confinement in the 3 types of networks investigated (3D nano vs 3D micro vs 2D), we may expect different tube orientations. Indeed nanotube orientation and alignment can dramatically affect the percolation and the conductivity of a network of high aspect ratio objects. 34,35 Polarized Raman spectroscopy was therefore performed to estimate the orientation of the nanotubes inside each network, by polarizing the laser beam in both the vertical (out-of-plane) and horizontal (in-plane) directions with respect to the substrate (see Figure 3a). The intensity of the Raman shift is expected to become stronger when more tubes are aligned with the direction of polarization of the beam. 36–38 The intensity of the Raman shift of the nanotubes G band (≈1600 cm−1 ) 39 with the incoming polarization in both in-plane (horizontal) and out-of-plane (vertical) directions is shown in Figure 3b for the three types of networks at nanotube loadings slightly above their percolation threshold (see Methods section). These results indicate a clear difference in preferred tube orientation between the random networks and the two 3D networks. This can be quantified by calculating the ratio R of the vertical to horizontal Raman shift intensity in all three cases. For R=1 there is no preferred orientation in the network (equal amount of tubes oriented in and out-of-plane); for 0 < R < 1, the tubes are in majority oriented in the plane of the film (a lower value means more nanotubes are oriented in-plane); and for R > 1 a larger amount of tubes are oriented vertically in the out-of-plane direction. The intensity of the signal was stronger in the horizontal direction (R ≈ 0.48 ± 0.14) in the random network (Figure 3c), which indicates a preferred alignment of the tubes in the plane of the film. By contrast, the Raman signal was stronger when the beam was polarized vertically in both the 3D nano and 3D micro networks. The ratios were R ≈ 1.42 ± 0.35 and R ≈ 1.58 ± 0.36 in the 3D nano and 3D micro networks respectively, as represented in Figure 3c, and indicate a preferred vertical (out-of-plane) orientation of the tubes. These results are summarized in Table 1, and a schematic of the nanotubes’ orientations in each network geometry, is shown in Figure 3d, e, and f for the nano, the micro and the random networks.

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DISCUSSION The ultra-low percolation thresholds measured in the 3D confined nanoscale networks cannot be explained in terms of classical percolation theory, which predicts that the statistical percolation threshold φstat can be approximated by φstat = 1/AR for high aspect ratio fillers. 40 Taking into account diameter (≈0.7–0.9 nm) and length distributions (≈500–1000 nm) for the tubes used in this study, this gives φstat ≈0.07–0.18 wt%. However, this statistical value of percolation does not take into account the network dimensionality, tubes orientation and confinement effects. A discussion of how these parameters can affect φc , and explain our results, is now presented.

Nanotubes Orientation and Network Dimensionality The orientation of the nanotubes with respect to the direction in which the conductivity is measured is an important factor to take into account. Simulations have shown that the network resistivity decreases significantly when the nanotubes are more aligned with the direction of measurement θm (see Figure 4a). 35 Moreover, a certain degree of misalignment of the nanotubes between themselves (θa ≈ 40◦ ) was found to enhance the network conductivity, compared to the extreme cases of nanotubes perfectly well aligned (θa = 0◦ ) and nanotubes randomly oriented (θa = 90◦ ). 41 The inset in Figure 4a shows that the probability to reach percolation increases more rapidly when the nanotubes are aligned with the direction in which the conductivity (or resistivity as in Figure 4a) is measured. Polarized Raman data, shown in Figure 3c and summarized in Table 1, indicated that a combination of horizontally and vertically aligned nanotubes was observed in all networks. However, this occurred in very different proportions in 2D and 3D networks, as indicated by the different R values measured, with a majority of tubes aligned in the out-of-plane direction (and therefore in the direction of electrical current measurement) in the micro and nanoconfined networks. By contrast, the preferred alignment of nanotubes was in-plane in the 2D network, and perpendicular to the direction of current measurement. Therefore, according 10


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to the simulations shown in Figure 4a, the preferred out-of-plane tube orientation should lower the percolation threshold in the 3D micro and nano-networks, which is corroborated by our experimental results. Note that the relative proportion of in-plane and out-of-plane orientated tubes also explains the more 3-dimensional geometry of the confined networks, which is corroborated by the experimental value of the exponent t extracted from equation 3. Indeed, the critical exponent t is commonly accepted to represent the dimensionality of the network. 20,42,43 A log-log representation of σ vs. (φ-φc ) is shown in Figure 5, in which the slope represents the exponent t in equation 3. Our experimental results indicated that t=1.3 in the case of the random network, whereas t=1.99 for the micro network, measured just above the percolation threshold. In the case of macroscopic or large enough samples, it is generally accepted that a value of t ≈ 1.3 represents a 2D network, 44 and a value of 1.9–2.0 describes a 3D network. 45 However, the nanoscale network gave a value of t=1.65, in between that of the random network and of the micro-network. Critical conductivity exponents t varying between 1.50 and 1.72 have previously been reported by Monte Carlo simulations in small size 3D networks, suggesting that our experimental value of t=1.65 is likely due to confinement size effects, compared to the much larger micro-network. 46–48 The values of t and the percolation thresholds φc are summarized in Table 1 for the different types of networks.

Effect of confinement on the network resistivity and φc The 3-dimensionality of the confined networks is explained by the nanoscale flow filling of the micro and nano-cavities by nanoimprinting from a viscous composite melt. 49–51 This was confirmed by taking atomic force microscopy (AFM) cross-sections (Figure S1) of partially filled cavities in which the flow of the material was halted by cooling it down to room temperature after a short imprint time (5-10 sec). As shown in Figure S1a-c, the composite melt is re-organized from an in–plane 2D configuration at the start of the imprinting, to a 3D configuration by vertical flow along the cavities of the mold during patterning. The nanotubes 12


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than the volume occupied by the nano network (Figure S2c), in which φc is nearly one order of magnitude less. Moreover, a reduction in network lateral dimension and height favor the formation of a conducting pathway in which fewer nanotubes are needed to reach φc . As determined by Raman measurements (Figure 3), the tubes vertical alignment is almost identical (a little stronger in the micro-network) in both 3D networks, however the volume occupied by the nano network is much smaller than the one occupied by the micro network (see Figure S2b,c), resulting in greater confinement of the nanotubes within the composite. As will be shown thereafter, the smaller volume and increased confinement in the nanonetwork enable formation of conducting percolated pathways at much lower loadings and with fewer contact resistances, thereby resulting in the reduction in φc observed.

From the electrical conductivity σ0 , which was experimentally determined from equation 3, we now calculate the network resistivity R0 , which takes into account the resistance of nanotube bundles and/or of the contact between nanotubes or bundles in the 3D networks: 27,52 R0 = σ0 · L · φtc

−1

(4)

where L is the nanotube length. From the value of R0 extracted just above percolation, we estimated the number of nanotube bundles necessary to reach percolation, and the difference in φc , between the 3D micro and nano-networks. Since we are dealing with very low nanotube concentrations (10−5 − 10−4 wt%), we make the assumption that only small diameter bundles are present inside the networks, and that the main contribution to the network resistance is the contact resistance between nanotubes and bundles. Taking values of contact Rc =200-532 kΩ, and tube Rt =8.5–100 kΩ/µm resistances for single wall carbon nanotubes and small bundles of 10-20 nm diameter from literature yields nnano in the range 9.8·103 –2.9·104 nanotubes for the nano-network, and nmicro in the range of 6.2·104 –1.8·105 nanotubes for the micronetwork. 53–55 The difference of roughly one order of magnitude in φc corresponds to the 14


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difference in the number of nanotubes close to percolation in the two confined networks: nnano ≈ (φnano /φmicro ) · nmicro . Figure 4c,d illustrates the micro and nano networks, with the c c presence of a higher number of nanotube-nanotube contact resistances in the micro network compared to the nano network, resulting in a higher resistance and a higher percolation threshold. Moreover, as shown in Figure S3, 3D confinement also affects the charge conduction mechanism in the network, resulting in a more ohmic conduction (slope ≈ 1.0 and linear J–V curves) in both 3D nano and micro networks (Figure S3a,b). This is indicative of a continuous network formation with low energy barrier (and low resistance) for electron tunneling between nanotubes and small diameter bundles in the 3D confined networks. In the 2D random network (Figure S3c) however, there is a linear increase of current density at low voltages which is indicative of tunneling between tubes, and a non-ohmic conduction for voltages above 0.1 V in the form J ≈ Vp with p=2–3, characteristic of space charge limited current. 56 Near ohmic conduction has been previously reported in dense and highly percolated networks were the number of metal-metal contacts is high enough to bypass the higher resistance Schottky barriers at semiconducting–metallic junctions, and give rise to a linear current-voltage characteristic. 57 However, it has not been reported in networks with very low nanotube concentrations as used here. These results therefore demonstrate that a greater amount of tubes aligned in the direction of current flow is necessary to decrease φc , but that moreover network confinement (e.g. smaller volume) enables further reduction in φc due to a reduced network resistivity and less nanotubes needed to produce percolation.

CONCLUSION We have shown that it is possible to significantly reduce the percolation threshold of composites consisting of single walled carbon nanotubes in polymer by using directed network 15


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formation in nanoscale domains, a cost-effective and easily scalable technique. Electrical conductivity measurements, polarized Raman spectroscopy and visualization of nanoscale flow by AFM, showed that the re-orientation of nanotubes from in-plane to the out-of-plane direction by formation of 3D confined networks help tube alignment with the direction of current flow and reduce φc . Small nanoscale domains also enable a more quasi-ohmic conduction compared to a random network. We moreover showed that increased nanoscale confinement, and reduced network volume, is responsible for a reduction in network resistance and the strong decrease in φc . The reduction in percolation threshold compared to a composite in which the nanotubes are randomly mixed can be tuned by selecting the pattern dimensions, and the degree of confinement. We believe these results are of importance for applications where a low amount of nanotubes is desirable in order to ease processing, reduce materials cost and enhance electrical properties.

METHODS Materials The nanotubes used in this study were produced by the CoMoCAT process and were mostly (6,5) single-walled carbon nanotubes, ≈760 nm long and ≈0.8–1.0 nm diameter, with more than 50 % semiconducting tubes as specified by the distributor (Sigma Aldrich). The polystyrene powder used had a molecular weight of Mw =50000 (Polysciences Inc.).

SWNT/polymer Processing The SWNTs were dispersed in orthodichlorobenzene (ODCB) at different concentrations before being mixed with 0.5 wt.% polystyrene in a 1:1 ODCB:chloroform (CF) solution. This solution was deposited on conducting p-doped silicon substrate by spin-coating at 5000 rpm in order to form a ≈25 nm thin layer, leading to a smooth bi-layer film as shown in Figure 1a. The second layer was made by spin-=coating a film from a solution of polystyrene 16


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(Mw =50kg/mol) in toluene with 2-6 wt% polystyrene depending on the patterns to be imprinted, resulting in a total thickness of 75 nm for the nano-patterns, and 390 nm for the micro-patterns. In the case of the random network, the deposition consisted in a single ≈850 nm thick layer of the nanotubes-containing PS solution deposited by spin coating. The micro and nano networks were made by patterning the SWNT/PS films by imprinting at 150◦ C and 15 bar pressure for about 10 minutes, as shown in Figure 1b and as explained in detail elsewhere. 22,25 The residual layer in between the pillars was ≈10 nm, as determined by atomic force microscopy (AFM).

Network Formation A two-layer film containing a first layer with SWNTs, and a second layer of pure polymer was imprinted (Obducat NIL2.5) from a polydimethylsiloxane (PDMS) mold at 150 ◦ C, and a pressure of 15 bar. The composites were cooled down to 35 ◦ C before demolding. The molds were prepared by mixing of PDMS and its crosslinker onto a patterned Si master and curing it at 150 ◦ C for 5 hours.

Characterization The composites were characterized by optical microscopy (Olympus BX51) and AFM (Veeco Multimode) to measure the patterns dimensions and the thicknesses of the films. A custom made flexible electrode system was used to characterized the electrical conductivity of the composites.

Conductivity Measurement: The electrical contacts were positioned so that electrical conductivity was measured through the film thickness. The conductive substrate was used as the bottom electrode, while a flexible electrode was used as the top contact. The flexible electrode was made of a gold

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evaporated PDMS slab. The flexibility of the top electrode allowed for a better conformal contact with the top of the patterns than what can be achieved using a rigid electrode. 26 The contact area was measured using optical microscopy. A voltage was applied between the top and the bottom of the films and the resulting current was measured using a source meter (Keithley 2450).

Raman Spectroscopy: Polarized Raman spectroscopy was performed with a 633 nm laser of 20 mW power with a spot size of 0.86 µm on a Raman spectrometer and microscope (Renishaw inVia). Over 150 measurements were performed for each type of network, targeting the G band of the carbon nanotubes at ≈1600 cm−1 . 39 In order to obtain similar laser intensities for both polarization, the polarizing filters were kept in the same configuration (both incoming and outgoing light uses normal polarization) for all measurements. The laser spot was accurately placed on the samples by observation through a magnified image using the software WiRE (from Renishaw), and the samples were rotated to change the direction of polarization relative to the sample orientation (horizontal or vertical). Each measurements for the micro and random networks consisted in 10 successive accumulations of 5 s exposure each. The nano network showed a much weaker signal, and required instead 600 accumulations of 1 s exposure each. The Raman signal (Figure 3b) was well defined and reproducible with an average signal to noise ratio between 5 and 15 for all samples. Different concentrations were used for each of the samples in order to be above their respective percolation threshold. The micro network had a SWNT concentration of 2·10−4 wt.%, while the nano-network and the random network had concentrations of 1.2 · 10−2 wt.% and 3 · 10−2 wt.% respectively.

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Supporting Information Supporting Information is available online from the ACS Online Library or from the author. It exposes in more details the mold filling mechanism, the effects of confinement on the percolation threshold, and gives more information about the electrical conductivity measurements.

Acknowledgements We thank the Baltic Foundation and the Kempe Foundation for financial support. D. R. B. also thanks a Young Researcher Career Award from Umeå University for support of this work.

References 1. Seo, M.; Kim, H.; Kim, Y. H.; Na, J.; Lee, B. J.; Kim, J. J.; Lee, I.; Yun, H.; McAllister, K.; Kim, K. S.; Jeong, G. H.; Kim, G. T.; Lee, S. W. Fabrication and Electrical Properties of Single Wall Carbon Nanotube Channel and Graphene Electrode Based Transistors Arrays. Appl. Phys. Lett. 2015, 107, 033103. 2. Arici, E.; Karazhanov, S. Carbon Nanotubes for Organic/Inorganic Hybrid Solar Cells. Mater. Sci. Semicond. Process. 2016, 41, 137–149. 3. Meng, Y.; Xin, G.; Nam, J.; Cho, S. M.; Chae, H. Electrospray Deposition of Carbon Nanotube Thin Films for Flexible Transparent Electrodes. J. Nanosci. Nanotechnol. 2013, 13, 6125–6129. 4. Kang, L.; Hu, Y.; Zhong, H.; Si, J.; Zhang, S.; Zhao, Q.; Lin, J.; Li, Q.; Zhang, Z.; Peng, L.; Zhang, J. Large-Area Growth of Ultra-High-Density Single-Walled Carbon Nanotube Arrays on Sapphire Surface. Nano Res. 2015, 8, 3694–3703.

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5. Sundramoorthy, A. K.; Wang, Y.-C.; Gunasekaran, S. Low-Temperature Solution Process for Preparing Flexible Transparent Carbon Nanotube Film for Use in Flexible Supercapacitors. Nano Res. 2015, 8, 3430–3445. 6. Pike, G. E.; Seager, C. H. Percolation and Conductivity: a Computer Study. I. Phys. Rev. B. 1974, 10, 1421. 7. Kilbride, B. E.; Coleman, J. N.; Fraysse, J.; Fournet, P.; Cadek, M.; Drury, A.; Hutzler, S.; Roth, S.; Blau, W. J. Experimental Observation of Scaling Laws for Alternating Current and Direct Current Conductivity in Polymer-Carbon Nanotube Composite Thin Films. J. Appl. Phys. 2002, 92, 4024–4030. 8. Blanchet, G. B.; Subramoney, S.; Bailey, R. K.; Jaycox, G. D.; Nuckolls, C. SelfAssembled Three-Dimensional Conducting Network of Single-Wall Carbon Nanotubes. Appl. Phys. Lett. 2004, 85, 828–830. 9. Hecht, D.; Hu, L.; Grüner, G. Conductivity Scaling with Bundle Length and Diameter in Single Walled Carbon Nanotube Networks. Appl. Phys. Lett. 2006, 89, 133112. 10. Rouhi, N.; Jain, D.; Burke, P. J. High-Performance Semiconducting Nanotube Inks: Progress and Prospects. ACS Nano 2011, 5, 8471–8487. 11. Abeygunasekara, W. L.; Hiralal, P.; Samaranayake, L.; Chien, C.-T.; Kumar, A.; Flewitt, A. J.; Karunaratne, V.; Amaratunga, G. A. J. Incorporating Semiconducting Single-Walled Carbon Nanotubes As Efficient Charge Extractors in Organic Solar Cells. Appl. Phys. Lett. 2015, 106, 123305. 12. Lee, D.; Lee, B.-H.; Yoon, J.; Ahn, D.-C.; Park, J.-Y.; Hur, J.; Kim, M.-S.; Jeon, S.B.; Kang, M.-H.; Kim, K.; Lim, M.; Choi, S.-J.; Choi, Y.-K. Three-Dimensional FinStructured Semiconducting Carbon Nanotube Network Transistor. ACS Nano 2016, 10, 10894–10900.

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Page 20 of 27

Page 21 of 27

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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13. Liu, L.; Stanchina, W. E.; Li, G. Effects of Semiconducting and Metallic Single-Walled Carbon Nanotubes on Performance of Bulk Heterojunction Organic Solar Cells. Appl. Phys. Lett. 2009, 94, 233309. 14. Bao, H.-D.; Sun, Y.; Xiong, Z.-Y.; Guo, Z.-X.; Yu, J. Effects of the Dispersion State and Aspect Ratio of Carbon Nanotubes on Their Electrical Percolation Threshold in a Polymer. J. Appl. Polym. Sci. 2013, 128, 735–740. 15. Nakaramontri, Y.; Kummerlöwe, C.; Nakason, C.; Vennemann, N. The Effect of Surface Functionalization of Carbon Nanotubes on Properties of Natural Rubber/Carbon Nanotube Composites. Polym. Compos. 2015, 36, 2113–2122. 16. Yan, D.-X.; Huang, H.-D.; Gao, J.-F.; Dai, K.; Zhang, W.-Q.; Li, Z.-M. A Conductive Carbon Nanotube-Polymer Composite Based on a Co-continuous Blend. J. Macromol. Sci., Part B 2013, 52, 167–177. 17. Sheng, P.; Sichel, E. K.; Gittleman, J. I. Fluctuation-Induced Tunneling Conduction in Carbon-Polyvinylchloride Composites. Phys. Rev. Lett. 1978, 40, 1197–1200. 18. Skákalová, V.; Dettlaff-Weglikowska, U.; Roth, S. Electrical and Mechanical Properties of Nanocomposites of Single Wall Carbon Nanotubes with PMMA. Synth. Met. 2005, 152, 349–352. 19. Musumeci, A. W.; Silva, G. G.; Liu, J.-W.; Martens, W. N.; Waclawik, E. R. Structure and Conductivity of Multi-Walled Carbon Nanotube/Poly(3-hexylthiophene) Composite Films. Polymer 2007, 48, 1667–1678. 20. Bauhofer, W.; Kovacs, J. Z. A Review and Analysis of Electrical Percolation in Carbon Nanotube Polymer Composites. Compos. Sci. Technol. 2009, 69, 1486–1498. 21. Throckmorton, J. A.; Watters, A. L.; Geng, X.; Palmese, G. R. Room Temperature Ionic

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ACS Nano

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Liquids for Epoxy Nanocomposite Synthesis: Direct Dispersion and Cure. Compos. Sci. Technol. 2013, 86, 38–44. 22. Barbero, D. R.; Boulanger, N.; Ramstedt, M.; Yu, J. Nano-Engineering of SWNT Networks for Enhanced Charge Transport at Ultralow Nanotube Loading. Adv. Mater. 2014, 26, 3111–3117. 23. Biswas, S.; Drzal, L. T. Multilayered Nanoarchitecture of Graphene Nanosheets and Polypyrrole Nanowires for High Performance Supercapacitor Electrodes. Chem. Mater. 2010, 22, 5667–5671. 24. Lin, Y.; Dong, X.; Liu, S.; Chen, S.; Wei, Y.; Liu, L. Graphene–Elastomer Composites with Segregated Nanostructured Network for Liquid and Strain Sensing Application. ACS Appl. Mater. Interfaces 2016, 8, 24143–24151. 25. Barbero, D. R.; Saifullah, M. S. M.; Hoffmann, P.; Mathieu, H. J.; Anderson, D.; Jones, G. A. C.; Welland, M. E.; Steiner, U. High-Resolution Nanoimprinting with a Robust and Reusable Polymer Mold. Adv. Funct. Mater. 2007, 17, 2419–2425. 26. Skrypnychuk, V.; Wetzelaer, G.-J. A. H.; Gordiichuk, P. I.; Mannsfeld, S. C. B.; Herrmann, A.; Toney, M. F.; Barbero, D. R. Ultrahigh Mobility in an Organic Semiconductor by Vertical Chain Alignment. Adv. Mater. 2016, 28, 2359–2366. 27. Barbero, D. R.; Stranks, S. D. Functional Single-Walled Carbon Nanotubes and Nanoengineered Networks for Organic- and Perovskite-Solar-Cell Applications. Adv. Mater. 2016, 28, 9668–9685. 28. Marquardt, D. W. An Algorithm for Least-Squares Estimation of Nonlinear Parameters. J. Soc. Ind. Appl. Math. 1963, 11, 431–441. 29. Regev, O.; ElKati, P. N. B.; Loos, J.; Koning, C. E. Preparation of Conductive Nanotube–Polymer Composites Using Latex Technology. Adv. Mater. 2004, 16, 248–251. 22


Page 22 of 27

Page 23 of 27

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ACS Nano

30. Bryning, M. B.; Islam, M. F.; Kikkawa, J. M.; Yodh, A. G. Very Low Conductivity Threshold in Bulk Isotropic Single-Walled Carbon Nanotube-Epoxy Composites. Adv. Mater. 2005, 17, 1186–1191. 31. Gommans, H. H.; Alldredge, J. W.; Tashiro, H.; Park, J.; Magnuson, J.; Rinzler, A. G. Fibers of Aligned Single-Walled Carbon Nanotubes: Polarized Raman Spectroscopy. J. Appl. Phys. 2000, 88, 2509–2514. 32. Rao, A. M.; Jorio, A.; Pimenta, M. A.; Dantas, M. S. S.; Saito, R.; Dresselhaus, G.; Dresselhaus, M. S. Polarized Raman Study of Aligned Multiwalled Carbon Nanotubes. Phys. Rev. Lett. 2000, 84, 1820–1823. 33. Liu, P.; Liu, L.; Zhang, Y. Alignment Characterization of Single-Wall Carbon Nanotubes by Raman Scattering. Phys. Lett. A 2003, 313, 302–306. 34. Du, F.; Fischer, J. E.; Winey, K. I. Effect of Nanotube Alignment on Percolation Conductivity in Carbon Nanotube/Polymer Composites. Phys. Rev. B 2005, 72 . 35. Behnam, A.; Guo, J.; Ural, A. Effects of Nanotube Alignment and Measurement Direction on Percolation Resistivity in Single-Walled Carbon Nanotube Films. J. Appl. Phys. 2007, 102, 044313. 36. Haggenmueller, R.; Gommans, H. H.; Rinzler, A. G.; Fischer, J. E.; Winey, K. I. Aligned Single-Wall Carbon Nanotubes in Composites by Melt Processing Methods. Chem. Phys. Lett. 2000, 330, 219–225. 37. Wang, Q.; Dai, J.; Li, W.; Wei, Z.; Jiang, J. The Effects of CNT Alignment on Electrical Conductivity and Mechanical Properties of SWNT/Epoxy Nanocomposites. Compos. Sci. Technol. 2008, 68, 1644–1648. 38. Dai, J.; Wang, J.; Mu, X.; Chen, X. Comparative Study on Electrical Properties of

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Orientated Carbon Nanotubes/Epoxy Composites. J. Appl. Polym. Sci. 2012, 124, 647– 653. 39. Dresselhaus, M.; Dresselhaus, G.; Saito, R.; Jorio, A. Raman Spectroscopy of Carbon Nanotubes. Phys. Rep. 2005, 409, 47–99. 40. Balberg, I.; Anderson, C. H.; Alexander, S.; Wagner, N. Excluded Volume and Its Relation to the Onset of Percolation. Phys. Rev. B 1984, 30, 3933. 41. Ackermann, T.; Neuhaus, R.; Roth, S. The Effect of Rod Orientation on Electrical Anisotropy in Silver Nanowire Networks for Ultra-Transparent Electrodes. Sci. Rep. 2016, 6 . 42. Hu, L.; Hecht, D. S.; Grüner, G. Percolation in Transparent and Conducting Carbon Nanotube Networks. Nano Lett. 2004, 4, 2513–2517. 43. Chang, T.-E.; Kisliuk, A.; Rhodes, S. M.; Brittain, W. J.; Sokolov, A. P. Conductivity and Mechanical Properties of Well-Dispersed Single-Wall Carbon Nanotube/Polystyrene Composite. Polymer 2006, 47, 7740–7746. 44. Li, J.; Zhang, S.-L. Conductivity Exponents in Stick Percolation. Phys. Rev. E 2010, 81, 021120. 45. Stauffer, D.; Aharony, A. Introduction to Percolation Theory; Taylor & Francis, 1992. 46. Webman, I.; Jortner, J.; Cohen, M. H. Numerical Simulation of Electrical Conductivity in Microscopically Inhomogeneous Materials. Phys. Rev. B 1975, 11, 2885. 47. Kirkpatrick, S. Percolation and Conduction. Rev. Mod. Phys. 1973, 45, 574. 48. Onizuka, K. Computer Experiment on a 3D Site Percolation Model of Porous MaterialsIts Connectivity and Conductivity. J. Phys. Soc. Jpn. 1975, 39, 527–535.

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Page 24 of 27

Page 25 of 27

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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49. Natale, G.; Ausias, G.; Férec, J.; Heuzey, M. C.; Carreau, P. J. Modeling Interactions in Carbon Nanotube Suspensions: Transient Shear Flow. J. Rheol. 2016, 60, 1069–1083. 50. Park, J. H.; Joo, Y. L. Tailoring Nanorod Alignment in a Polymer Matrix by Elongational Flow Under Confinement: Simulation, Experiments, and Surface Enhanced Raman Scattering Application. Soft Matter 2014, 10, 3494. 51. Eken, A. E.; Tozzi, E. J.; Klingenberg, D. J.; Bauhofer, W. Combined Effects of Nanotube Aspect Ratio and Shear Rate on the Carbon Nanotube/Polymer Composites. Polymer 2012, 53, 4493–4500. 52. Foygel, M.; Morris, R. D.; Anez, D.; French, S.; Sobolev, V. L. Theoretical and Computational Studies of Carbon Nanotube Composites and Suspensions: Electrical and Thermal Conductivity. Phys. Rev. B 2005, 71, 104201. 53. Yao, Z.; Kane, C. L.; Dekker, C. High-Field Electrical Transport in Single-Wall Carbon Nanotubes. Phys. Rev. Lett. 2000, 84, 2941–2944. 54. Topinka, M. A.; Rowell, M. W.; Goldhaber-Gordon, D.; McGehee, M. D.; Hecht, D. S.; Gruner, G. Charge Transport in Interpenetrating Networks of Semiconducting and Metallic Carbon Nanotubes. Nano Lett. 2009, 9, 1866–1871. 55. Znidarsic, A.; Kaskela, A.; Laiho, P.; Gaberscek, M.; Ohno, Y.; Nasibulin, A. G.; Kauppinen, E. I.; Hassanien, A. Spatially Resolved Transport Properties of Pristine and Doped Single-Walled Carbon Nanotube Networks. J. Phys. Chem. C 2013, 117, 13324–13330. 56. Palumbo, M.; Lee, K. U.; Ahn, B. T.; Suri, A.; Coleman, K. S.; Zeze, D.; Wood, D.; Pearson, C.; Petty, M. C. Electrical Investigations of Layer-by-Layer Films of Carbon Nanotubes. J. Phys. D: Appl. Phys. 2006, 39, 3077âĂŞ3085. 57. Mustonen, T.; Mäklin, J.; Kordás, K.; Halonen, N.; Tóth, G.; Saukko, S.; Vähäkangas, J.; Jantunen, H.; Kar, S.; Ajayan, P. M.; Vajtai, R.; Helistö, P.; Seppä, H.; Moilanen, H. 25


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Controlled Ohmic and Nonlinear Electrical Transport in Inkjet-Printed Single-Wall Carbon Nanotube Films. Phys. Rev. B 2008, 77 .

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The graphic on the left shows the reduction in percolation threshold with increased confinement going from macro-scale networks to nano-networks. 26x7mm (300 x 300 DPI)


Ultralow Percolation Threshold in Nanoconfined Domains - ACS Nano

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