Open Access
Add to BibSonomy
Abstract
Anisotropic plasmonic films are a desirable material for many optoelectronic applications. Here, we propose a method to align silver nanowires (AgNWs) with the help of uniaxial nematic alignment of cellulose nanocrystal (CNC) liquid crystals (LCs) that can preserve their LC orientation in solid film. AgNWs are doped into uniaxial nematic CNC LCs, where AgNWs are oriented parallel to the director of shear- aligned CNCs without aggregation. The AgNWs orientations are determined by polarized optical and dark field microscopic images. The alignment of AgNWs is characterized by the scalar order parameter S, and the measured S around 0.59 for aligned AgNWs presents an improved anisotropy with the assistance of uniaxial nematic CNC LCs. The electrical property of aligned AgNWs is examined by the four-probe method and exhibits the maximum ratio of anisotropic sheet resistance around 5, consistent with the simulated percolation probability performance using the Monte Carlo computation. Our results show that the uniaxial nematic CNC LCs can act as an effective template in aligning AgNWs, which is compatible with 3D printing and microfluidics, and allows for the preparation of low-cost, innovative optical materials and devices.
© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Aligned anisotropic plasmonic nanoparticles such as silver nanowires (AgNWs) attract great interest due to the ability to transfer anisotropic properties from the nanoscale to the device scale [1], finding a widespread application in transparent electrodes [2], antennas [3], sensors [4] and surface enhanced Raman spectroscopy (SERS) [5]. To obtain a high degree of orientation, there are many viable approaches including Langmuir-Blodgett [6], external electric field [7], blown bubble [8], brush coating [9], shearing coating [10], liquid crystals (LCs) [11] and so on. LCs can serve as a smart template to assemble nanoparticles and allow for dynamic response to external stimuli [12]. Nanoparticles doped in traditional thermotopic LCs only maintain its LC orientation in fluid and typically sediment on a timescale of several days. Cellulose nanocrystals (CNCs) LCs can act as a robust host in assembling nanoparticles since its LC orientations can be preserved in solid films after a drying process [13]. LCs primary advantages over other alignment techniques are facile fabrication due to self-assembled long-range ordering and the potential for local manipulation through topological defects [14] and elasticity. CNCs from hydrolyzing native cellulose exhibit the rod-like shape with surface charge [15], and can form LCs when the concentration of CNCs above the critical value [16]. CNCs generally exhibit helical alignment LCs with left-handed Bragg structure [17], and can be uniaxial nematic alignment LCs with reduced Debye length [18]. The self-assembly of gold nanorods with smaller aspect ratio in CNC LCs [19,20] is well understood, but larger aspect ratio nanoparticles are more difficult to disperse uniformly without aggregation. Guang chu et al doped AgNWs into helical alignment CNC LCs and fabricated chiral Bragg AgNWs films with plasmonic optical performance [21]. Helical alignment CNC LCs are not an ideal template for preparing aligned AgNWs since the intrinsic helical orientation requires complex methods to unwind the spiral compared with uniaxial nematic alignments [22]. Uniaxial nematic ordered CNCs is the natural to use in preparing aligned films, while the alignment of AgNWs in uniaxial nematic CNC LCs is still an open question. Complex microfluidic systems can achieve stronger alignment [23], however our CNC LC system is simple and scalable.
In this paper, we prepare aligned AgNWs through uniaxial nematic CNC LCs and shearing forces. AgNWs are doped into uniaxial nematic ordered CNC LCs, where AgNWs are oriented parallel to the direction of CNCs without aggregation. AgNW-uniaxial nematic ordered CNCs are aligned by shearing forces and characterized by polarized optical microscope and dark field microscope. The scalar order parameter S for the AgNWs is calculated to be 0.59 from the absorption spectra. The electrical property of aligned AgNWs is examined by the four-probe method, and the measured maximum sheet resistance ratio is around 5. The percolation probability of aligned AgNWs is further analyzed using the Monte Carlo simulation and exhibits an improved percolation threshold in the direction perpendicular to the orientation of AgNWs with higher order parameter.
2. Results and discussion
The TEM image of CNCs in Fig. 1(a) shows the rod-like shape that is a few hundreds of nanometers long and 5∼20 nm wide. The SEM image of AgNWs (Fig. 1(b)) presents that the typical length L is around 50 μm and the diameter D is 90 nm. Using the finite difference time domain (FDTD) method, the extinction cross-section of AgNWs is simulated and shown in Fig. 1(c). When the polarization for incident light is perpendicular to the long axis of AgNWs, the extinction cross-section of nanowires ${\sigma _ \bot }$ (black line) has a transverse surface plasmon resonance peak (TSPR) around 438 nm; and the extinction cross-section ${\sigma _\parallel }$ (red line) for the parallel incident polarization presents no observable longitudinal surface plasmon peak (LSPR) in visible range. AgNWs doped uniaxial nematic ordered CNCs exhibit the typical Schlieren texture (Fig. 1(d) and (e)), when the orientation of CNCs nc is parallel to the slow axis γ of the standard “red” 530 nm λ-plate, areas exhibit blue; and areas become yellow when ${{\mathbf n}_\textrm{c}} \bot {\mathbf \gamma }$ since CNCs have a positive birefringence. The orientation of AgNWs ns can be deduced from the dark field microscope image (Fig. 1(f)), where the ns in blue areas is perpendicular to the polarization P of the polarizer since the TSPR has a peak at 438 nm, while bright white areas correspond to ns parallel to P because there are no LSPR peaks in the visible range.
Fig. 1. (a) TEM image of CNCs. (b) SEM image of AgNWs. (c) Simulated extinction cross section ${\sigma _\parallel }$ (red line) and ${\sigma _ \bot }$ (black line) of the AgNW when the polarization for incident light is parallel and vertical to the long axis of AgNWs respectively. Polarized optical microscopy images of (d) AgNWs doped in uniaxial nematic ordered CNCs, and (e) with a phase compensator (530 nm λ-plate). (f) Dark field microscopic image of AgNWs doped in uniaxial nematic ordered CNCs. P and A indicate the polarizations of the polarizer and the analyzer respectively; γ denotes the slow axis of the λ-plate.
Figure 2(a) and (f) depict the formation process of aligned AgNWs in uniaxial nematic ordered CNCs and isotropic ethanol respectively, where k denotes the direction for shearing forces. Aligned AgNWs with CNCs in Fig. 2(b) exhibits the uniform bright color, inserting the 530 nm phase compensator produces a blue color indicating that the orientation of CNC nc is parallel to k (${{\mathbf n}_\textrm{c}}\parallel {\mathbf k}$). Dark field microscope images in Fig. 2(d) and (e) show blue and bright color with ${{\mathbf n}_\textrm{s}}\parallel {\mathbf P}$ and ${{\mathbf n}_{\mathbf s}} \bot {\mathbf P}$ respectively, confirming ns is parallel to k. While for AgNWs in ethanol, Fig. 2(g) is dark with some scattering light of AgNWs, and Fig. 2(h) exhibits purple color due to the negligible birefringence. Dark field microscopic images (Fig. 2(i), (j)) show many aggregated domains and weak extinction color, indicating the random orientation of AgNWs.
Fig. 2. (a) Schematic of shearing AgNWs-uniaxial nematic ordered CNCs. (b), (c) Polarized optical microscopy images, and (d), (e) dark field microscope images of the aligned AgNWs with CNCs. (f) Schematic of shearing AgNWs-ethanol. (g), (h) Polarized optical microscopy images, and (i), (j) dark field microscope images of the aligned AgNWs without CNCs. k denotes the direction of shearing force; P and A indicate the polarization directions of the polarizer and the analyzer; γ depicts the slow axis of the λ-plate.
The quality of alignment for AgNWs along ns is characterized by the scalar order parameter S. Here S is theoretical analyzed using extinction cross-section $\sigma $ and absorbance $\alpha $ that can be deduced from the measured transmittance [24]. From Fig. 3(a), the orientation ${{\mathbf n}_\textrm{s}}$ of aligned AgNWs is parallel to z axis and a denotes the direction for the long axis of a single AgNW (yellow rod), when the polarization of incident light ${\mathbf E}$ is parallel to the orientation of AgNWs ${{\mathbf n}_\textrm{s}}$ (${\mathbf E}\parallel {{\mathbf n}_\textrm{s}}\parallel z$-axis), and the parallel absorbance ${\alpha _\parallel }$ is
Fig. 3. (a) Schematics for the theoretical analysis of scalar order parameter S, where ${{\mathbf n}_\textrm{s}}$ denotes the orientation of aligned AgNWs and a presents the direction for the long axis of the single AgNW. (b) The experimental setup for measuring the transmittance T of the aligned AgNWs (left), parallel and vertical transmittance (${T_\parallel }$, ${T_ \bot }$) are recorded by a spectrometer when P is parallel and perpendicular to k, respectively (right). (c) Measured transmittance (${T_\parallel }$, ${T_ \bot }$), and (d) calculated absorbance (${\alpha _\parallel }$, ${\alpha _ \bot }$) of aligned AgNWs with CNCs (red line) and without CNCs (blue line). (e) Calculated scalar order parameter S for aligned AgNWs with CNCs around S∼0.59, and the S of aligned AgNWs without CNCs is around 0.13. k denotes the direction of shearing force and P indicates the polarization directions of the polarizer.
Thus the absorbance ${\alpha _\parallel }$ can be written as
The electrical conductivity of aligned AgNWs is tested using the established four-probe method, schematically shown in Fig. 4(a), sheet resistance ${R_\parallel }$ and ${R_ \bot }$ are parallel and vertical to the direction of sliding direction k respectively. The measured sheet resistance of four batches aligned AgNWs with CNCs (Fig. 4(b)) for the volume of AgNWs $X = 15,20,25,30$ shows that the calculated anisotropic sheet resistance ratio $\eta = {{{R_ \bot }} / {{R_\parallel }}}$ (green line) reaches a maximum of $\eta \sim 5$ for $X = 25$. The measured sheet resistance of aligned AgNWs without CNCs (Fig. 4(c)) has a maximum ratio of ∼2.1 for $X = 20$. This shows a significant change in material performance due to the improved alignment of AgNWs in uniaxial nematic ordered CNCs.
Fig. 4. (a) The approach for measuring the electronic conductivity of aligned AgNWs, where sheet resistance ${R_\parallel }$ and ${R_ \bot }$ are oriented parallel and vertical to the sliding direction k, respectively. (b) Measured sheet resistance (${R_\parallel }$, ${R_ \bot }$) of four batches aligned AgNW with CNCs for the volume of AgNWs around $X = 15,20,25,30$, and (c) measured sheet resistance (${R_\parallel }$, ${R_ \bot }$) of aligned AgNW without CNCs. The green line presents the calculated anisotropic sheet resistance ratio $\eta = {{{R_ \bot }} / {{R_\parallel }}}$. (d) Simulated function between the scalar order parameter S and the FWHM of the distribution function $f(\theta )$ for AgNWs, and distribution functions of aligned AgNWs with CNCs (${f_{\textrm{w, CNCs}}}(\theta )$, red line) and without CNCs (${f_{\textrm{w/o, CNCs}}}(\theta )$, blue line) are depicted in the inset image. (e) Simulated AgNW network following ${f_{\textrm{w, CNCs}}}(\theta )$ with the number of AgNWs around $N = 100$ (left), $N = 200$ (middle), and $N = 300$ (right). (f), (g) Simulated percolation probabilities (${p_\parallel }$, ${p_ \bot }$) as a function of N for aligned AgNWs with ${f_{\textrm{w, CNCs}}}(\theta )$ and ${f_{\textrm{w/o, CNCs}}}(\theta )$ respectively, and the green line shows the percolation probability threshold around 0.77. (h) Calculated percolation probability difference $\rho = {p_\parallel } - {p_ \bot }$ for aligned AgNWs with CNCs (red line) and without CNCs (blue line) respectively.
To simulate the conductivity of the AgNWs, we need to find the distribution function $f(\theta )$ for AgNWs. The distribution function satisfies:
Assuming the distribution function $f(\theta )$ follows a Gaussian distribution $f(\theta ) = \frac{a}{{\sqrt {2\pi {\varsigma ^2}} }}{e^{\frac{{ - {\theta ^2}}}{{2{\varsigma ^2}}}}}$, a is the normalization factor and $\varsigma $ denotes the standard deviation [23]. It is difficult to obtain $f(\theta )$ by solving Eq. (6) and (7) directly, here we substitute the full width at half height ($\textrm{FWHM} = 2\sqrt {2\ln (2)} \varsigma $) of $f(\theta )$ within the range of $[40^\circ ,160^\circ ]$ into Eq. (7) to obtain the normalization factor a, and then substitute the calculated $f(\theta )$ into Eq. (6) to calculate the corresponding S. The simulated relationship between S and FWHM is shown in Fig. 4(d), where the FWHM is around 57° (red dot) for aligned AgNWs with CNCs, and the FWHM corresponding to aligned AgNWs without CNCs is around 118° (blue dot), thus the distribution function $f(\theta )$ of aligned AgNWs with CNCs and without CNCs are ${f_{\textrm{w, CNCs}}}(\theta ) = 5.95{e^{ - 2.80{\theta ^2}}}$, and ${f_{\textrm{w/o, CNCs}}}(\theta ) = 1.78{e^{ - 0.65{\theta ^2}}}$ respectively (see the inset image in Fig. 4(d)). The network of AgNWs can be randomly generated from the function $f(\theta )$, and continuous electronic routes are typically simulated by the reported computation in Mathematica [25]. In our simulation, the simulation range is $\textrm{3000} \times \textrm{3000 }$; the direction of sliding direction k is parallel to y axis; the aspect ratio L/D is around 500 from SEM image in Fig. 1(b) and the number of AgNWs is N. Clusters of electrically isolated AgNWs are shown in different colors. Figure 4(e) shows the generated aligned AgNW network with ${f_{\textrm{w, CNCs}}}(\theta ) = 5.95{e^{ - 2.80{\theta ^2}}}$, there are no continuous routes for $N = 100$ (left); when $N = 200$ there exhibits one continuous route (purple) along the y axis and no continuous routes along the x axis (middle); and with $N = 300$ the vast majority of nanowires are electrically connected (right). The percolation probability p of AgNW networks can be characterized by the Monte Carlo simulation, and the probability p is $p = {{{N_{con}}} / {{N_{total}}}}$, where ${N_{con}}$ is the number of the network possessing continuous paths and ${N_{total}}$ denotes the total number of networks generated [26]. ${p_\parallel }$ and ${p_ \bot }$ are determined by running the simulation for 100 times (${N_{total}} = 100$) for every N. Figure 4(f) shows the simulated ${p_\parallel }$ and ${p_ \bot }$ of aligned AgNW with CNCs as the function of N, and the corresponded percolation threshold number ${N_C}$ is ${N_{C,\parallel }}\sim 195$ and ${N_{C, \bot }}\sim 275$ since the percolation probability threshold is set as ${p_C} = 0.77$ (green line) [27]. When N is larger than 275, both ${p_\parallel }$ and ${p_ \bot }$ are above 0.77, and aligned AgNWs show continuous routes with the conductive mode both in x and y axis; while for N is smaller than 195, aligned AgNWs exhibits no continuous paths with the non-conductive mode along x and y axis. With $N = 195\sim 275$, ${p_\parallel }$ is above 0.77 but ${p_ \bot }$ is lower than 0.77 indicating that AgNWs form the continuous routes in y axis and do not form continuous routes in x axis, which may have the maximum of anisotropic sheet resistance ratio between x and y axis. As a comparison, the simulated ${p_\parallel }$ and ${p_ \bot }$ of aligned AgNW following ${f_{\textrm{w/o, CNCs}}}(\theta )$ in Fig. 4(g) exhibit the similar graph, and the percolation threshold number ${N_{C,\parallel }}\sim 180$ is close to ${N_{C, \bot }}\sim 195$, indicating AgNWs without CNCs almost have the same conductivity in x and y direction. The calculated difference $\rho = {p_\parallel } - {p_ \bot }$ is shown in Fig. 4(h), and aligned AgNWs with CNCs show the maximum difference is ${\rho _m} = 0.81$ at $N = 200 \in [195,275]$, while the difference $\rho $ is around 0.1 for $N \in [180,195]$ for aligned AgNWs without CNCs. The aligned AgNWs with uniaxial nematic ordered CNCs show around 8 times the anisotropic parameter ${\rho _m}$. Compared with other reports of aligning AgNWs through brush coating, the anisotropic ratio is around 1.41 [9], our uniaxial nematic alignment of CNC LCs increase the anisotropic ratio around 5 times. The FWHM of aligned AgNWs prepared by dip-coating is around 82° [28], and the scalar order parameter is around 0.43 [2]. Ye Xu used the more complex microfluidic method and prepared the aligned AgNWs with highest anisotropic ratio around 10 until now [23]. CNC LCs are also suitable for microfluidics [29], showing a potential application in preparing highly aligned AgNWs.The relationship between anisotropic percolation probability and the scalar order parameter S in the wide range of 0.067∼0.59 is also simulated by the Monte Carlo computation to evaluate its anisotropy more complete. Simulated percolation threshold number (${N_{C,\parallel }}$, ${N_{C, \bot }}$) is shown in Fig. 5(a), as a function of S, ${N_{C, \bot }}$ is increased more quickly than ${N_{C,\parallel }}$. The difference of percolation threshold number $\Delta {N_C} = {N_{C, \bot }} - {N_{C,\parallel }}$ in Fig. 5(c) blue line exhibits the positive relationship with S. The simulated difference of percolation probability $\rho $ is shown in Fig. 5(b), and the corresponding maximum difference ${\rho _m} = \max \textrm{ (}{p_\parallel } - {p_ \bot }\textrm{)}$ in $[{{N_{C,\parallel }},{N_{C, \bot }}} ]$ is presented in Fig. 5(c) red line. At larger S, the ${\rho _m}$ is also improved, confirming the improvement of anisotropic electrical property due to the higher alignment of AgNWs. For the S ranging from 0.29 to 0.59, the ${\rho _m}$ is also increased from 0.3 to 0.83, as the S of shear-aligned CNCs films is typically around 0.35∼0.65 [30], confirming shearing aligning AgNW-CNC LC compound materials can be served as an effective robust in aligning AgNWs.
Fig. 5. (a) Simulated percolation threshold number (${N_{C,\parallel }}$, ${N_{C, \bot }}$) as the function of the scalar order parameter S, and (b) calculated percolation probability difference $\rho $. (c) Calculated difference of percolation threshold number $\Delta {N_C}$ (blue line), and the corresponding maximum of difference percolation probability ${\rho _m}$ (red line).
3. Conclusion
In conclusion, we have doped AgNWs into uniaxial nematic ordered CNCs without large-scale aggregation, where the orientation of AgNWs is parallel to the direction of CNCs. AgNWs-uniaxial nematic ordered CNCs are uniformly aligned by shearing forces. Polarized optical and dark field microscopes are utilized to characterize the orientation of AgNW which is further characterized with the scalar order parameter S. Measured S of aligned AgNWs exhibits an improved alignment with the assistance of uniaxial nematic alignment of CNC LCs. The electrical property of aligned AgNWs is examined by the four-probe method, and the measured maximum of anisotropic sheet resistance ratio is around 5 that is in accordance with the theoretical analysis of percolation probability simulated by Monte Carlo computation. This low cost uniaxial nematic ordered CNC can act as an effective template allowing for aligning AgNWs and other nanowires or carbon nanotubes, and also is in principal compatible with 3D printing [31] and microfluidics [23,29], which may find a potential application in innovative optical materials and devices.
4. Experimental section
Uniaxial nematic alignment CNC LCs were prepared by hydrolysis and pH control according to established methods [18]. Briefly, 6.5 g degreasing cotton was dispersed in 70 mL of 65 wt % sulfuric acid and stirred at 46 ℃ in a water bath for 1 hour, and then 70 mL of deionized water was added to the resulting dispersion to quench the reaction. The CNC suspension was purified by centrifugation at 9000 rpm for 10 min several times. The resulting precipitant was under dialysis (MWCO 12000) for several days until the pH value reached 7. The CNC suspension was centrifuged at 12500 rpm for 40 min to remove impurities and the redundant solvent. The obtained 13wt % CNC sample showed a helical alignment, which was made uniaxial nematic alignment at pH∼10 by adding 6 μL of 2 mol/L NaOH into 100 μL of the sample. The shape and size of the obtained CNCs were also characterized by transmission electron microscopy (TEM, JEM-1200) to avoid charging effects. 5 mg/mL AgNW suspension purchased from SuJiang JI Cang Nano Technology Co.Lrd (JSCW-995-90-50) was characterized using scanning electron microscopy (SEM, Raith 150 TWO) under the InLens mode with the accelerating voltage around 5 kV. 1.5 mL of 5 mg/mL AgNW suspension was centrifuged at 4 rpm for 3 min to increase the concentration to 75 mg/mL. 15 μL, 20 μL, 25 μL and 30 μL of AgNW solution were added into 100 μL uniaxial nematic ordered CNCs to prepare four batch samples with different volume of AgNWs ($X = 15,20,25,30$), and stirred for several minutes until homogeneous. 5 μL AgNW-uniaxial nematic ordered CNCs were sheared by a piece of glass on the glass substrate (1.5 cm×1.5 cm) and dried on a hot plate at 70 ℃ for 30 min. The orientation of CNCs and AgNWs were determined by the polarized optical and dark field microscope (Olympus BX53M) respectively. The anisotropic optical performance of aligned AgNW-CNC films was also characterized through measuring its transmitted spectra using a spectrometer (Ocean Optics, QEPro) mounted on the same microscope. The sheet resistance of aligned AgNWs was measured by a home-built four-probe measurement system.
Funding
China Postdoctoral Science Foundation (2019M662018); National Key Research and Development Program of China (2017YFA0205700); National Natural Science Foundation of China (12004332, 61850410525, 62050410447, 91833303).
Acknowledgements
We gratefully thank Tingbiao Guo and Xinan Xu for measuring sheet resistance.
Disclosures
The authors declare no conflict of interest.
Data availability
No data were generated or analyzed in the presented research.
References
1. B. Su, Y. Wu, and L. Jiang, “The art of aligning one-dimensional (1D) nanostructures,” Chem. Soc. Rev. 41(23), 7832 (2012). [CrossRef]
2. B. Park, I. G. Bae, and Y. H. Huh, “Aligned silver nanowire-based transparent electrodes for engineering polarisation-selective optoelectronics,” Sci Rep 6(1), 19485 (2016). [CrossRef]
3. L. Lu, L.-L. Wang, C.-L. Zou, X.-F. Ren, C.-H. Dong, F.-W. Sun, S.-H. Yu, and G.-C. Guo, “Doubly and triply coupled nanowire antennas,” J. Phys. Chem. C 116(44), 23779–23784 (2012). [CrossRef]
4. F. Yin, H. Lu, H. Pan, H. Ji, S. Pei, H. Liu, J. Huang, J. Gu, M. Li, and J. Wei, “Highly sensitive and transparent strain sensors with an ordered array structure of AgNWs for wearable motion and health monitoring,” Sci Rep 9, 2403 (2019). [CrossRef]
5. M. Chen, I. Y. Phang, M. R. Lee, J. K. Yang, and X. Y. Ling, “Layer-by-layer assembly of Ag nanowires into 3D woodpile-like structures to achieve high density “hot spots” for surface-enhanced Raman scattering,” Langmuir 29, 7061–7069 (2013). [CrossRef]
6. A. Tao, F. Kim, C. Hess, J. Goldberger, R. He, Y. Sun, Y. Xia, and P. Yang, “Langmuir−Blodgett silver nanowire monolayers for molecular sensing using surface-enhanced Raman spectroscopy,” Nano Lett. 3, 1229–1233 (2003). [CrossRef]
7. Y. Cao, W. Liu, J. Sun, Y. Han, J. Zhang, S. Liu, H. Sun, and J. Guo, “A technique for controlling the alignment of silver nanowires with an electric field,” Nanotechnology 17, 2378–2380 (2006). [CrossRef]
8. G. Yu, A. Cao, and C. M. Lieber, “Large-area blown bubble films of aligned nanowires and carbon nanotubes,” Nature Nanotech 2, 372 (2007). [CrossRef]
9. L. Meng, R. Bian, C. Guo, B. Xu, H. Liu, and L. Jiang, “Aligning Ag nanowires by a facile bioinspired directional liquid transfer: toward anisotropic flexible conductive electrodes,” Adv. Mater. 30(25), 1706938 (2018). [CrossRef]
10. Y. Ko, S. K. Song, N. H. Kim, and S. T. Chang, “Highly transparent and stretchable conductors based on a directional arrangement of silver nanowires by a microliter-scale solution process,” Langmuir 32(1), 366–373 (2016). [CrossRef]
11. S. Murali, T. Xu, B. D. Marshall, M. J. Kayatin, K. Pizarro, V. K. Radhakrishnan, D. Nepal, and V. A. Davis, “Lyotropic liquid crystalline self-assembly in dispersions of silver nanowires and nanoparticles,” Langmuir 26(13), 11176–11183 (2010). [CrossRef]
12. Y. Zhang, Q. Liu, H. Mundoor, Y. Yuan, and I. I. Smalyukh, “Metal nanoparticle dispersion, alignment, and assembly in nematic liquid crystals for applications in switchable plasmonic color filters and e-polarizers,” ACS Nano 9(3), 3097–3108 (2015). [CrossRef]
13. M. Giese, L. K. Blusch, M. K. Khan, and M. J. MacLachlan, “Functional materials from cellulose-derived liquid-crystal templates,” Angew. Chem. Int. Ed. 54(10), 2888–2910 (2015). [CrossRef]
14. B. Senyuk, J. S. Evans, P. Ackerman, T. Lee, P. Manna, L. Vigderman, E.R. Zubarev, J. van de Lagemaat, and I. I. Smalyukh, “Shape-dependent oriented trapping and scaffolding of plasmonic nanoparticles by topological defects for self-assembly of colloidal dimers in liquid crystals,” Nano Lett. 12(2), 955–963 (2012). [CrossRef]
15. F. V. Ferreira, I. F. Pinheiro, R. F. Gouveia, G. P. Thim, and L. M. F. Lona, “Functionalized cellulose nanocrystals as reinforcement in biodegradable polymer nanocomposites,” Polym. Compos. 39, E9–E29 (2018). [CrossRef]
16. R. M. Parker, G. Guidetti, C. A. Williams, T. Zhao, A. Narkevicius, S. Vignolini, and B. Frka-Petesic, “The self-assembly of cellulose nanocrystals: hierarchical design of visual appearance,” Adv. Mater. 30(19), 1704477 (2018). [CrossRef]
17. P. X. Wang, W. Y. Hamad, and M. J. MacLachlan, “Structure and transformation of tactoids in cellulose nanocrystal suspensions,” Nat Commun 7(1), 11515 (2016). [CrossRef]
18. C. Li, J. Evans, N. Wang, T. Guo, and S. He, “pH dependence of the chirality of nematic cellulose nanocrystals,” Sci Rep 9(1), 11290 (2019). [CrossRef]
19. Q. Liu, M. G. Campbell, J. S. Evans, and II Smalyukh, “Orientationally ordered colloidal co-dispersions of gold nanorods and cellulose nanocrystals,” Adv. Mater. 26, 7178–7184 (2014). [CrossRef]
20. M. G. Campbell, Q. Liu, A. Sanders, J. S. Evans, and II Smalyukh, “Preparation of nanocomposite plasmonic films made from cellulose nanocrystals or mesoporous silica decorated with unidirectionally aligned gold nanorods,” Materials 7(4), 3021–3033 (2014). [CrossRef]
21. G. Chu, X. Wang, T. Chen, J. Gao, F. Gai, Y. Wang, and Y. Xu, “Optically tunable chiral plasmonic guest–host cellulose films weaved with long-range ordered silver nanowires,” ACS Appl. Mater. Inter. 7(22), 11863–11870 (2015). [CrossRef]
22. C. Li, N. Wang, T. Guo, J. Evans, and S. He, “Preparation of optical waveplates from cellulose nanocrystal nematics on patterned polydimethylsiloxane substrates,” Opt. Mater. Express 9(12), 4614 (2019). [CrossRef]
23. Y. Xu, D. Ge, G. A. Calderon-Ortiz, A. L. Exarhos, C. Bretz, A. Alsayed, D. Kurz, J. M. Kikkawa, R. Dreyfus, S. Yang, and A. G. Yodh, “Highly conductive and transparent coatings from flow-aligned silver nanowires with large electrical and optical anisotropy,” Nanoscale 12(11), 6438–6448 (2020). [CrossRef]
24. M. F. Islam, D. E. Milkie, C. L. Kane, A. G. Yodh, and J. M. Kikkawa, “Direct measurement of the polarized optical absorption cross section of single-wall carbon nanotubes,” Phys. Rev. Lett. 93(3), 037404 (2004). [CrossRef]
25. C. Zamora-Ledezma, C. Blanc, N. Puech, M. Maugey, C. Zakri, E. Anglaret, and P. Poulin, “Conductivity anisotropy of assembled and oriented carbon nanotubes,” Phys. Rev. E 84(6), 062701 (2011). [CrossRef]
26. X. Zeng, X. Xu, P. M. Shenai, E. Kovalev, C. Baudot, N. Mathews, and Y. Zhao, “Characteristics of the electrical percolation in carbon nanotubes/polymer nanocomposites,” J. Phys. Chem. C 115(44), 21685–21690 (2011). [CrossRef]
27. H.-K. Jang, J. E. Jin, J. H. Choi, P.-S. Kang, D.-H. Kim, and G. T. Kim, “Electrical percolation thresholds of semiconducting single-walled carbon nanotube networks in field-effect transistors,” Phys. Chem. Chem. Phys. 17(10), 6874–6880 (2015). [CrossRef]
28. T. Ackermann, R. Neuhaus, and S. Roth, “The effect of rod orientation on electrical anisotropy in silver nanowire networks for ultra-transparent electrodes,” Sci Rep 6(1), 34289 (2016). [CrossRef]
29. Y. Li, J. Jun-Yan Suen, E. Prince, E. M. Larin, A. Klinkova, H. Therien-Aubin, S. Zhu, B. Yang, A. S. Helmy, O. D. Lavrentovich, and E. Kumacheva, “Colloidal cholesteric liquid crystal in spherical confinement,” Nat Commun 7, 12520 (2016). [CrossRef]
30. J. A. Diaz, X. Wu, A. Martini, J. P. Youngblood, and R. J. Moon, “Thermal expansion of self-organized and shear-oriented cellulose nanocrystal films,” Biomacromolecules 14, 2900–2908 (2013). [CrossRef]
31. A. J. Hess, A. J. Funk, Q. Liu, J. A. De La Cruz, G. H. Sheetah, B. Fleury, and II Smalyukh, “Plasmonic metamaterial gels with spatially patterned orientational order via 3D printing,” ACS Omega 4(24), 20558–20563 (2019). [CrossRef]
