Fatima Zahra
Kharchich
ab,
Andres
Castellanos-Gomez
c and
Riccardo
Frisenda
*a
aPhysics Department, Sapienza University of Rome, Piazzale Aldo Moro 5, 00185 Rome, Italy. E-mail: riccardo.frisenda@uniroma1.it
bPhysics Department, Abdelmalek Essaadi University, M'haneche II, 93002 Tetouan, Morocco
cMaterials Science Factory, Instituto de Ciencia de Materiales de Madrid (ICMM-CSIC), Madrid E-28049, Spain
First published on 12th April 2024
One of the primary objectives in contemporary electronics is to develop sensors that are not only scalable and cost-effective but also environmentally sustainable. To achieve this goal, numerous experiments have focused on incorporating nanomaterial-based films, which utilize nanoparticles or van der Waals materials, on paper substrates. In this article, we present a novel fabrication technique for producing dry-abraded van der Waals films on paper, demonstrating outstanding electrical characteristics. We assess the quality and uniformity of these films by conducting a spatial resistivity characterization on a 5 × 5 cm2 dry-abraded WS2 film with an average thickness of 25 μm. Employing transfer length measurements with varying channel length-to-width ratios, we extract critical parameters, including sheet resistance and contact resistance. Notably, our findings reveal a resistivity approximately one order of magnitude lower than previous reports. The film's inherent disorder manifests as an asymmetric distribution of resistance values for specific geometries. We explore how this behavior can be effectively modeled through a random resistance network (RRN), which can reproduce the experimentally observed resistance distribution. Finally, we investigate the response of these devices under applied uniaxial strain and apply the RRN model to gain a deeper understanding of this process.
Achieving highly conductive films using ink suspensions containing vdW materials is challenging, due to the presence of solvent-related adsorbates on the deposited vdW materials that reduce the coupling between platelets.9,14–17 In contrast, films fabricated from the direct abrasion method using a manually operated cotton swab, have already demonstrated outstanding electrical properties, with improvements of the film resistivities of more than one order of magnitude compared to vdW inks.18 In this work we demonstrate a fabrication method capable of improving the film electrical resistivity based on the use of an electric drill with a modified spherical drill bit to deposit the vdW powder on paper. This setup allows to fabricate homogenous and large area (larger than 5 × 5 cm2) films of WS2 or MoS2 on paper in a relatively short time, which, thanks to the solvent-free processing, yields a disordered network of intimately interconnected platelets. Transfer length methods measurements performed in a statistical way give a resistivity ρ = 19.7 Ωm and contact resistance RC = 0.13 MΩ, which to our knowledge are the lowest values reported in literature for disorder WS2 thin films and are more than one order of magnitude lower than previous reports.18 Our electrical results can be reproduced by a random resistor network (RRN) solved by a combination of Ohm's law and Kirchhoff's circuit law, which capture the essential physics of these disordered films such as the intrinsic device-to-device variation.19,20 We also demonstrate the strain sensing capabilities of our devices by subjecting them to controlled uniaxial strain and discuss the results using the RRN model.
After depositing the film we test the electrical properties of the film such as its resistivity by depositing graphite electrodes onto the film. Fig. 2a shows the electrode deposition and the electrical testing setup. Firstly we draw an array of graphite electrodes using an 8B pencil separated by 5 mm one from the other (1) and labelled with numbers 1,2…9. By varying this separation we can achieve different channel lengths. We then cut, using a sharp razor blade, the film in the direction perpendicular to the electrodes in 5 mm wide ribbons (2) labelled with letters a, b…i. In this way we obtain 81 different devices with channel length L = 5 mm and channel width W = 5 mm, which, thanks to the labelling, can be spatially localized in the film. We then proceed to recording the resistance of each device using two electrical probes supported by a magnet to achieve reproducible probe pressure, as shown in (3). After fabrication we recorded the individual resistance (at a low constant voltage of 0.1 V) of each of the 81 devices finding values in the 0.5 to 2.7 MΩ range. Fig. 2b shows these resistance values as a colormap where black regions correspond to low resistance devices and yellow/white to large resistance ones. Thanks to the device labelling this colormap gives information on the spatial homogeneity of the electrical properties of the WS2 film. As can be seen, the film homogeneity is good on a few cm scale demonstrating the capabilities of the proposed deposition method in producing large area films. Fig. 2c shows an histogram of the resistance values taken from the map in panel b, which shows a peak at low resistance values and a tail at larger resistance values. We fit this histogram to a log–normal distribution, which accounts for the fact that the resistance R is positive bounded, using the formula . From the fitting parameters we can calculate the mode of the distribution according to M = exp(μ − σ2). From the fit we find μ = −0.077 MΩ and σ = 0.25 MΩ which gives a resistance R(L = 5 mm) = (0.87 ± 0.25) MΩ.
The resistance properties of the fabricated films can be extracted through a transfer length measurement. To do this we repeated the previous fabrication four additional times increasing the channel length in steps of 5 mm. Note that given the larger channel length each time we decreased the number of fabricated devices. For each set of resistance values R(L) we bin the values in a histogram and fit it to the log–normal distribution. Fig. 2d shows the results of this procedure where the resistance is plotted as a function of the channel length. The colored circles correspond to the resistances values of all the devices and the black horizontal and vertical bars represent respectively the distribution mode and standard deviation of each channel length calculated from the fitting parameters. The mode values increase from 0.86 MΩ to 4 MΩ when increasing the channel length from 5 mm to 25 mm and the standard deviation increases as well. From this set of mode values at different lengths we extract the contact resistance RC and the sheet resistance RS of the film (see inset of Fig. 2d for a circuit diagram) by performing a linear fit to these points. In the fitted linear equation the slope is equal to RS/W and the intercept with the vertical axis to 2RC. The red line in Fig. 2d is the result of such a fit from which we find RS = 0.79 MΩ □−1 and RC = 0.13 MΩ. Finally, using the just found RS value and the thickness t (estimated in Fig. 1d) we can calculate the resistivity ρ according to ρ = RSt and we find ρ = 19.7 Ωm. To our knowledge this resistivity is the lowest value reported in literature for WS2 films on paper fabricated by dry abrasion or by liquid phase exfoliated inks.18,21 Compared to the in-plane conductivity of bulk or of single-layer WS2 obtained by mechanical exfoliation,22,23 this resistivity value is still more than three orders of magnitude larger. This suggests that the out-of-plane and the flake-to-flake transport play a significant role in the total resistance of the WS2 films on paper. On the other hand, RC is comparable to previous reports for WS2 films contacted by graphite electrodes suggesting that it does not depend on the film itself but rather on the graphite–WS2 interface.18,24,25
To understand the origin of the resistance distribution and model the transport through the disordered WS2 films we propose a random resistor network (RRN) model,26,27 which we used in a previous article to model the superconducting transport transition in a disordered film of NbSe2 on paper.12Fig. 3a shows a schematic of the physical devices and a zoomed-in sketch of the WS2 film composed of interconnected WS2 platelets. Here, one can identify two components to the film resistance, a lower intra-platelet resistance (RIntra) and a larger inter-platelet one (RInter). A crude model of the film can then be given by a two-dimensional network of RIntra and RInter resistances with low valued resistance elements (RElectrodes) at the two sides to simulate the graphite electrodes (and used to apply voltage uniformly to the film). The right panel of Fig. 3a shows an example of a small RRN composed of 36 voltage nodes and 60 resistances.
To model mathematically the RRN we construct a Nx × Ny matrix (with Nx = 2nx − 1 and Ny = 2ny − 1, where nx and ny are the number of voltage nodes across the x and y directions), which contains the resistance and the voltage values. The resistance elements occupy the positions identified by the indexes r = 1, 3, 5…Nx and c = 2, 4, 6…Ny − 1 (for horizontally oriented resistors) or r = 2, 4, 6…Nx − 1 and c = 1, 3, 5…Ny (for vertically oriented resistors). The voltage nodes are located at the positions r = 1, 3, 5…Nx and c = 1, 3, 5…Ny. Note that given nx × ny voltage nodes, the number of resistors can be calculated according to: (2nx − 1)×(2ny − 1) − nx × ny − (nx − 1) × (ny − 1). We populate the matrix with binomial distributed random resistances in the channel and low resistances at the left and right sides. In the case of the left panel of Fig. 3b, a RRN with nx = ny = 100, we choose RIntra = 105 Ohm, RInter = 1010 Ohm and Relectrodes = 1 Ohm. These values for the resistance can be considered as effective values used to reproduce the general physics of the problem and not to simulate the specific film. Notice that in the chosen RRN geometry, the length L and width W of the channel are well defined geometrical quantities. To finish the setting-up of the simulation we apply a fixed voltage to the left and right electrodes by assigning the desired voltage values at the right positions (in the showed case VLeft = 1 V and VRight = 0 V respectively).
To solve for the network unknown voltages and currents we use the Kirchoff's node law combined to the Ohm's law in matrix form. To account for these two laws we create a new matrix, of size approximately nx2 × ny2, that represents a system of linear equations where the unknowns are the voltages across the network. We then solve for the voltages using the linear equations solver in MATLAB (version R2022b, MathWorks) and then calculate the current across each resistor element. Fig. 3b central and right panels show the results for the voltages and the magnitude of the current flowing through the RRN presented in the left panel. We can see that the voltage is constant in each electrode as expected and that the voltage drop has a step-like behavior, with islands of approximately constant voltage appearing. The logarithmic map of the current shows a filament behavior where few parallel paths contribute mostly to the total current flowing through the RRN, and most of the RRN resistors carry a negligible current. Notice that this behavior is typical of percolative networks of different nature.28,29 From this current map we find the total current flowing in the RRN (and the total resistance of the network), calculated by summing all the currents flowing through a column of horizontal resistors (i.e. summing all the currents with indexes r = 1, 3, 5…Nx and c = Ny/2).
To assess statistically the distribution of the total resistance in a given RRN geometry, we simulate hundreds of randomly generated RRNs and construct the histogram of the total resistance found in each case. To simulate the transfer length discussed in Fig. 2, we generate different RRNs with fixed width W = 10 and varying lengths L = 5, 10, 15, 20, 25 (see the inset of Fig. 3c). For each L we generate and solve hundreds of RRNs and we plot the results in Fig. 3c as a scatter plot (for the individual resistances) combined with a half violin plot to show the total histogram of each L. From this graph we can see that the resistances for a given L show a distribution peaked at lower resistance and with a tail at larger resistance values. This behavior is comparable with the one found from the histograms of the transfer length resistances of Fig. 2c. Similar to the experimental case, we characterize the different distributions by their mode and standard deviation. Interestingly, by increasing L the mode increases in an approximately linear fashion and the standard deviation also increases, similar to the experimental observations.
Being paper an easily deformable material, one possible application of electrical devices based on films on paper is in strain sensing.25,30 In the following we discuss the strain sensing capabilities of our devices and show how the RRN model can give some insight into the physical process behind the strain sensing in disordered films. We start by characterizing a WS2 drawn channel contacted by graphite drawn electrodes and subjected to uniaxial (compressive or tensile) strain using the apparatus shown in the inset of Fig. 4a. The use of linear micromanipulators allows to finely tune the radius of curvature R of the device and thus the strain. We calculate the strain using the formula , where t is the thickness of the device (approximately 100 μm, see Fig. 1c). For each value of strain we record the resistance of the device and we plot the results in Fig. 4a. The unstrained device has a resistance of R0 = 2.03 MΩ, which decreases for compressive strain and increases for tensile strain. The rate of change in the resistance as a function of strain is commonly referred to as gauge factor (GF) which is calculated as GF = (R − R0/R0)/ε = (ε/R0)/ε.5,25Fig. 4b shows ΔR/R0versus epsilon for two different devices based on WS2 with unstrained resistances respectively R0 = 1.83 MΩ (red circles) and R0 = 2 MΩ (orange circles). In these two devices the data shows a linear increase with applied strain symmetric for tensile and compressive strain. We find GF = 100 by performing a linear regression to the data. Fig. 4c shows similar measurements performed on a MoS2 film based device. The devices in this case show a much larger unstrained resistance of R0 = 7 GΩ and R0 = 11 GΩ, in accordance with previous reports on MoS2 films on paper fabricated with similar methods.11 These resistance values are around two orders of magnitude larger than those of large-area MoS2 films deposited on SiO2/Si with Au prepatterned electrodes (L = 10 μm, W = 1000 μm) where square resistances are in the order of 5–50 MΩ □−1 compared to our MoS2 film where the film resistance is 1000 MΩ □−1.31 This difference could be due to the different production method of MoS2 that in ref. 31 comes from mechanically exfoliated flakes from bulk MoS2 and in our case comes from MoS2 micronized powder. Interestingly, while the lower R0 device shows similar slopes both for tensile and compressive strain with a GF = 100, the larger R0 device shows a smaller slope for compressive strain in respect to the tensile train datapoints. In this last device we find GF = 100 for tensile strain and GF = 10 for compressive strain.
In order to gain more insight on the strain sensing properties of disordered films we apply the RRN model. In this case, to simulate disordered films and apply strain we generate a network of randomly placed squares which we can individually track and displace independently one from the other. The top row of Fig. 4d shows two resistance networks generated in this way, on the left for a larger number (or density) of squares and on the right for a lower number of squares. The central panel in each of the two cases correspond to the unstrained network. The left and right panel of each case correspond respectively to compressive and tensile strained networks. The bottom row shows the calculated current in each case. For the unstrained case we see the usual behavior of RRN where current is carried mostly through a few “filaments” in parallel. The high density network does not show strong change in the number of current paths as a function of strain meaning that also the total resistance does not depend strongly on the strain and thus the gauge factor is small (lower than 10). On the other hand, the low density RRN shows a strong dependency of the current paths on the strain. From the bottom right panel of Fig. 4d it is clear how for compressive strain the network shows a large number of parallel current paths while for tensile strain the current paths are less and carry overall a much lower current. This can give a strong modulation of the total resistance versus strain for tensile strain and larger gauge factors (larger than 10). Fig. 4e summarizes the results from four different simulation performed for increasing RRN densities.
Footnote |
† Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d3nr06535a |
This journal is © The Royal Society of Chemistry 2024 |