Percolation Curve Research Articles

Thermo-Mechanical and Thermo-Electric Properties of a Carbon-Based Epoxy Resin: An Experimental, Statistical, and Numerical Investigation.

Due to their remarkable intrinsic physical properties, carbon nanotubes (CNTs) can enhance mechanical properties and confer electrical and thermal conductivity to polymers currently being investigated for use in advanced applications based on thermal management. An epoxy resin filled with varying concentrations of CNTs (up to 3 wt%) was produced and experimentally characterized. The electrical percolation curve identified the following two critical filler concentrations: 0.5 wt%, which is near the electrical percolation threshold (EPT) and suitable for exploring mechanical and piezoresistive properties, and 3 wt% for investigating thermo-electric properties due to the Joule effect with applied voltages ranging from 70 V to 200 V. Near the electrical percolation threshold (EPT), the CNT concentration in epoxy composites forms a sparse, sensitive network ideal for deformation sensing due to significant changes in electrical resistance under strain. Above the EPT, a denser CNT network enhances electrical and thermal conductivity, making it suitable for Joule heating applications. Numerical models were developed using multiphysics simulation software. Once the models have been validated with experimental data, as a perfect agreement is found between numerical and experimental results, a simulation study is performed to investigate additional physical properties of the composites. Furthermore, a statistical approach based on the design of experiments (DoE) was employed to examine the influence of certain thermal parameters on the final performance of the materials. The purpose of this research is to promote the use of contemporary statistical and computational techniques alongside experimental methods to enhance understanding of materials science. New materials can be identified through these integrated approaches, or existing ones can be more thoroughly examined.

Molecular cluster analysis using local order parameters selected by machine learning.

Accurately extracting local molecular structures is essential for understanding the mechanisms of phase and structural transitions. A promising method to characterize the local molecular structure is defining the value of the local order parameter (LOP) for each particle. This work develops the Molecular Assembly structure Learning package for Identifying Order parameters (MALIO), a machine learning package that can propose an optimal (set of) LOP(s) quickly and automatically for a huge number of LOP species and various methods of selecting neighboring particles for the calculation. We applied this package to distinguish between the nematic and smectic phases of uniaxial liquid crystal molecules, and selected candidate LOPs that could be used to precisely observe the nematic-smectic phase transition. The LOP candidates were used to observe the nucleation and subsequent percolation transition, and the effect of the choice of LOP species and neighboring particles on the statistics of local molecular structures (clusters) was examined. The procedure revealed the time evolution of the number of clusters and the dependence of the percolation curve on the number of neighboring particles for each LOP species. The LOP species with the lowest dependence on the number of neighboring particles was the best-performing LOP species in the MALIO screening strategy. These results not only show that machine learning can powerfully screen a huge number of LOP species and suggest only a few promising candidates, but also indicate that MALIO can select the best LOP species.

Liquid-vapour coexistence line and percolation line of rose water model

Monte Carlo simulations and Wertheim’s thermodynamic perturbation theory (TPT) are used to predict the phase diagram and percolation curve for the simple two-dimensional rose model of water. In the rose model of water, the water molecules are modelled as two-dimensional Lennard-Jones disks, with additional rose potentials for orientation dependent pairwise interactions that mimic formation of hydrogen bonds. Modifying both the shape and range of a 3-petal rose function, it was constructed an efficient and dynamical mimic of the 2D Mercedes Benz (MB) water model and experimental water. The liquid part of the phase space is explored using grand canonical Monte Carlo simulations and two versions of Wertheim’s TPT for associative fluids. We find that the theory reproduces well the physical properties of hot water but is less successful at capturing the more structured hydrogen bonding that occurs in cold water. In addition to reporting the phase diagram and percolation curve of the model, it is shown that the improved TPT predicts the phase diagram rather well, while the standard one predicts a phase transition at lower temperatures. For the percolation line, both versions have problems predicting the correct position of the line at high temperatures.

Exploring the Capabilities of a Piezoresistive Graphene-Loaded Waterborne Paint for Discrete Strain and Spatial Sensing.

The development of a piezoresistive coating produced from dispersing graphene nanoplatelets (GNPs) inside a commercial water-based polyurethane paint is presented. The feasibility of its exploitation for realizing highly sensitive discrete strain sensors and to measure spatial strain distribution using linear and two-dimensional depositions was investigated. Firstly, the production process was optimized to achieve the best electromechanical response. The obtained materials were then subjected to different characterizations for structural and functional investigations. Morphological analyses showed a homogenous dispersion of GNPs within the host matrix and an average thickness of about 75 µm of the obtained nanostructured films. By several adhesion tests, it was demonstrated that the presence of the nanostructures inside the paint film lowered the adhesion strength by only 20% in respect to neat paint. Through electrical tests, the percolation curve of the nanomaterial was acquired, showing an effective electrical conductivity ranging from about 10−4 S/m to 3.5 S/m in relation to the different amounts of filler dispersed in the neat paint: in particular, samples with weight fractions of 2, 2.5, 3, 3.5, 4, 5 and 6 wt% of GNPs were produced and characterized. Next, the sensitivity to flexural strain of small piezoresistive sensors deposited by a spray-coating technique on a fiberglass-reinforced epoxy laminate beam was measured: a high gauge factor of 33 was obtained at a maximum strain of 1%. Thus, the sensitivity curve of the piezoresistive material was successively adopted to predict the strain along a multicontact painted strip on the same beam. Finally, for a painted laminate plate subjected to a mechanical flexural load, we demonstrated, through an electrical resistance tomography technique, the feasibility to map the electrical conductivity variations, which are strictly related to the induced strain/stress field. As a further example, we also showed the possibility of using the coating to detect the presence of conducting objects and damage.

Study on the Effect of Threshold Pressure Gradient on Remaining Oil Distribution in Heavy Oil Reservoirs

Due to the spatial network structure, heavy oil has a high threshold pressure gradient when it flows through porous media, and the threshold pressure gradient plays a crucial role in the distribution of remaining oil. In previous study, the common methods to measure the threshold pressure gradient include the microflow-established differential pressure (MFEDP) method, capillary equilibrium method, and the percolation curve fitting method. In this study, a sample from the SZ36-1 oilfield was analyzed for the basic physical properties based on the comparison of the previous measurement to study the influence of mobility on the threshold pressure gradient and then an independently developed numerical simulator was established to study the effect of the threshold pressure gradient on the remaining oil distribution considering the permeability range, crude oil viscosity, well network deployment, well spacing, and fluid recovery rate. The results show that the SZ36-1 oilfield fluid belongs to Bingham fluids with yield stress and the mobility having an exponent relation to the threshold pressure gradient based on the measurement of the MFEDP method. Considering the threshold pressure gradient of heavy oil, the uneven distribution of remaining oil is intensified and the remaining oil is enriched. This study provides a reference for efficient development of heavy oil reservoirs.

Influence of the nanostructure on the electric transport properties of resistive switching cluster-assembled gold films

The use of Au clusters produced in the gas phase and deposited at low kinetic energy on a substrate allows the bottom-up fabrication of nanostructured metallic thin films with an extremely large number of interfaces, grain boundary junctions and crystal lattice defects. Cluster-assembled gold films exhibit non-ohmic electrical transport properties with a complex resistive switching behavior, exploring discrete resistance states which depend on their structural features (average thickness, resistance value reached on the percolation curve). Their electric conduction properties can be modelled in terms of complex networks of nanojunctions and used to perform binary classification of Boolean functions. The fabrication of devices based on cluster-assembled Au films and exploiting emergent complexity and collective phenomena requires a deep understanding of the influence of the nanoscale structure on the fundamental mechanisms of electrical conduction. Here we present a detailed study of the correlation between the nanostructure and the electrical properties of cluster-assembled gold films by a systematic characterization of the film growth from sub-monolayer to continuous layer beyond the electrical percolation threshold. The influence of different cluster size distributions on the onset of the electrical conduction and the role of defects is investigated by combining in situ and ex situ electrical and structural characterizations.

Metal-Organic Framework and Silver Nanowire Composites As Chemiresistive Gas Sensors Operating at the Percolation Threshold

The high internal service areas and consequent high numbers of sites for analyte adsorption of Metal-Organic Frameworks, MOFs, make them attractive candidates for gas sensing applications. Through synthesis of conductive MOFs we present a novel way of fabricating chemiresistive sensors able to detect NO2 gas in the low ppm range. A suspension of MOF and Ag nanowires in solution is prepared and drop cast onto paper to form the sensing medium. Sufficient conductive MOF is added to an insulating concentration of nanowires to give a conductive sample operating in the percolation region. The percolation region refers to the point before a thin film has formed where a small change in the number of conductive pathways leads to the largest change in material conductivity, as depicted in figure 1.1 By fabricating sensors operating in this region, a small interruption in the conductive network due to analyte interaction leads to a large change in measurable conductivity, allowing higher sensor sensitivities to be accessed.2 , 3 Moreover, the use of MOFs lends itself to the systematic synthesis of sensing media tailored to respond to desired gaseous analytes. Through selection of organic linkers with particular functional groups and/or particular metal nodes, the functionality and pore sizes of the resulting MOFs can be manipulated. We have synthesised MOFs with Cu, Ni and Fe metal centres linked by hexahydroxytriphenylene ligands4 and fabricated chemiresistive sensors through combination with Ag nanowires. Their different sensing responses to NO2 and NH3 gases with concentrations below 5 ppm have been recorded, and the simultaneous exposure of all three MOF sensors in an array to gaseous analytes is anticipated to further increase sensor selectivity. Figure 1: Schematic of a percolation curve, demonstrating how the conductivity between two electrodes changes as the concentration of conductive material, such as conductive polymer, between the electrodes is increased. The optimum region for sensing experiments is where the gradient is steepest; the percolation region. Image reproduced from reference 1. References Murugappan K, Castell MR. Bridging electrode gaps with conducting polymers around the electrical percolation threshold. Electrochem commun. 2018;87:40-43. doi:10.1016/j.elecom.2017.12.019Lefferts MJ, Murugappan K, Wu C, Castell MR. Electrical percolation through a discontinuous Au nanoparticle film. Appl Phys Lett. 2018;112(25):251602. doi:10.1063/1.5023163Armitage BI, Murugappan K, Lefferts MJ, Cowsik A, Castell MR. Conducting polymer percolation gas sensor on a flexible substrate. J Mater Chem C. 2020;8:12669. doi:10.1039/d0tc02856hCampbell MG, Liu SF, Swager TM, Dincə M. Chemiresistive Sensor Arrays from Conductive 2D Metal-Organic Frameworks. J Am Chem Soc. 2015;137(43):13780-13783. doi:10.1021/jacs.5b09600 Figure 1

Percolation Characteristics and Fluid Movability Analysis in Tight Sandstone Oil Reservoirs.

The development of tight oil has started relatively late, and the flow mechanisms and fluid movability are still research spotlights. The goal of this paper is to investigate the percolation characteristics and fluid movability of the Chang 6 tight sandstone oil layer in the Upper Triassic Yanchang Formation, Ordos Basin, China. Results show that (1) at low flow velocity, the percolation curve of flow velocity vs pressure gradient is a concave-up nonlinear curve and does not pass through the origin. It is more difficult for oil flow than water flow in cores with similar permeability due to rock wettability and fluid apparent mobility. The application of back pressure makes the nonlinear stage eliminated and the percolation character improved. (2) Two-phase flow tests reveal that oil-phase permeability decreases faster in samples with lower permeability, and the coexistent flow region of oil and water is relatively narrow. The contribution of oil recovery mainly happens at the early stage. The permeability at the isotonic point reduces with the decrease of sample permeability. (3) Flow during water flooding can be roughly divided into four stages according to the injection pressure and flow change. The injection pressure experiences stages of increasing to a peak, then decreasing, and finally becoming stable, accompanied by an increase of oil production until water breaks through. (4) The pore throats of the target reservoir mainly range from 0.001 to 10 μm, and the bound water mainly distributes in pores less than 0.2 μm. The irreducible water saturation is 30–35%, and the movable fluid saturation is 65–70%, mainly distributed in pores at 0.2–10.0 μm with a maximum of 2.0 μm. The results will supplement the existing knowledge of percolation characters and fluid movability in tight sandstone oil reservoirs.

Chemiresistive Vapour Sensors Based on a Percolation Network of Conductive Polymers

Introduction: Vapour sensing plays an important role in various safety, security, and healthcare applications. However, it is perhaps surprising that despite modern technologies sniffer dogs are still considered the gold standard in vapour sensing. Achieving high sensitivities often remains challenging. Furthermore, existing technological solutions often require relatively large pieces of equipment, or pre-concentration steps [1].Conductive polymer (CP) based chemiresistive vapour sensors offer a promising solution because of the large range of materials available and their relatively cheap and easy processing methods. Furthermore, their small scale makes it possible to use them in small scale devices. CP based sensors described in literature often use a CP thin film as the sensing layer. Here we demonstrate a significantly improved sensitivity by using a percolation network of CPs instead of a CP thin film. Concept: Electrical percolation describes the likelihood of a current running from an electrode on one side of a network to an electrode on the other side. If there are no electrical connections between the electrodes the conductance is zero. When enough connections are added to the network to form a conductive pathway between the electrodes the conductance increases sharply. When more connections are added to the network the conductance keeps increasing and eventually reaches a plateau. Traditional chemiresistive vapour sensors, consisting of a CP thin film, are operated in this flat part of the percolation curve. We’ve shown that by creating sensors in the steep part of the curve, close to the percolation threshold, a significantly higher sensitivity can be achieved. Experimental: Our sensors consist of a polypyrrole (PPy) network between interdigitated Pt electrodes on a glass substrate. Au nano-islands were used as nodes in the PPy network. Sensors with different polymer coverages, corresponding to different points along the percolation curve, were exposed to various concentrations of ammonia. Results and conclusion: Sensors with polymer coverages corresponding to the steep part of the percolation curve give a significantly higher sensitivity than those in the thin film regime. One would perhaps also expect that the closer to the percolation threshold the better the sensor, however in practice this doesn’t hold true. Moving closer to the percolation threshold from this optimum does result in a higher absolute sensor response, however due to an increase in relative noise the sensitivity decreases when a sensor is too close to the percolation threshold. At this optimum, in the steep part of the percolation curve, we have achieved sensitivities as low as 9 ±2 ppb. Outlook: Further avenues of research that we are currently exploring include increasing the range of sensing materials and analyte vapours, as well as using this sensor technology for specific applications such as the detection of improvised explosives. We are also using percolation networks to improve the sensitivity of sensors on flexible substrates, and for the inclusion of this technology into wearable devices. Finally, we have developed an integrated device that not only allows us to take this technology out of the lab and test it in real-life scenarios, but also allows us to use multiple sensors at the same time in an electronic nose type setup. This allows us to increase our selectivity in addition to the increased sensitivity achieved by using percolation networks of CPs instead of thin films.[1] Lefferts, M. J. & Castell, M. R. Vapour sensing of explosive materials, Analytical Methods 7, 9005-9017 (2015); DOI: 10.1039/C5AY02262B

Self-sensing nanocomposites in automotive/aeronautic field

Carbon Nanotubes have been incorporated in a resin-based on the bi-functional epoxy precursor diglycidyl ether of bisphenol A (DGEBA). Electrical measurements allowed evaluating the electric percolation curve with a value of electric percolation threshold detected around 0.015% by weight of multi-wall carbon nanotubes (MWCNTs). It has been found, by electro-mechanical tests, that the Gauge Factor (G.F.) decreases with increasing the carbon nanotubes percentage. Furthermore, the presence of a residual resistivity allows diagnosing permanent damage in the epoxy matrix. High piezoresistive performance (G.F. = 4.7) of the Carbon Fiber Reinforced Panels (CFRP) coated with the epoxy resin containing 0.1 wt% of MWCNT, has been obtained.

Electrical properties of stretchable and skin–mountable PDMS/MWCNT hybrid composite films for flexible strain sensors

Flexible strain sensors based on carbon nanofillers have great potential in the application of skin-adhesive sensors, wearable sensors, and tactile sensors, due to their superior electrical properties. Herein, the electrical properties of highly sensitive PDMS/MWCNT strain sensors made by vacuum filtration method were investigated. In order to obtain the electrical percolation curve of the flexible conductive films, first different samples were made with the same surface area but with different wt. % of CNTs. Then, depending on CNT content, the obtained conductive films exhibited initial electrical resistance in the range of 12.5 KΩ to 22.8 MΩ. The piezoresistive films with the CNT concentration of 1.4 to 2.9 [Formula: see text] had shown superior resistance drop, so this interval was determined as the percolation threshold region. According to the SEM images, the nanocomposite layer thickness of the flexible strain sensors in this region was 790 nm to 1210 nm. Afterward, the percolation curve was obtained using curve fitting to the experimental data and the exact value of the percolation threshold was defined as [Formula: see text]. Finally, in order to determine the minimum gauge factor ([Formula: see text]) of the sensors in percolation region, a flexible strain sensor in the upper limit of this region was selected and the piezoresistive properties of the selected sample were investigated.

Electrical conductivity modelling of polypropylene composites with carbon fillers

Samples of a composite material based on polypropylene matrix and carbon fillers (carbon black and carbon nanofibers) were obtained. It was experimentally shown that the dependences of the electrical conductivity on the filler mass fraction have a threshold nature/When the mass fraction of the filler is higher than the threshold the values of the electrical conductivity increases by more than 8-10 orders. Determination of the electrical conductivity value near the percolation threshold is difficult. In the article the simulation method was proposed which considers the presence of a dielectric layer between the filler particles, presented a method for its evaluation: the percolation curve near the percolation threshold was described. A fairly good agreement between the experimental and theoretical values of conductivity for various geometries and types of fillers is shown in this work.

A multi-technique experimental and modelling study of the porous structure of IG-110 and IG-430 nuclear graphite

In nuclear graphite, the wide range of void sizes precludes a full characterisation of pore volume by means of a single technique. A novel multi-technique approach, consisting of pycnometry, low pressure gas adsorption and mercury porosimetry is presented. The approach is validated for two nuclear-grade graphites designed for use in Generation IV nuclear reactors, namely IG-110 and IG-430. Damage and deformation caused to the structure of the graphite by mercury intrusion is estimated by consecutive intrusion experiments. The damage is assumed to be caused by the highest applied pressures of mercury. It is compensated by substituting that part of the percolation curve with one derived from adsorption measurements. The various measurements are inverse modelled in a way which intelligently bridges the size gap between the techniques. The resulting complete non-hierarchical pore structure covers sizes spanning 4 orders of magnitude. The new approach resolves the long standing issues associated with performing porosimetry on graphitic samples, and fills the gap in knowledge for the assessment of multilevel porosity within graphite. As an example of the possible applications of the resulting void network structure, we calculated the air network flow capacity, related to absolute permeability, for the two graphite samples.

Liquid part of the phase diagram and percolation line for two-dimensional Mercedes-Benz water.

Monte Carlo simulations and Wertheim's thermodynamic perturbation theory (TPT) are used to predict the phase diagram and percolation curve for the simple two-dimensional Mercedes-Benz (MB) model of water. The MB model of water is quite popular for explaining water properties, but the phase diagram has not been reported till now. In the MB model, water molecules are modeled as two-dimensional Lennard-Jones disks, with three orientation-dependent hydrogen-bonding arms, arranged as in the MB logo. The liquid part of the phase space is explored using grand canonical Monte Carlo simulations and two versions of Wertheim's TPT for associative fluids, which have been used before to predict the properties of the simple MB model. We find that the theory reproduces well the physical properties of hot water but is less successful at capturing the more structured hydrogen bonding that occurs in cold water. In addition to reporting the phase diagram and percolation curve of the model, it is shown that the improved TPT predicts the phase diagram rather well, while the standard one predicts a phase transition at lower temperatures. For the percolation line, both versions have problems predicting the correct position of the line at high temperatures.

Synergistic effects on polyurethane/lead zirconate titanate/carbon black three-phase composites

Synergistic processes in hybrid composites have frequently been described in the literature over the past few years, opening doors to new studies and applications for this type of material. In this study, three-phase composites were obtained using polyurethane (PU) as the matrix, lead zirconate titanate (PZT) as the ferroelectric ceramic and carbon black (CB) as the conductive phase. The discussion is primarily focused on a comparison of the electrical, thermal and dielectric properties of three-phase composites with those of PU_CB and PU_PZT biphasic composites. The study describes a synergistic effect between the PU/PZT/CB phases involved in the generation of charges between the particles, implying better homogeneity of the composites as well as influence over the PU crystallization. The PU_CB conductivity profile showed a phenomenon of multi-step percolation thresholds attributed to the molecular structure and repulsive surface charge of CB particles. The surface charge phenomenon restricted the percolation curve analysis of the three-phase composites by means of classic percolation theory, shown by distortion of the critical exponents. The dielectric constant three-phase composites increased gradually as a function of CB in accordance with the percolation profile.

Corrosion behavior of a steel bar embedded in a cement-based conductive composite

Corrosion behavior of a steel bar embedded in a cement-based conductive composite was the object of study described in this paper. First, the conductivity percolation curve of a carbon-fiber- (CF-) reinforced cement-based composite was obtained. The dry-wet cycle method was then adopted to accelerate the corrosion of the steel bar embedded in the cement-based conductive composite. The corrosion behavior was analyzed using the linear polarization resistance (LPR) technique, the corrosion potential and the weight loss method. In addition, the effect of the CF added on the pore structure was discussed. Finally, it was found that the percolation threshold of CF in the composite is a critical value that determines the corrosion level of the steel bar. The addition of CF has no effect on the corrosion level of the steel bar at the early stage when the CF content is lower than the CF percolation threshold, while the corrosion level tends to increase when the CF content is higher than the CF percolation threshold.

Graphene Nanoplatelet–Polystyrene Nanocomposite: Dielectric and Charge Storage Behaviors

Graphene nanoplatelet (GNP)–polystyrene nanocomposites filled with up to 20 wt.% GNPs were prepared by melt mixing. The microstructure, direct-current (dc) electrical percolation behavior, and dielectric characteristics were investigated as functions of frequency. In addition, the effects of dc bias on the complex impedance and charge transport mechanisms were explored. The dc electrical percolation curve showed a gradually transition from the insulating to conducting state. At 15 wt.% GNP loading and frequency greater than 104 Hz, the nanocomposite exhibited dielectric constant and loss factor of 180 and 0.11, respectively, revealing remarkable storage capabilities at high frequencies. For nanocomposites filled with 12 wt.% to 20 wt.% GNPs, the alternating-current conductivity was found to follow the universal dynamic response behavior, implying electron conduction due to tunneling in addition to direct contact between GNPs.

Impact of BaTiO3 as insulative ferroelectric barrier on the broadband dielectric properties of MWCNT/PVDF nanocomposites

This study was devoted to investigating the effects of BaTiO3 incorporation on the broadband dielectric properties of melt‐mixed multi‐walled carbon nanotube/poly(vinylidene fluoride) (MWCNT/PVDF) nanocomposites. BaTiO3, as insulative barrier, was incorporated into the composites with MWCNT loadings close to and above the percolation threshold, where conductive networks were unstable and newly formed. The results showed that BaTiO3 did not create any change in the volume resistivity and percolation curve; nevertheless, it reduced the dissipation factor considerably. For instance, at 100 Hz the dissipation factor of the MWCNT/PVDF nanocomposite was 130, which dropped to 48 and 0.45 by adding 1.0 and 3.0 vol% BaTiO3, respectively. It was also observed that incorporating BaTiO3 muted the descending trends of dielectric permittivity and dielectric loss with frequency, confirming the role of BaTiO3 as insulative barrier. The positive impact of BaTiO3 on the dielectric properties of the MWCNT/PVDF nanocomposites was attributed to deteriorated conductive network. POLYM. COMPOS., 299–304, 2016. © 2014 Society of Plastics Engineers

Influence of carbon nanotube dimensions on the percolation characteristics of carbon nanotube/polymer composites

The effect of carbon nanotube aspect ratio (AR) on the percolation characteristics of their polymer composites was investigated by melt blending the multi-wall carbon nanotubes (MWCNTs) with different AR with a thermoplastic elastomer. Previously, most studies reported the effect of aspect ratio of MWCNTs only in the context of achieving the maximum electrical conductivity at lower percolation thresholds in the polymer composites. In this study, our results indicate that aspect ratio can also influence other percolation properties such as the pre-percolation conductivity, percolation conductivity and post-percolation conductivity, shape of the percolation curve, and the width of the insulator-conductor transition. We have established that AR can be used to tailor the percolation curves from sharp to quasi-linear ones, which can help us fabricate the percolative composites with stable electrical properties. Experimental results suggested that the mathematically calculated nominal AR of the MWCNTs was an unclear parameter to correlate with the percolation characteristics of the composites. Instead, an approach taking into consideration the nominal length (l) and the diameter (d) of the MWCNTs individually rather than as a combined AR (l/d) parameter gave a better explanation of the relation between MWCNT dimensions and percolation characteristics.

Effect of graphitic filler size and shape on the microstructure, electrical percolation behavior and thermal properties of nanostructured multilayered carbon films deposited onto paper substrates

Abstract