Electrical Conductivity Model Research Articles

Modeling of Effective Electrical Conductivity and Percolation Behavior in Conductive-Polymer Nanocomposites Reinforced with Spherical Carbon Black

Modeling of Effective Electrical Conductivity and Percolation Behavior in Conductive-Polymer Nanocomposites Reinforced with Spherical Carbon Black

Predictive model for progressive salinization in a coastal aquifer using artificial intelligence and hydrogeochemical techniques: a case study of the Nile Delta aquifer, Egypt.

To monitor groundwater salinization due to seawater intrusion (SWI) in the aquifer of the eastern Nile Delta, Egypt, we developed a predictive regression model based on an innovative approach using SWI indicators and artificial intelligence (AI) methodologies. Hydrogeological and hydrogeochemical data of the groundwater wells in three periods (1996, 2007, and 2018) were used as input data for the AI methods. All the studied indicators were enrolled in feature extraction process where the most significant inputs were determined, including the studied year, the distance from the shoreline, the aquifer type, and the hydraulic head. These inputs were used to build four basic AI models to get the optimal prediction results of the used indicators (the base exchange index (BEX), the groundwater quality index for seawater intrusion (GQISWI), and water quality). The machine learning models utilized in this study are logistic regression, Gaussian process regression, feedforward backpropagation neural networks (FFBPN), and deep learning-based long-short-term memory. The FFBPN model achieved higher evaluation results than other models in terms of root mean square error (RMSE) and R2 values in the testing phase, with R2 values of 0.9667, 0.9316, and 0.9259 for BEX, GQISWI, and water quality, respectively. Accordingly, the FFBPN was used to build a predictive model for electrical conductivity for the years 2020 and 2030. Reasonable results were attained despite the imbalanced nature of the dataset for different times and sample sizes. The results show that the 1000 μS/cm boundary is expected to move inland ~9.5 km (eastern part) to ~10 km (western part) to ~12.4 km (central part) between 2018 and 2030. This encroachment would be hazardous to water resources and agriculture unless action plans are taken.

Global 3‐D Electrical Conductivity Model of the World Ocean and Marine Sediments

AbstractThis study presents global 3‐D electrical conductivity models of the world ocean and marine sediments. Electrical conductivity of the ocean was calculated by invoking the Equation of State of Seawater (TEOS‐10) with temperature and salinity data retrieved from the World Ocean Atlas and a series of high‐resolution regional ocean climatology data sets. The resolution of the ocean conductivity atlas varies between 0. and 0. globally. The conductivity of marine sediments was estimated by using compaction and thermal gradient models constrained by real observations on a 5‐arc‐minute global marine sediment thickness grid. I present numerical simulations of electromagnetic (EM) induction responses that demonstrate a significant effect of 3‐D electrical conductivity of the ocean and marine sediments on EM responses for a broad range of frequencies. I show that both marine and land‐based surveys designed for subsurface conductivity imaging or Space Weather modeling will benefit from inclusion of more realistic conductivity models of the ocean and seabed sediments.

A continuum-molecular model for anisotropic electrically conductive materials

An anisotropic model for two-dimensional electrical conduction, elasticity and fracture is proposed in the peridynamic theoretical framework. Material points interact through elastic non-central pair potentials and inelastic pair potential functions of pairwise elastic and inelastic deformation measure, allowing to obtain a bond-based type model for conductive Cauchy orthotropic media without restrictions in the number of independent material constants. The elasticity of pair interactions can be described mechanistically by equivalent normal and shear springs, whose stiffness varies continuously with the spatial orientation of the ligament and, preserving the elastic symmetries of the material, depends on four material parameters defining in-plane orthotropic classical elasticity. The macroscopic anisotropic conductivity is described instead by continuous functions of the micro-conductive properties of the interparticles interactions. Moreover, non-uniform material toughness is modeled adopting an anisotropic energetic failure criterion related to direction-dependent fracture energy functionals. The accuracy of the proposed model has been assessed by several problems including the anisotropic electrical conduction in multi-phases laminae with a central hole and evolving cracks, and the fracture and damage sensing in cortical bone considering different orientation of the material reference system.

Comparative Analysis of Methods for Mathematical Modeling of Specific Electrical Conductivity of Plasma in the Channel of an Electric Discharge in Water

In the present work, a comparative analysis of three methods for determining the specific electrical conductivity of the plasma formed in the channel of an electric discharge in water is carried out for its mathematical modeling. The parameters of the empirical function are determined, at which the results of mathematical modeling are consistent with the experimental data. The necessity of using empirical functions in calculating the specific electrical conductivity of plasma has been substantiated. The obtained ratios made it possible to significantly increase the adequacy of the previously developed mathematical model of the physical discharge processes in water and to expand the range of parameters in which it can be used.

Applications of linear algebra to the study of mathematical modelling of the physical phenomena of heat conduction by electricity

The study of the phenomenon of electrical conduction has its origin in two historical antecedents, Fourier’s law and Maxwell’s equations. The mathematical formulation of electrical conduction has been extensively studied and the differential equations describing the phenomenon are known. The mathematical solution of the physical model of electrical conduction employs different techniques, the best known of which are the Fourier series, Grenn functions and Bessel equations. The purpose of this research is to present a model of heat conduction with the use of electric current that dissipates heat by convection. The research proposes a method for solving the mathematical model associated with the conduction phenomenon using linear algebra. The advantage of using linear algebra will allow to establish a step-by-step procedure that could be used to study phenomena related to heat conduction, in addition to allowing its implementation through programming. In order to establish the fit of the method derived from linear algebra, the analytical solution and the solution proposed in the research were compared to verify that the proposed method fits with a small error.

Magnetotelluric Sampling and Geoelectric Hazard Estimation: Are National‐Scale Surveys Sufficient?

AbstractAt present, the most reliable information for inferring storm‐time ground electric fields along electrical transmission lines comes from coarsely sampled, national‐scale magnetotelluric (MT) data sets, such as that provided by the EarthScope USArray program. An underlying assumption in the use of such data is that they adequately sample the spatial heterogeneity of the surface relationship between geomagnetic and geoelectric fields. Here, we assess the degree to which the density of MT data sampling affects geoelectric hazard assessments. For electrical transmission networks in each of four focus regions across the contiguous United States, we perform two parallel band‐limited (101–103 s) hazard analyses: one using only USArray‐style (∼70‐km station spacing) MT data, and one incorporating denser (≪70‐km station spacing) MT data. We find that the use of USArray‐style MT sampling alone provides a useful first‐order estimate of integrated geoelectric fields along electrical transmission lines. However, we also find that the use of higher density MT data can in some areas lead to order‐of‐magnitude differences in line‐averaged electric field estimates at the level of individual transmission lines and can also yield significant differences in subregional hazard patterns. As we demonstrate using variogram plots, these differences reflect short‐spatial‐scale variability in Earth conductivity, which in turn reflects regional lithotectonic structure and history. We also provide a cautionary example in the use of electrical conductivity models to predict dense MT data; although valuable for hazard applications, models may only be able to reproduce surface geoelectric fields as captured by the MT data from which they were derived.

An electrical conductivity model of a coastal geothermal field in southeastern China based on 3D magnetotelluric imaging

The hydrology and geology of the Xinzhou geothermal field in South China and its surrounding area have been well studied. Previous studies have indicated that mantle heat, granite radioactive heat, and partial melting are the likely key thermal sources. However, neither the geometry of the geothermal reservoir nor the groundwater circulation pattern has been fully characterized. Toward that aim, a grid of magnetotelluric (MT) data has been acquired to reveal the subsurface distribution of electrical conductivity and to detect the geothermal reservoir. An analysis of the phase tensors suggests that 3D MT inversion is essential for accurate interpretation of the data. We perform a 3D full-impedance MT inversion and observe pronounced low electrical conductivity zones in the inverse model. We interpret these materials as widely developed granites that form the bedrock, which is cut by a crisscross of faults. The cracks in the bedrock provide pathways for the vertical and lateral movement of the hydrothermal fluid. The geothermal reservoir appears as a prominent high electrical conductivity anomaly beneath the hot spring. A northwest-dipping zone of enhanced electrical conductivity reaching approximately 6–7 km in depth is found in the southeast part of the study area, and it is interpreted as the geothermal reservoir recharge channel. We develop an inferred underground fluid circulation model, informed by the electrical conductivity of the area, in combination with hydrologic data. We suggest that the water supply of the Xinzhou geothermal field mainly comes from meteoric water, which is mixed with the invading seawater and shallow cold groundwater as it rises along the fault. The results of our MT study confirm earlier inferences that the Xinzhou geothermal field belongs to an intraplate deep-circulation type originated from the mantle heat flow.

A Model for Electrical Conductivity of Porous Materials under Saturated Conditions

Measurements of electrical conductivity have been used for the geological material characterizations due to their sensitivity to various parameters of porous materials. It is one of the most used geophysical methods in geological, geotechnical, and environmental issues. In this study, we develop a theoretical model for predicting the electrical conductivity of porous media under water-saturated conditions using a similarly skewed pore size distribution. The proposed model is related to the electrical conductivity of the pore fluid, the specific electrical conductance and the microstructural parameters of a porous medium. The model predictions are successfully compared with published experimental data as well as another model available in literature. The model opens up new possibilities for prediction of the electrical conductivity of porous materials.

University students’ conceptual understanding of microscopic models of electrical and thermal conduction in solids

Teaching the concepts of electrical and thermal transport in solids begins in elementary school through simple macroscopic models and progressively develops to microscopic quantum models within specialized university courses. Educational research has pointed to a number of misconceptions in this field, especially when it comes to understanding related phenomena at the microscopic level. This study aimed to design an appropriate open-ended version of the concept inventory to test the level of students’ understanding of microscopic models of electrical and thermal conduction in solids (METCS). The METCS concept inventory consists of 27 open-ended questions that examine the understanding of different and interrelated concepts. We used it as a tool for conducting interviews on a sample of ten students from the universities of Rijeka and Split (Croatia). The results of our research confirmed some previously discovered students’ misconceptions and revealed a wide range of new ones. These results can be used to stimulate student discussions and to design curricula and lecture plans for more efficient teaching of transport phenomena in solids. The obtained spectrum of misconceptions will serve as a reference tool for the development of a multiple-choice conceptual METCS test to allow research on larger sample.

Soil thermal conductivity model by de Vries: Re‐examination and validation analysis

AbstractThe thermal conductivity (λ) of soils is an important property in a variety of science and engineering applications. One of the most widely used λ models in soil science was proposed by de Vries (deV‐0). This model is complicated and difficult to use as it is based on several controversial assumptions. The deV‐0 assumes that a soil system is composed of non‐contacting solid particles (rotated uniform ellipsoids) that are dispersed in a continuous homogeneous medium (air or water). Furthermore, deV‐0 assumes that soil solids consist of quartz and consolidated bulk minerals. These assumptions do not reflect the true nature of soils that are composed of several compacted minerals, diverse in shape and notably different in size. A critical analysis of this model concluded that its most controversial feature was inherited from an electrical conductivity model for a two‐phase dispersion system; specifically, from weighting shape factors of non‐contacting rotated oblate ellipsoids. Furthermore, deV‐0 has not yet been fully examined and verified with respect to a comprehensive and complete soil λ database. Also, there is a lack of comparable models to deV‐0 that would contain a complete set of clearly described and linked expressions. Consequently, two slightly adjusted versions of deV‐0 were developed; namely, deV‐1 with soil bulk mineralogy (quartz plus integrated residual minerals) and deV‐2 with complete soil mineralogy (i.e., including individual contributions from all soil minerals). Both models underwent successful calibration and verification against λ data of 39 Canadian field soils and three Standard sands. Markedly improved estimates (λest) were obtained when, instead of dry air thermal conductivity (λa), an apparent air thermal conductivity (λa‐app = λa + λv) was applied (λv represents thermal effects caused by migration of water vapour and evaporation/condensation processes). For deV‐1, the following reduction of standard deviation (SD) data was obtained: 53.5% for 17 coarse soils, 34% for 22 fine soils, and 44.5% for all 39 soils. Then, the same calibration factors of deV‐1 were applied to the deV‐2 model and a similar reduction of SD data was obtained (52.7, 24.1 and 40.1%, respectively). Generally, for 39 Canadian field soils, both models (deV‐1 and deV‐2), with quartz thermal conductivity (λqtz) of 7.6 W·m−1·K−1, produced very close λ estimates (SD ≈ 0.099 and 0.094 W·m−1·K−1, respectively). Taking into account the simplicity of mineral composition and fewer calibration coefficients, deV‐1 was a preferable choice. For that reason, soil bulk mineralogy appears to be a good equivalent to complete soil mineralogy. Also, for Standard sands (100% sand: C‐109, C‐190, NS‐04), improved λest were obtained by replacing λa with λa‐app. Finally, the deV‐1 model was successfully applied to 10 Chinese soils and the following average SD values were obtained: for four coarse soils 0.135 W·m−1·K−1, whereas for six fine soils 0.127 W·m−1·K−1.Highlights The original λ model by de Vries (deV‐0) underestimates experimental λ data. Two modified deV‐0 versions were developed: deV‐1, quartz + bulk minerals; deV‐2, all soil minerals. Improved estimates were obtained when, instead of dry air λ, an apparent air λ was applied. The deV‐1 model was successfully applied to 10 Chinese soils.

Coupled physics simulation of fracture in nuclear fuel pellets induced by resistive heating

While it is well known that ceramic UO 2 fuel cracks early in its life in a nuclear reactor, it is very difficult to collect in-reactor data regarding fuel cracking initiation and propagation to validate fracture models in fuel performance codes. Most fracture data comes from the post-irradiation examination of fuel that has been subjected to long and complex power histories. Replicating the thermal gradients experienced in this fuel to study crack initiation and propagation in a laboratory environment is challenging. This is primarily because the fuel is heated volumetrically by fission, which is difficult to replicate. One way to approximate this volumetric heating out of the reactor is to use electrical resistance (or Joule heating). An electrical conductivity model has been developed and coupled with the existing thermomechanical modeling capability in the BISON nuclear fuel performance code. This will permit simulation of experiments that use resistive heating for the purpose of validating fracture models in BISON. The modeling approach developed here is applied to simulate both historical and current resistive heating experiments on ceramic nuclear fuel.

A new integrated geophysical-petrological global 3-D model of upper-mantle electrical conductivity validated by the Swarm M2 tidal magnetic field

SUMMARY A new global model of the present-day thermochemical state of the lithosphere and upper mantle based on global waveform inversion, satellite gravity and gradiometry measurements, surface elevation and heat flow data has been recently presented: WINTERC-G (Fullea et al. 2021). WINTERC-G is built within an integrated geophysical-petrological framework where the mantle seismic velocity and density fields are computed in a thermodynamically self-consistent framework, allowing for a direct parametrization in terms of the temperature, pressure and composition of the subsurface rocks. In this paper, we combine WINTERC-G thermal and compositional fields along with laboratory experiments constraining the electrical conductivity of mantle minerals, melt and water, and derive a set of new global three dimensional electrical conductivity models of the upper mantle. The new conductivity models, WINTERC-e, consist of two end-members corresponding to minimum and maximum conductivity of the in situ rock aggregate accounting for mantle melting, mineral water content and the individual conductivities of the main stable mantle mineral phases. The end-member models are validated over oceans by simulating the magnetic field induced by the ocean M2 tidal currents and comparing the predicted fields with the M2 tidal magnetic field estimated from 6-yr Swarm satellite observations. Our new conductivity model, derived independently from any surface or satellite magnetic data sets, is however able to predict tidal magnetic fields that are in good agreement with the Swarm M2 tidal magnetic field models estimated by Sabaka et al. and Grayver & Olsen. Our predicted M2 tidal magnetic fields differ in amplitudes by about 5–20 per cent from the Swarm M2 tidal magnetic field, with the high conductivity WINTERC-e end-member model accounting for mantle melt and water content capturing the structure of Swarm data better than the low conductivity end-member model. Spherically symmetric conductivity models derived by averaging new WINTERC-e conductivities over oceanic areas are slightly more conductive than the recent global conductivity models AA17 by Grayver et al. derived from Swarm and CHAMP satellite data in the 60–140 km depth range, while they are less conductive deeper in the mantle. The conductivities in WINTERC-e are about three to four times smaller than the AA17 conductivities at a depth of 400 km. Despite the differences in electrical conductivity, our spherically symmetric high conductivity end-member model WINTERC-e captures the structure of Swarm M2 tidal magnetic field almost the same as a state of the art 1-D conductivity models derived entirely from magnetic data (AA17, Grayver et al.). Moreover, we show that realistic lateral electrical conductivity inhomogeneities of the oceanic upper mantle derived from the temperature, melt and water distributions in WINTERC-e contribute to the M2 tidal magnetic field up to ±0.3 nT at 430 km altitude.

Development of Ji Micromechanics Model for Electrical Conductivity of Carbon Nanotubes-reinforced Samples

In this paper, Ji model for tensile modulus of nanocomposites is expanded to forecast the conductivity of polymer nanocomposites including carbon nanotubes (CNT) summarized as PCNT. The advanced model undertakes the volume fraction of networked CNT and the inherent resistances of tunneling and interphase sections. CNT loading, CNT size and interphase depth suggest the proportion of networked CNT. In addition, the tunneling confrontation is correlated to tunneling width, tunneling distance and polymer tunneling resistivity. The advanced model is used to express the parameters’ roles in the conductivity. Furthermore, the predictions of advanced model are linked to the experimental results of some examples. The proper impressions of all factors on the conductivity as well as the fine agreements among experimental data and calculations justify the advanced model. The radius and length of CNT mainly handle the conductivity, but CNT conduction is useless. Also, a dense interphase causes desirable conductivity, but the interphase conduction cannot govern the conductivity. Moreover, wide tunnels, deprived polymer tunneling resistivity and minuscule tunneling distance enhance the conductivity.

Unravelling the multi-scale structure\u2013property relationship of laser powder bed fusion processed and heat-treated AlSi10Mg

Tailoring heat treatments for Laser Powder Bed Fusion (LPBF) processed materials is critical to ensure superior and repeatable material properties for high-end applications. This tailoring requires in-depth understanding of the LPBF-processed material. Therefore, the current study aims at unravelling the threefold interrelationship between the process (LPBF and heat treatment), the microstructure at different scales (macro-, meso-, micro-, and nano-scale), and the macroscopic material properties of AlSi10Mg. A similar solidification trajectory applies at different length scales when comparing the solidification of AlSi10Mg, ranging from mould-casting to rapid solidification (LPBF). The similarity in solidification trajectories triggers the reason why the Brody-Flemings cellular microsegregation solidification model could predict the cellular morphology of the LPBF as-printed microstructure. Where rapid solidification occurs at a much finer scale, the LPBF microstructure exhibits a significant grain refinement and a high degree of silicon (Si) supersaturation. This study has identified the grain refinement and Si supersaturation as critical assets of the as-printed microstructure, playing a vital role in achieving superior mechanical and thermal properties during heat treatment. Next, an electrical conductivity model could accurately predict the Si solute concentration in LPBF-processed and heat-treated AlSi10Mg and allows understanding the microstructural evolution during heat treatment. The LPBF-processed and heat-treated AlSi10Mg conditions (as-built (AB), direct-aged (DA), stress-relieved (SR), preheated (PH)) show an interesting range of superior mechanical properties (tensile strength: 300–450 MPa, elongation: 4–13%) compared to the mould-cast T6 reference condition.

Micromechanics Modeling of Electrical Conductivity for Polymer Nanocomposites by Network Portion, Interphase Depth, Tunneling Properties and Wettability of Filler by Polymer Media

This study presents a micromechanics model for conductivity of polymer nanocomposites comprising carbon nanotubes (CNT) (PCNT) established by expanded Takayanagi equation. The advanced model presumes the roles of CNT nets, interphase, electron tunneling and wettability of particles by polymer media in the conductivity. The effective filler concentration and percolation onset reflect the contribution of interphase to networks. Moreover, the model properly studies the tunneling properties and wettability based on the available equations. The model’s predictions for some samples are linked to the experimental data. Furthermore, the established model estimates the parameters’ impacts on the conductivity. All forecasts fairly agree with the empirical data of specimens approving the recommended model. A thick interphase, poor CNT curliness, thin CNT, high CNT conduction and large networks improve the conductivity. Furthermore, the conductivity expressively increases to 16 S/m at the largest tunneling diameter (d=30 nm) and the smallest tunneling distance (λ=3 nm), but an insulated sample is observed at λ>5 nm. Therefore, the tunneling dimensions largely manipulate the nanocomposite’s conductivity.

New Insights into Hydrothermal Fluid Circulation Affected by Regional Groundwater Flow in the Asal Rift, Republic of Djibouti

The Asal Rift hosts a lake located in a depression at 150 m below sea level, where recharge is influenced by regional groundwater flow interacting with the Ghoubbet Sea along the coast of Djibouti. This regional groundwater flow is believed to influence hydrothermal fluid circulation, which we aim to better understand in this study, having the objective of developing concepts for geothermal exploration in the area. To this end, magnetotelluric data acquired in the Asal Rift were processed and analyzed. 1D inversion models of electrical conductivity were interpolated for interpretation. These data were then used to build a 2D hydrogeological model, allowing multiphase flow and heat transfer simulations to be performed, considering the regional groundwater flow near the surface and the site topography, in order to confirm the preferred path of fluid flow. Geophysical data analysis indicates the presence of normal faults, notably the H fault, which may act as a conduit for the circulation of hydrothermal fluids and where the hanging wall can be a hydrogeological barrier within the hydrothermal system of the Asal Rift. The results from the 2D numerical flow and heat transfer modelling show the importance of groundwater flow responsible for thermal springs located at the periphery of Asal Lake. Reservoir temperature inferred by means of geothermometry ranging from 200 to 270 °C was shown to correspond to simulated temperature at potential reservoir depth. Moreover, simulated temperature between 600 and 1700 m depth is close to the temperature profile measured in the geothermal well Asal 6 of the area, with less than 20 °C difference. Simulations indicate that hydrothermal fluid circulation is likely influenced by the regional groundwater flow controlled by the topography and the major water bodies, the Ghoubbet Sea and Asal Lake, feeding buoyant fluids interacting with a deep magmatic source and where tectonic activity created normal faults offering a preferred path for fluid circulation.

A piecewise analysis model for electrical conductivity calculation from time domain reflectometry waveforms

Electrical conductivity (EC) represents a material’s ability to conduct electric current. Soil EC has been used as a soil quality attribute related to soil pH, nutrient availability, crop suitability and soil microbial activity. Time domain reflectometry (TDR) estimates soil water content and EC based on the propagation/reflection and energy attenuation of voltage signals along a waveguide. To maximize the data use efficiency, waveform interpretations for simultaneous water content and EC determination are needed. A tangent line/bounded mean oscillation (TL-BMO) model is available to estimate soil water content from TDR waveforms, but an associated EC model is not yet available. The objectives of this study are (1) to introduce a piecewise analysis method for TDR waveform interpretation, and (2) to develop a model for EC computation along a TDR waveguide under homogeneous water content. The proposed model sequentially fits a TDR waveform for the coaxial cable, the connection, and the waveguide according to the transmission line equation. A TDR waveguide can be discretized into multiple successive pieces for the determination of EC variations along the waveguide. Simplifications of the fitting procedures via (1) existing models, e.g., TL-BMO and Topp et al. (1988) models, and (2) analysis of waveforms obtained from controlled conditions, e.g., in distilled water under room temperature (~20 °C) and air pressure (~101 kPa), are also applied. Accuracy and stability of the proposed model are tested via observed TDR waveforms obtained under uniform EC conditions but perturbated with a range of noise levels. EC values computed with only one discretized piece (i.e., no discretization along the waveguide) are consistent with the theoretical EC values, and the results are robust for all of the tested noise levels. As the number of discretized pieces and the noise levels increase, numerical oscillations in the results increase. The maximum relative errors are <20%, occurring when the mean power of noise is as large as the mean power of waveforms (0 dB noise). Flexibility of the proposed model is tested using waveforms simulated under spatially varying EC, and the EC variations along a TDR waveguide can be detected by the proposed model. In summary, the proposed model provides reliable EC estimations, and it can evaluate uniform or varying EC distributions along a TDR waveguide under uniform moisture conditions. This model can be imbedded into the TL-BMO model for integrated water content and EC determination for commonly measured (251-scanning point) TDR waveforms.

Bipolar and Complementary Resistive Switching Characteristics and Neuromorphic System Simulation in a Pt/ZnO/TiN Synaptic Device.

In this work, a ZnO-based resistive switching memory device is characterized by using simplified electrical conduction models. The conventional bipolar resistive switching and complementary resistive switching modes are accomplished by tuning the bias voltage condition. The material and chemical information of the device stack including the interfacial layer of TiON is well confirmed by transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS) analysis. The device exhibits uniform gradual bipolar resistive switching (BRS) with good endurance and self-compliance characteristics. Moreover, complementary resistive switching (CRS) is achieved by applying the compliance current at negative bias and increasing the voltage at positive bias. The synaptic behaviors such as long-term potentiation and long-term depression are emulated by applying consecutive pulse input to the device. The CRS mode has a higher array size in the cross-point array structure than the BRS mode due to more nonlinear I–V characteristics in the CRS mode. However, we reveal that the BRS mode shows a better pattern recognition rate than the CRS mode due to more uniform conductance update.

Evaluation and modeling of electrical conductivity in conductive polymer nanocomposite foams with multiwalled carbon nanotube networks

Conductive filler/polymer composite foams (CPC) with micro-/nano-scale bubbles have attracted much attention due to their various advantages. Understanding the evolution of electrical behavior in CPC foams is important for their functional application. There have been many experimental investigations of the electrical behavior of CPC foams, but how the electrical conductivity varies with bubble growth is not fully understood. Here, a novel resistive network model based on Monte Carlo simulation to directly predict the electrical conductivity of CPC foams is reported. The model uses multiwalled carbon nanotubes (MWCNTs) as a conductive filler and considers both the intrinsic electrical conductivity of the nanotubes and the electron tunneling effect. The model predictions agreed very well with the experimental data for both the solid and foamed composites. The results showed that the percolation threshold and the conductivity are strongly affected by the relative sizes of MWCNT length and bubble diameter. At relatively low void fractions (up to ~20%), the growth of bubbles with size comparable to the MWCNT length increased the conductivity. Further growth of cells (>30%) resulted in a gradual decrease in the conductivity. This model can be used in the design and optimization of conductive foams.