Search Results (29)

Conductive polymer composites (CPCs) filled with anisotropic materials such as carbon nanotubes (CNTs) exhibit electrical behavior governed by percolation through filler networks. While filler volume and shape are commonly studied, the influence of orientation and alignment remains underexplored. This study uses Monte Carlo simulations to examine how the mean orientation angle and angular dispersion of CNTs affect conductive network formation. The results demonstrate that electrical connectivity is highly sensitive to orientation. Contrary to conventional assumptions, maximum connectivity occurred not at 45° but at around 55–60°. A Gaussian-based orientation probability function was proposed to model this behavior. Additionally, increased orientation dispersion enhanced conductivity in cases where alignment initially hindered connection, highlighting the dual role of alignment and randomness. These findings position orientation as a critical design parameter—beyond filler content or geometry—for engineering CPCs with optimized electrical performance. The framework provides guidance for processing strategies that control alignment and supports applications such as stretchable electronics, directional sensors, and multifunctional materials. Future research will incorporate full 3D orientation modeling to reflect complex manufacturing conditions. Full article

Conductive polymer composites (CPCs) are widely used in flexible electronics due to their tunable electrical properties and mechanical deformability. However, accurately predicting the evolution of conductive networks, particularly under compressive strain, remains a significant challenge. In this study, we developed a statistical mechanics model and an extended dynamic statistical mechanics model to quantitatively describe percolation behavior in CPCs. The static model incorporates filler geometry, aspect ratio (AR), and surface-to-volume ratio, and was validated using Monte Carlo simulations. Results show that the percolation threshold for spherical fillers was 0.11965, while significantly lower values of 0.00669 and 0.00203 were observed for plate- and rod-shaped fillers, respectively, confirming the enhanced connectivity of anisotropic particles. To capture strain-dependent behavior, a dynamic model was constructed using a Smoluchowski-type gain–loss framework. This model separates conductive network formation (gain) from network disconnection (loss) caused by filler alignment and Poisson-induced expansion. At high Poisson’s ratios (0.3 and 0.5), the model accurately predicted the reduction in connectivity, particularly for anisotropic fillers. Across all tested conditions, the model exhibited strong agreement with simulation data, with RMSE values ranging from 0.0004 to 0.0449. The results confirm that high AR fillers enhance conductivity under compression, while large Poisson’s ratios suppress network formation. These findings provide a reliable, physically grounded modeling framework for designing strain-sensitive devices such as flexible pressure sensors. Full article

This study investigates the impact of graphite (GR) concentration and particle size on the performance of conductive polymer composites (CPCs) using polyvinylidene fluoride (PVDF), polypropylene (PP), and polyethylene terephthalate (PET) as matrix materials. Composites were prepared with GR concentrations ranging from 20 to 60 wt. % and particle sizes categorized as G1 (5.9 µm), G2 (17.8 µm), and G3 (561 µm), and evaluated for their electrical, thermal, and mechanical properties. The investigation of the effect of graphite particle size on composite properties represents the main originality of this work. Among all composites, PVDF containing 60 wt. % of medium-sized G2 particles exhibited the lowest electrical resistivity (0.77 ohm·cm through-plane and 0.69 ohm·cm in-plane), along with the highest residual ash content (72%). In PP and PET matrices, incorporating 60 wt. % G2 particles resulted in through-plane resistivities of 11.3 ohm·cm and 1.6 ohm·cm, and in-plane resistivities of 5 ohm·cm and 1.2 ohm·cm, respectively, with thermal decomposition temperatures of 374 °C and 401 °C. Regarding mechanical performance and thermal stability, composites with small-sized G1 particles demonstrated superior performance due to their larger surface area and stronger matrix interactions. The PVDF/G1 (40/60 wt. %) composite achieved the highest flexural modulus (6.8 GPa), flexural strength (38.6 MPa), compressive modulus (0.28 GPa), and decomposition temperature (445 °C), highlighting its exceptional properties. These CPCs show significant promise for energy and electronic applications, particularly in the fabrication of bipolar plates for proton exchange membrane fuel cells, as well as in shielding materials and thermoelectric devices. Full article

Polydimethylsiloxane (PDMS) and poly(3,4-ethylene dioxythiophene):poly(4-styrene-sulfonate) (PEDOT:PSS) composites were tested to determine their suitability for charging small-scale batteries in conjunction with a piezoelectric actuator as an energy harvester. Two different PEDOT:PSS patterns (zigzag and serpentine) were tested, and the maximum DC voltage of a system incorporating PEDOT:PSS was determined. The aim of this work is to study the effect of soft corners in the electrical routing of aircraft and IoT sensors. The zigzag and serpentine patterns were considered for this study because of their simplicity in design. Without the polymer, 2.3 V was produced by the actuator, while adding PEDOT:PSS resulted in the voltage being reduced to 1.7 V. The piezoelectric actuator was connected to a 3.6 V rechargeable Li-ion battery, and the battery’s voltage was recorded over 1 h. The voltage from the piezoelectric actuator was 3.8 V. Without PEDOT:PSS, the battery was charged to a maximum of 3 V. Adding the PEDOT:PSS to the circuit reduced the maximum charge to a voltage of 2 V. The results indicate that while PEDOT:PSS composites can be used in conjunction with piezoelectric energy harvesters, more work is still needed to optimize the system to increase efficiency and charging rates. Full article

Conductive polymer composites (CPCs) with nanocarbon fillers are at the high end of modern materials science, advancing current electronic applications. Herein, we establish the interplay between the chemistry and electrophysical properties of reduced graphene oxide (rGO), separately and as a filler for CPCs with the segregated structure conferred by the chemical composition of the initial graphene oxide (GO). A set of experimental methods, namely X-ray photoelectron spectroscopy (XPS), ultraviolet-visible spectroscopy, van der Paw and temperature-dependent sheet resistance measurements, along with dielectric spectroscopy, are employed to thoroughly examine the derived materials. The alterations in the composition of oxygen groups along with their beneficial effect on nitrogen doping upon GO reduction by hydrazine are tracked with the help of XPS. The slight defectiveness of the graphene network is found to boost the conductivity of the material due to facilitating the impact of the nitrogen lone-pair electrons in charge transport. In turn, a sharp drop in material conductivity is indicated upon further disruption of the π-conjugated network, predominantly governing the charge transport. Particularly, the transition from the Mott variable hopping transport mechanism to the Efros–Shklovsky one is signified. Finally, the impact of rGO chemistry and physics on the electrophysical properties of CPCs with the segregated structure is evaluated. Taken together, our results give a hint at how GO chemistry manifests the properties of rGO and the CPC derived from it, offering compelling opportunities for their practical applications. Full article

Additive manufacturing (AM) of components using material extrusion (MEX) offers the potential for the integration of functions through the use of multi-material design, such as sensors, actuators, energy storage, and electrical connections. However, there is a significant gap in the availability of electrical composite properties, which is essential for informed design of electrical functional structures in the product development process. This study addresses this gap by systematically evaluating the resistivity (DC, direct current) of 14 commercially available filaments as unprocessed filament feedstock, extruded fibers, and fabricated MEX-structures. The analysis of the MEX-structures considers the influence of anisotropic electrical properties induced by the selective material deposition inherent to MEX. The results demonstrate that composites containing fillers with a high aspect ratio, such as carbon nanotubes (CNT) and graphene, significantly enhance conductivity and improve the reproducibility of MEX structures. Notably, the extrusion of filaments into MEX structures generally leads to an increase in resistivity; however, composites with CNT or graphene exhibit less reduction in conductivity and lower variability compared to those containing only carbon black (CB) or graphite. These findings underscore the importance of filler selection and composition in optimizing the electrical performance of MEX structures. Full article

The enhancement of the electromagnetic interference shielding efficiency (EMI SE) for conductive polymer composites (CPCs) has garnered increasing attention. The shielding performance is influenced by conductivity, which is dependent on the establishment of effective conductive pathways. In this review, Schelkunoff’s theory on outlining the mechanism of electromagnetic interference shielding was briefly described. Based on the mechanism, factors that influenced the electrical percolation threshold of CPCs were presented and three main kinds of efficient methods were discussed for establishing conductive pathways. Furthermore, examples were explored that highlighted the critical importance of such conductive pathways in attaining optimal shielding performance. Finally, we outlined the prospects for the future direction for advancing CPCs towards a balance of enhanced EMI SE and cost–performance. Full article

Conductive polymer composites (CPCs) filled with carbon-based materials are widely used in the fields of antistatic, electromagnetic interference shielding, and wearable electronic devices. The conductivity of CPCs with a carbon-based filling is reflected by their electrical percolation behavior and is the focus of research in this field. Compared to experimental methods, Monte Carlo simulations can predict the conductivity and analyze the factors affecting the conductivity from a microscopic perspective, which greatly reduces the number of experiments and provides a basis for structural design of conductive polymers. This review focuses on Monte Carlo models of CPCs with a carbon-based filling. First, the theoretical basis of the model’s construction is introduced, and a Monte Carlo simulation of the electrical percolation behaviors of spherical-, rod-, disk-, and hybridfilled polymers and the analysis of the factors influencing the electrical percolation behavior from a microscopic point of view are summarized. In addition, the paper summarizes the progress of polymer piezoresistive models and polymer foaming structure models that are more relevant to practical applications; finally, we discuss the shortcomings and future research trends of existing Monte Carlo models of CPCs with carbon-based fillings. Full article

Conductive polymer composites (CPCs), obtained by incorporating conductive fillers into a polymer matrix, are suitable for producing strain sensors for structural health monitoring (SHM) in infrastructure. Here, the effect of the addition of inorganic semiconductor nanoparticles (INPs) to a poly (vinylidene fluoride) (PVDF) composite filled with multi-walled carbon nanotubes (MWCNTs) on the piezoresistive behavior is investigated. INPs with different morphologies and sizes are synthesized by a hydrothermal method. The added inorganic oxide semiconductors showed two distinct morphologies, including different phases. While particles with flower-like plate morphology contain phases of orth-ZnSnO₃ and SnO, the cauliflower-like nanoparticles contain these metal oxides and ZnO. The nanoparticles are characterized by field-emission scanning electron microscopy (FE-SEM) and X-ray diffraction (XRD), and the nanocomposites by Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA). Cyclic tensile testing is applied to determine the strain-sensing behavior of PVDF/1 wt% MWCNT nanocomposites with 0–10 wt% inorganic nanoparticles. Compared to the PVDF/1 wt% MWCNT nanocomposite, the piezoresistive sensitivity is higher after the addition of both types of nanoparticles and increases with their amount. Thereby, nanoparticles with flower-like plate structures improve strain sensing behavior slightly more than nanoparticles with cauliflower-like structures. The thermogravimetric analysis results showed that the morphology of the semiconductor nanoparticles added to the PVDF/MWCNT matrix influences the changes in thermal properties. Full article

The objective of this research was to develop highly effective conductive polymer composite (CPC) materials for flexible piezoresistive sensors, utilizing hollow three-dimensional graphitic shells as a highly conductive particulate component. Polystyrene (PS), a cost-effective and robust polymer widely used in various applications such as household appliances, electronics, automotive parts, packaging, and thermal insulation materials, was chosen as the polymer matrix. The hollow spherical three-dimensional graphitic shells (GS) were synthesized through chemical vapor deposition (CVD) with magnesium oxide (MgO) nanoparticles serving as a support, which was removed post-synthesis and employed as the conductive filler. Commercial multi-walled carbon nanotubes (CNTs) were used as a reference one-dimensional graphene material. The main focus of this study was to investigate the impact of the GS on the piezoresistive response of carbon/polymer composite thin films. The distribution and arrangement of GS and CNTs in the polymer matrix were analyzed using techniques such as X-ray diffraction and scanning electron microscopy, while the electrical, thermal, and mechanical properties of the composites were also evaluated. The results revealed that the PS composite films filled with GS exhibited a more pronounced piezoresistive response as compared to the CNT-based composites, despite their lower mechanical and thermal performance. Full article

Soft strain sensors based on conductive polymer composites (CPCs) provide a simple and feasible detection tool in wearable electronics, soft machines, electronic skin, etc. However, the CPCs-based soft strain sensors exhibit resistive viscoelasticity (or time-dependent properties) that hinder the intuitive reflection of the accurate strain and a simple calibration process. In this paper, CPCs with different carbon nanotubes (CNTs) and carbon black (CB) contents were prepared, and electro-mechanical experiments were conducted to study the effect of filler dimensionality and content on the resistive viscoelasticity of CPCs, aimed at guiding the fabrication of CPCs with low resistive viscoelasticity. Furthermore, resistive viscoelasticity and mechanical viscoelasticity were compared to study the origin of the resistive viscoelasticity of CPCs. We found that, at the vicinity of their percolation threshold, the CPCs exhibit high resistive viscoelasticity despite their high sensitivity. In addition, the secondary peaks for CB/SR composite were negligible when the CB concentration was low. Generally, compared with one-dimensional CNT-filled CPCs, the zero-dimensional CB-filled CPCs show higher sensitivity, lower resistive hysteresis, lower resistance relaxation ratio, and better cyclic performance, so they are more suitable for sensor usage. By comparing the resistive viscoelasticity and mechanical viscoelasticity of CPCs, it is indicated that, when the concentration of nanoparticles (NPs) approaches the percolation thresholds, the resistive viscoelasticity is mainly derived from the change of conductive network, while when the concentration of NPs is higher, it is primarily due to the unrecoverable deformations inside the material. Full article

Conductive polymer composites (CPCs) have shown potential for structural health monitoring applications based on repeated findings of irreversible transducer electromechanical property change due to fatigue. In this research, a high-fidelity stochastic modeling framework is explored for predicting the electromechanical properties of spherical element-based CPC materials at bulk scales. CPC dogbone specimens are manufactured via casting and their electromechanical properties are characterized via uniaxial tensile testing. Model parameter tuning, demonstrated in previous works, is deployed for improved simulation fidelity. Modeled predictions are found in agreement with experimental results and compared to predictions from a popular analytical model in the literature. Full article

Due to the properties of a positive temperature coefficient (PTC) effect and a negative temperature coefficient (NTC) effect, electrically conductive polymer composites (CPCs) have been widely used in polymer thermistors. A dual percolated conductive microstructure was prepared by introducing the polybutylene adipate terephthalate phase (PBAT) into graphene nanoplatelets (GNPs)-filled polylactic acid (PLA) composites, intending to develop a favorable and stable PTC material. To achieve this strategy, GNPs were selectively distributed in the PBAT phase by injection molding. In this study, we investigated the crystallization behavior, electrical conductivity, and temperature response of GNP-filled PLA/PBAT composites. The introduction of GNPs into PLA significantly increased PLA crystallization capacity, where the crystallization onset temperature (T_o) is raised from 116.7 °C to 134.7 °C, and the crystallization half-time (t_1/2) decreases from 35.8 min to 27.3 min. The addition of 5 wt% PBAT increases the electrical conductivity of PLA/PBAT/GNPs composites by almost two orders of magnitude when compared to PLA/GNPs counterparts. The temperature of the heat treatment is also found to play a role in affecting the electrical conductivity of PLA-based composites. Increasing crystallinity is favorable for increasing electrical conductivity. PLA/PBAT/GNPs composites also show a significant positive temperature coefficient, which is reflected in the temperature–electrical resistance cycling tests. Full article

In many textile fields, such as industrial structures or clothes, one way to detect a specific liquid leak is the electrical conductivity variation of a yarn. This yarn can be developed using melt spun of Conductive Polymer Composites (CPCs), which blend insulating polymer and electrically conductive fillers. This study examines the influence of the proportions of an immiscible thermoplastic/elastomer blend for its implementation and its water detection. The thermoplastic polymer used for the detection property is the polyamide 6.6 (PA6.6) filled with enough carbon nanotubes (CNT) to exceed the percolation threshold. However, the addition of fillers decreases the polymer fluidity, resulting in the difficulty to implement the CPC. Using an immiscible polymers blend with an elastomer, which is a propylene-based elastomer (PBE) permits to increase this fluidity and to create a flexible conductive monofilament. After characterizations (morphology, rheological and mechanical) of this blend (PA6.6_CNT/PBE) in different proportions, two principles of water detection are established and carried out with the monofilaments: the principle of absorption and the short circuit. It is found that the morphology of the immiscible polymer blend had a significant role in the water detection. Full article

Conductive polymer composites (CPC) from renewable resources exhibit many interesting characteristics due to their biodegradability and conductivity changes under mechanical, thermal, chemical, or electrical stress. This study is focused on investigating the physical properties of electroconductive thermoplastic starch (TPS)–based composites and changes in electroconductive paths during cyclic deformation. TPS–based composites filled with various carbon black (CB) contents were prepared through melt processing. The electrical conductivity and physicochemical properties of TPS–CB composites, including mechanical properties and rheological behavior, were evaluated. With increasing CB content, the tensile strength and Young’s modulus were found to increase substantially. We found a percolation threshold for the CB loading of approximately 5.5 wt% based on the rheology and electrical conductivity. To observe the changing structure of the conductive CB paths during cyclic deformation, both the electrical conductivity and mechanical properties were recorded in parallel using online measurements. Moreover, the instant electrical conductivity measured online during mechanical deformation of the materials was taken as the parameter indirectly describing the structure of the conductive CB network. The electrical conductivity was found to increase during five runs of repeated cyclic mechanical deformations to constant deformation below strain at break, indicating good recovery of conductive paths and their new formation. Full article