Ultra-Low Percolation Threshold Induced by Thermal Treatments in Co-Continuous Blend-Based PP/PS/MWCNTs Nanocomposites

A Review of the Establishment of Effective Conductive Pathways of Conductive Polymer Composites and Advances in Electromagnetic Shielding

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.

Unveiling the restricted mobility of carbon nanotubes inside a long chain branched polymer matrix via probing the shear flow effects on the rheological and electrical properties of the filled systems

The present work has aimed at gaining a deeper understanding of the effects of shear flow on the behaviors of nano filler evolution inside linear and long chain branched polymer matrices. Accordingly, measurements consisting of transient start-up shear rheology coupled with small amplitude oscillatory sweep (SAOS) and dielectric tests were designed. Linear polypropylene (PPC) and polypropylene (PPH) with long chain branching (LCB) were chosen as the polymer matrices and carbon nanotubes (CNTs) as the nanofillers. The percolation threshold of the LCB PPH nanocomposites was found to be higher than for linear PPC, due to the high viscosity and elasticity of LCB PPH. A transient shear with different shear rates was imposed on the composites after which SAOS and electrical conductivity measurements were conducted. The liquid-solid transitions of the nanocomposites were found to be different and to depend on the shear flow conditions (shear rate). For the linear PPC, higher shear rates caused the filler network to break down while lower shear rates helped the nanofillers to agglomerate. Interestingly, for LCB PPH, both higher and lower pre-shear rates resulted in the breakup of the filler networks, which was due to the restricted mobility of the CNTs by the LCB. The confinement of the polymer chains to the CNTs and their aggregates made it difficult for the fillers to move thus causing the formed network to be easily destroyed even under slow and slight shears. Similarly, the trend was also found after shear flows as reflected by the increase and decrease of electrical conductivities.

Predicting of tunneling resistivity between adjacent nanosheets in graphene-polymer systems

In this work, the tunneling resistivity between neighboring nanosheets in grapheme-polymer nanocomposites is expressed by a simple equation as a function of the characteristics of graphene and tunnels. This expression is obtained by connecting two advanced models for the conductivity of graphene-filled materials reflecting tunneling role and interphase area. The predictions of the applied models are linked to the tested data of several samples. The impressions of all factors on the tunneling resistivity are evaluated and interpreted using the suggested equation. The calculations of tunneling resistivity for the studied examples by the model and suggested equation demonstrate the same levels, which confirm the presented methodology. The results indicate that the tunneling resistivity decreases by super-conductive graphene, small tunneling width, numerous contacts among nanosheets and short tunneling length.

Influence of Polymer Processing on the Double Electrical Percolation Threshold in PLA/PCL/GNP Nanocomposites

For the first time, the double electrical percolation threshold was obtained in polylactide (PLA)/polycaprolactone (PCL)/graphene nanoplatelet (GNP) composite systems, prepared by compression moulding and fused filament fabrication (FFF). Using scanning electron microscopy (SEM) and atomic force microscopy (AFM), the localisation of the GNP, as well as the morphology of PLA and PCL phases, were evaluated and correlated with the electrical conductivity results estimated by the four-point probe method electrical measurements. The solvent extraction method was used to confirm and quantify the co-continuity in these samples. At 10 wt.% of the GNP, compression-moulded samples possessed a wide co-continuity range, varying from PLA55/PCL45 to PLA70/PCL30. The best electrical conductivity results were found for compression-moulded and 3D-printed PLA65/PCL35/GNP that have the fully co-continuous structure, based on the experimental and theoretical findings. This composite owns the highest storage modulus and complex viscosity at low angular frequency range, according to the melt shear rheology. Moreover, it exhibited the highest char formation and polymers degrees of crystallinity after the thermal investigation by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC), respectively. The effect of the GNP content, compression moulding time, and multiple twin-screw extrusion blending steps on the co-continuity were also evaluated. The results showed that increasing the GNP content decreased the continuity of the polymer phases. Therefore, this work concluded that polymer processing methods impact the electrical percolation threshold and that the 3D printing of polymer composites entails higher electrical resistance as compared to compression moulding.

Modeling of Electrical Conductivity for Polymer-Carbon Nanofiber Systems

There is not a simple model for predicting the electrical conductivity of carbon nanofiber (CNF)-polymer composites. In this manuscript, a model is proposed to predict the conductivity of CNF-filled composites. The developed model assumes the roles of CNF volume fraction, CNF dimensions, percolation onset, interphase thickness, CNF waviness, tunneling length among nanoparticles, and the fraction of the networked CNF. The outputs of the developed model correctly agree with the experimentally measured conductivity of several samples. Additionally, parametric analyses confirm the acceptable impacts of main factors on the conductivity of composites. A higher conductivity is achieved by smaller waviness and lower radius of CNFs, lower percolation onset, less tunnel distance, and higher levels of interphase depth and fraction of percolated CNFs in the nanocomposite. The maximum conductivity is obtained at 2.37 S/m by the highest volume fraction and length of CNFs.

Effective Conductivity of Carbon-Nanotube-Filled Systems by Interfacial Conductivity to Optimize Breast Cancer Cell Sensors

Interfacial conductivity and “L_c”, i.e., the least carbon-nanotube (CNT) length required for the operative transfer of CNT conductivity to the insulated medium, were used to establish the most effective CNT concentration and portion of CNTs needed for a network structure in polymer CNT nanocomposites (PCNT). The mentioned parameters and tunneling effect define the effective conductivity of PCNT. The impact of the parameters on the beginning of percolation, the net concentration, and the effective conductivity of PCNT was investigated and the outputs were explained. Moreover, the calculations of the beginning of percolation and the conductivity demonstrate that the experimental results and the developed equations are in acceptable agreement. A small “L_c” and high interfacial conductivity affect the beginning of percolation, the fraction of networked CNTs, and the effective conductivity. Additionally, a low tunneling resistivity, a wide contact diameter, and small tunnels produce a highly effective conductivity. The developed model can be used to optimize breast cancer cell sensors.

Thermal/Electrical Properties and Texture of Carbon Black PC Polymer Composites near the Electrical Percolation Threshold

Polycarbonate (PC), a thermoplastic polymer with excellent properties, is used in many advanced technological applications. When PC is blended with other polymers or additives, new properties, such as electrical properties, can be available. In this study, carbon black (CB) was melt-compounded with PC to produce polymer compounds with compositions (10–16 wt.% of CB), which are close to or above the electrical percolation threshold (13.5–14 wt.% of CB). Effects due to nanofiller dispersion/aggregation in the polymer matrix, together with phase composition, glass transition temperature, morphology and textural properties, were studied by using thermal analysis methods (thermogravimetry and differential scanning calorimetry) and scanning electron microscopy. The DC electrical properties of these materials were also investigated by means of electrical conductivity measurements and correlated with the “structure” of the CB, to better explain the behaviour of the composites close to the percolation threshold.