Application and Suitability of Polymeric Materials as Insulators in Electrical Equipment

Dielectric, Mechanical, and Thermal Properties of Crosslinked Polyethylene Nanocomposite with Hybrid Nanofillers

Crosslinked polyethylene (XLPE) nanocomposite has superior insulation performance due to its excellent dielectric, mechanical, and thermal properties. The incorporation of nano-sized fillers drastically improved these properties in XLPE matrix due to the reinforcing effect of interfacial region between the XLPE–nanofillers. Good interfacial strength can be further improved by introducing a hybrid system nanofiller as a result of synergistic interaction between the nanofiller relative to a single filler system. Another factor affecting interfacial strength is the amount of hybrid nanofiller. Therefore, the incorporation amount of hybridising layered double hydroxide (LDH) with aluminium oxide (Al2O3) nanofiller into the XLPE matrix was investigated. Herein, the influence of hybrid nanofiller content and the 1:1 ratio of LDH to Al2O3 on the dielectric, mechanical, and thermal properties of the nanocomposite was studied. The structure and morphology of the XLPE/LDH-Al2O3 nanocomposites revealed that the hybridisation of nanofiller improved the dispersion state. The dielectric, mechanical, and thermal properties, including partial discharge resistance, AC breakdown strength, and tensile properties (tensile strength, Young’s modulus, and elongation at break) were enhanced since it was influenced by the synergetic effect of the LDH-Al2O3 nanofiller. These properties were increased at optimal value of 0.8 wt.% before decreasing with increasing hybrid nanofiller. It was found that the value of PD magnitude improvement went down to 47.8% and AC breakdown strength increased by 15.6% as compared to pure XLPE. The mechanical properties were enhanced by 14.4%, 31.7%, and 23% for tensile strength, Young’s modulus, and elongation at break, respectively. Of note, the hybridisation of nanofillers opens a new perspective in developing insulating material based on XLPE nanocomposite.

Temperature Rise of an Adhesive Particle-Reinforced Polymer during Fatigue Testing

Construction adhesives are usually polymers that have been modified to achieve specific properties so that they can be used under various loading conditions. An attempt was made to estimate the effect of fatigue loading on the temperature of an adhesive material by further physically modifying the basic adhesive composition used in the research. The temperature of the materials during the tests was recorded using a thermal imaging camera and a thermoelectric thermometer. For most materials tested at 20 Hz, an increase in the number of load cycles corresponded to an increase in the temperature of the samples. For a frequency of 30 Hz, after the temperature increased by a certain value, the temperature of the modified samples recorded with the thermal imaging camera decreased. Fatigue loading caused an increase of the temperature of all tested polymeric materials. Observation of the sample during testing with a thermal imaging camera allows a simple identification of the areas with the highest temperature and can be much more useful in practice than recording temperatures with a thermocouple thermometer, as thermocouples need to be properly positioned before testing.

LGB-Stack: Stacked Generalization with LightGBM for Highly Accurate Predictions of Polymer Bandgap

Recently, the Ramprasad group reported a quantitative structure-property relationship (QSPR) model for predicting the E _gap values of 4209 polymers, which yielded a test set R ² score of 0.90 and a test set root-mean-square error (RMSE) score of 0.44 at a train/test split ratio of 80/20. In this paper, we present a new QSPR model named LGB-Stack, which performs a two-level stacked generalization using the light gradient boosting machine. At level 1, multiple weak models are trained, and at level 2, they are combined into a strong final model. Four molecular fingerprints were generated from the simplified molecular input line entry system notations of the polymers. They were trimmed using recursive feature elimination and used as the initial input features for training the weak models. The output predictions of the weak models were used as the new input features for training the final model, which completes the LGB-Stack model training process. Our results show that the best test set R ² and the RMSE scores of LGB-Stack at the train/test split ratio of 80/20 were 0.92 and 0.41, respectively. The accuracy scores further improved to 0.94 and 0.34, respectively, when the train/test split ratio of 95/5 was used.

Nonlinear Surface Conductivity Characteristics of Epoxy Resin-Based Micro-Nano Structured Composites

Nonlinear composite materials serve to homogenize electric fields and can effectively improve the local concentration of the electric field in power systems. In order to study the nonlinear surface conductivity properties of micro-nano epoxy composites, two types of epoxy micro-nano composite specimens were prepared in the laboratory using the co-blending method. The surface conductivity of the composites was tested under different conditions using a high-voltage DC surface conductivity test system. The results show that the surface conductivity of micro-nano structured composites increases and then decreases with the rise of nanofiller doping concentration. The nonlinear coefficient was 1.781 at 4 wt% of doped nanostructured SiC, which was the most significant nonlinear coefficient compared to other doping contents. For the same doping concentration, the micro-nano structured composites doped with nanostructured SiC have more significant surface conductivity at the same test temperature with a nonlinear coefficient of 1.635. As the temperature increases, the surface conductivity of the micro-nano structured composite increases significantly, and the threshold field strength moves towards the high electric field. Along with the increase in temperature, the nonlinear coefficients of micro-nano composites after doping with nanostructured SiC showed a gradually decreasing trend. The temperature has little effect on the nonlinear coefficients of the micro-nano structured composites after doping with O-MMT.

Influence of Ramped Compression on the Dielectric Behavior of the High-Voltage Epoxy Composites

The emergence of micro and nano-based inorganic oxide fillers with optimal filler-loadings further enhances the required insulation characteristics of neat epoxy. During manufacturing and service application, insulators and dielectrics face mechanical stresses which may alter their basic characteristics. Keeping this in mind, the facts' influence of mechanical stresses and fillers on dielectric properties of polymeric insulators of two epoxy/silica composites were fabricated and thoroughly analyzed for dielectric characteristics under ramped mechanical compressions relative to the unfilled sample. Before compression, epoxy nanocomposites exhibited responses having an average dielectric constant of 7.68 with an average dissipation factor of 0.18. After each compression, dielectric properties of all samples were analyzed. The dissipation factor and the dielectric constant trends of each sample are plotted against a suitable frequency range. It was observed that after the successive compressions up to 25 MPa, the dielectric properties of epoxy micro-silica composites were highly affected, having an average final dielectric constant of 9.65 times that of the uncompressed sample and a dissipation factor of 2.2 times that of the uncompressed sample, and these were recorded.