Chain?Like Semiconductive Fillers for Dielectric Enhancement and Loss Reduction of Polymer Composites

Two types of chain?like nanofibers (TiO2 and TINO) are synthesized by electrospinning for the dielectric composites. The intrinsic high?temperature loss tangent is effectively reduced by the atomic layer deposition?coated alumina shells on the nanofibers, which blocks carrier movement across the interfaces. The transformed crystalline porous alumina can further reduce dielectric loss by isolating the polymer from the nanofibers.Dielectric loss is a crucial factor in determining the long?term endurance for security and energy loss of dielectric composites. Here, chain?like semiconductive fibers of titanium oxide, indium, and niobium?doped titanium oxide are used for enhancing the complex dielectric properties of a polymer through composite construction, which involves significant interface enhancements. The chain?like fibers significantly enhance the dielectric constant owing to the special morphology of the fillers and their interfacial polarization, especially at higher temperatures. The dielectric loss and electrical conductivity of the composites are substantially reduced across the entire investigated temperature range, achieved by passivating the fiber surface with an alumina shell using atomic layer deposition. The as?deposited alumina shell transformed from an amorphous to a crystalline phase through thermal annealing results in a porous shell and more effective suppression of the loss tangent and electrical conductivity. A plausible mechanism for loss suppression is associated with carrier movement along the surface of the fibers and bulk, leading to a higher loss tangent. The alumina shell blocks the carrier transport path, particularly at the interfaces, resulting in a reduced interfacial polarization contribution and energy storage loss. This study provides a method for inhibiting dielectric loss by fabricating fillers with special surfaces.

» Publication Date: 31/03/2024

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This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737


                   




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