Literature DB >> 29987658

Electrical tree inhibition by SiO2/XLPE nanocomposites: insights from first-principles calculations.

Xiaonan Zheng1, Yang Liu2, Ya Wang1.   

Abstract

It has been extensively observed in experiments that nanoparticle additives can efficiently inhibit the electrical tree growth of the cross-linked polyethylene (XLPE) matrix of power cables. Inspired by this, the first-principles calculations employing the density functional theory (DFT) method were performed in this study to investigate the significant role of SiO2 nanosized fillers as a voltage stabilizer for power cable insulation. Several different types of α-SiO2 fillers, including hydroxylated, reconstructed, doped or oxygen vacancy surface structures, were constructed to model the interfacial interaction for SiO2/XLPE nanocomposites. It is found that the SiO2 additives can restrict the movement of the polyethylene chain through van der Waals physical interaction. More importantly, based on the Bader charge analysis we reveal that SiO2 could effectively capture hot electrons to suppress space charge accumulation in XLPE. However, some particular modified-surface SiO2, such as incompletely hydroxylated, B-doped, and oxygen vacancy defect on the top layer, could induce the H migration reaction and consequent electrical tree growth of the XLPE chain. In contrast, the SiO2 particles that have N-doped or oxygen vacancy on the lower layer with completely hydroxylated surfaces, as well as the reconstructed surface, are predicted to be favorable additives because of their quite strong physical interaction and very weak chemical activity with XLPE. The present study is useful to understand the mechanism of the nanosized voltage stabilizer and also provide important information for further experimental investigation.

Entities:  

Keywords:  Cross-linked polyethylene; Density functional theory; Electrical tree inhibition; Interfacial interaction; SiO2

Year:  2018        PMID: 29987658     DOI: 10.1007/s00894-018-3742-4

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  9 in total

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