Molecular dynamics study on functional group surface modified graphene oxide towards enhanced dielectric properties and thermal conductivity of natural ester insulating oil

Danquan Lan, Yiyi Zhang, Pengfei Jia, Xianfu Lin, Chuanhui Xu, Heqi Song, Wenchang Wei, Zhicheng Su and Xingtuo Zhang

Renewable Energy, 2025, vol. 250, issue C

Abstract: As a sustainable dielectric fluid critical for next-generation green power grids, natural ester insulating oil requires rational design strategies to overcome performance limitations. This study provided a simulation-guided experimental strategy to enhance the performance of nano-natural ester insulating oil. Through multi-scale molecular dynamics (MD) simulations, we established an atomistic model of 3-aminopropyltriethoxysilane (APTES)-functionalized graphene/natural ester systems, systematically evaluating dielectric response, thermal transport, and interfacial interactions characteristics. Based on the simulation results, nano-modified graphene/natural ester insulating oils with optimized concentration (0.05 g/L) were then prepared, ensuring a more targeted and effective experimental process. The experimental results indicated that the modified natural ester insulating oil exhibited a 30.5 % reduction in dielectric loss degradation factor, a 23.8 % increase in breakdown voltage, and a 10.9 % enhancement in thermal conductivity compared to the pure natural ester insulating oil. Density functional theory (DFT) simulations revealed the microscopic mechanisms of property enhancement in natural ester oils via silanol groups (-Si-OH) and amino groups (-NH2) functionalization. This work demonstrates the feasibility of using MD simulation to guide the modification of new insulating oil. Compared with traditional preparation methods, this method is expected to be applied to the research on new insulating oil materials in the future.

Keywords: Natural ester insulating oil; Molecular dynamics simulation; Nano-modification; Graphene oxide; APTES (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:250:y:2025:i:c:s0960148125010754

DOI: 10.1016/j.renene.2025.123413

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