Modeling Particle-Doped Materials for Performance Improvement of Contact-Separation Triboelectric Nanogenerators

Abstract

Triboelectric nanogenerators (TENGs) are an attractive energy harvesting technology due to their high efficiency and vast applications in self-powered sensors. In this work, dielectric–dielectric contact-separation TENGs were modeled with time-dependent finite element simulations with the objective of improving TENG’s performance by enhancing the relative permittivity (εr).To achieve this, the chosen material (PDMS, εr=2.75) was doped with SrTiO3 (εr = 300) particles. The open-circuit voltage (VOC) and short-circuit current (ISC) remained constant as ϵr increased, as predicted by existent models, but in contradiction with available experimental data. Thus, we introduced a charge correction model relating ϵr and surface charge density, allowing us to observe an increase in TENG performance output (VOC and ISC). This work shows that finite element simulations are suitable for better understanding and optimizing TENGs’ performance.