A multiphysics model for triboelectric nanogenerator design with explicit surface roughness representation

TL;DR

This paper introduces a multiphysics finite element model for triboelectric nanogenerators that explicitly incorporates surface roughness, improving prediction accuracy of electrical outputs and aiding device optimization.

Contribution

It presents a coupled mechanical-electrostatic simulation framework with explicit surface roughness representation, advancing beyond idealized models for TENG design.

Findings

Accurately predicts real contact area ratio compared to optical microscopy.

Improves agreement with experimental open-circuit voltage and capacitance measurements.

Provides a scalable tool for optimizing TENG performance under various conditions.

Abstract

The design of triboelectric nanogenerators (TENGs) for efficient energy harvesting requires predictive models that capture the interplay between surface roughness, real contact area, and electrostatic behaviour across diverse tribolayer materials and roughness levels. To address this demand, this paper presents a multiphysics finite element framework that couples mechanical contact analysis with electrostatic simulations, considering exact surface roughness representations rather than idealised statistical approximations. Compared with optical interference microscopy measurements, the framework predicts the real contact area ratio more accurately than analytical models. The proposed approach captures the electrostatic behaviour by scaling the TENG surface charge density with the real contact area ratio between the rough tribolayers, computed for a given mechanical load. This method improves agreement with experiments for open-circuit voltage and capacitance relative to approximate analytical models. To represent the TENG circuit, a time-dependent ordinary differential equation is integrated, enabling evaluation of electrical responses under varying load conditions and elucidating the roles of surface roughness, mechanical load, contact-separation frequency, and resistive load. The framework provides a robust, scalable tool for performance optimisation across dielectric materials, mechanical behaviours, and operating conditions and is readily extendable to other surface-dependent energy-harvesting devices.