Physics-governed executable modelling of triboelectric nanogenerators

2026-06-22

AI Summary

This work addresses the long-standing challenge in predictive modeling of triboelectric nanogenerators (TENGs), which has been hindered by the fragmentation among analytical theories, finite-geometry solvers, and simulation workflows, lacking a unified executable framework. The authors propose a self-consistent electrostatic hierarchical modeling approach that treats charge as the state variable, establishing—for the first time—a unified charge definition bridging the analytical limit of infinite parallel plates and numerical simulations of finite geometries. This methodology is implemented in TENG-CLAW, a physics-driven executable platform that automatically compiles user specifications into physically consistent simulation tasks. The platform supports automatic boundary condition configuration and multidimensional workflow integration, ensuring traceable simulation processes and reproducible results, thereby providing a reliable infrastructure for mechanistic analysis and physics-guided design of TENGs.

Abstract

Predictive modelling of triboelectric nanogenerators (TENGs) remains fragmented across analytical theories, finite-geometry solvers and disconnected simulation workflows. These disparate approaches must be unified into an executable framework to advance quantitative TENG research.Here we introduce a charge-defined modelling framework and implement it as TENG-CLAW, a physics-governed platform for traceable TENG simulation. The framework establishes a self-consistent electrostatic hierarchy in which triboelectric charges, pre-charging charges and compensating electrode charges serve as defining state variables.This hierarchy connects the infinite plate analytical limit for near-uniform fields with finite-geometry numerical formulations required for edge-dominated devices. Built on this basis, TENG-CLAW converts user-defined research requests into physically admissible simulation tasks, so that generated outputs are tied to explicit charge states, boundary conditions, solver routes and reusable artifacts across spatial, temporal, field-level, comparative and reporting workflows. This work establishes a rigorous computational basis for interpreting TENG mechanisms and provides reproducible research infrastructure for simulation and physics-guided device design.

Problem

• triboelectric nanogenerators
• predictive modelling
• simulation framework
• electrostatic hierarchy
• computational physics

Innovation

• triboelectric nanogenerator
• charge-defined modelling
• physics-governed simulation
• electrostatic hierarchy
• executable framework