Physics-governed executable modelling of triboelectric nanogenerators
2026-06-22 • Artificial Intelligence
Artificial IntelligenceMathematical Software
AI summaryⓘ
The authors created a new method called TENG-CLAW to better predict how triboelectric nanogenerators (TENGs) work by combining different modeling approaches into one clear system. Their framework uses specific charge types as main variables to link simple theoretical models with complex real-world shapes. This makes simulations more consistent, traceable, and easier to reproduce. Their work helps scientists understand TENG behavior and design devices based on accurate physics-based simulations.
Triboelectric nanogeneratorPredictive modellingElectrostaticsFinite geometryCharge hierarchySimulation frameworkAnalytical theoryNumerical methodsDevice designPhysics-based simulation
Authors
Hongfa Zhao, Baiqiao Wang, Tiancong Zhao, Chun Jin, Hanlin Zhou, Mingrui Shu, Minyi Xu, Liwei Lin, Wenbo Ding, Zhong Lin Wang
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.