3 papers
cond-mat.soft2025
Banding and polarization in driven multistable materials
Sheng Huang, Daniel Hexner
We study a disordered network of bistable bonds subjected to periodic strain. The model is inspired by experiments on crumpled sheets and it features behaviors associated with glas…
cond-mat.stat-mech2025
Bridging statistical mechanics and thermodynamics away from equilibrium: a data-driven approach for learning internal variables and their dynamics
Weilun Qiu, Shenglin Huang, Celia Reina
Thermodynamics with internal variables is a common approach in continuum mechanics to model inelastic (i.e., non-equilibrium) material behavior. While this approach is computationa…
cond-mat.stat-mech2023
Statistical-Physics-Informed Neural Networks (Stat-PINNs): A Machine Learning Strategy for Coarse-graining Dissipative Dynamics
Shenglin Huang, Zequn He, Nicolas Dirr +2
Machine learning, with its remarkable ability for retrieving information and identifying patterns from data, has emerged as a powerful tool for discovering governing equations. It…