3 papers
cond-mat.mtrl-sci2026
Differentiable inverse design of short-range order in high-entropy alloys: from target sro to target property
Tiancheng Ding, Conrard Giresse Tetsassi Feugmo
Short-range order (SRO) governs the mechanical response of multi-principal-element alloys, but designing an alloy for a target property usually means solving two disconnected probl…
cond-mat.mtrl-sci2026
A physics-informed neural network approach to the point defect model for electrochemical oxide film growth
Mohid Farooqi, Ingmar Bösing, Ingmar Bösing +1
Physics-informed neural networks (PINNs) offer a novel AI-driven framework for integrating physical laws directly into neural network models, facilitating the solution of complex m…
physics.app-ph2026
A Systematic Benchmark of Physics-Informed Neural Network Architectures for the Stiff Poisson-Nernst-Planck System: Adaptive LossWeighting and Multi-Scale Resolution
David Pankaczy, Conrard Giresse Tetsassi Feugmo
The Poisson Nernst Planck PNP system constitutes a canonical stiff coupled PDE problem where the charge density prefactor produces extreme coefficient ratios and the electric doubl…