3 papers
cond-mat.mtrl-sci2026
Multi-fidelity Machine Learning Interatomic Potentials for Charged Point Defects
Xinwei Wang, Irea Mosquera-Lois, Aron Walsh
Machine learning interatomic potentials (MLIPs) can now reproduce the energy, forces and stresses of bulk materials with high accuracy compared to first-principles calculations. Th…
cond-mat.mtrl-sci2025
Dynamic Vacancy Levels in CsPbCl3 Obey Equilibrium Defect Thermodynamics
Irea Mosquera-Lois, Aron Walsh
Halide vacancies are the dominant point defects in perovskites with VCl identified as a detrimental trap for the optoelectronic performance of CsPbCl3, with applications ranging fr…
cond-mat.mtrl-sci2024
Point defect formation at finite temperatures with machine learning force fields
Irea Mosquera-Lois, Johan Klarbring, Aron Walsh
Point defects dictate the properties of many functional materials. The standard approach to modelling the thermodynamics of defects relies on a static description, where the change…