2 papers
cond-mat.mtrl-sci2026
A Self-Evolving Machine-Learning-Based Kinetic Monte Carlo Method for Modelling Thin-Film Growth
Jyri Kimari, Flyura Djurabekova, Kostas Sarakinos
We present a kinetic Monte Carlo (KMC) simulation framework parameterized by automatically sampling machine-learning (ML) for modeling thin-film growth atom by atom. Given an inter…
cond-mat.mtrl-sci2025
Effect of surface orientation on blistering of copper under high fluence keV hydrogen ion irradiation
A. Lopez-Cazalilla, C. Serafim, J. Kimari +6
Copper and hydrogen are among the most common elements that are widely used in industrial and fundamental research applications. Copper surfaces are often exposed to hydrogen in th…