3 papers
cond-mat.stat-mech2026
Generative Nested Sampling of Atomistic Thermodynamic Landscapes
Alessandro Coretti, Nico Unglert, Sebastian Falkner +2
Nested sampling (NS) resolves the thermodynamics of an atomistic system from a single simulation, but its practical reach is limited by the Markov-chain updates needed to decorrela…
cond-mat.mtrl-sci2025
How Realistic are Idealized Copper Surfaces? A Machine Learning Study of Rough Copper-Water Interfaces
Linus C. Erhard, Johannes Schörghuber, Aleix Comas-Vives +1
Copper is a highly promising catalyst for the electrochemical CO reduction reaction (CO2RR) since it is the only pure metal that can form highly added-value products such as et…
cond-mat.stat-mech2025
Replica exchange nested sampling
Nico Unglert, Livia Bartók Pártay, Georg K. H. Madsen
Nested sampling (NS) has emerged as a powerful tool for exploring thermodynamic properties in materials science. However, its efficiency is often hindered by the limitations of Mar…