7 citations · 7 across the 2 of their papers we have counts for
3 papers
Can Universal Machine-Learning Interatomic Potentials Capture Small Polarons? A Geometry-Based Benchmark in Transition-Metal Oxides
Vladislav Korostelev, Pjotrs Žguns, Konstantin Klyukin
Small polarons, formed when excess electrons become localized through lattice distortions, play a critical role in charge transport, catalysis, and degradation processes in transit…
Hydrogen in Brownmillerite Perovskites: First-Principles Insights into Energetics and Induced Electronic-Magnetic Changes
Vladislav Korostelev, Pjotrs Žguns, Konstantin Klyukin
Hydrogen uptake in brownmillerite perovskites A2B2O5 offers an (electro)chemically accessible route to tune functional properties, but mechanistic understanding and design rules fo…
Benchmarking CHGNet Universal Machine Learning Interatomic Potential Against DFT and EXAFS: Case of Layered WS2 and MoS2
Pjotrs Žguns, Inga Pudza, Alexei Kuzmin
Universal machine learning interatomic potentials (uMLIPs) deliver near ab initio accuracy in energy and force calculations at low computational cost, making them invaluable for ma…