7 citations · 7 across the 4 of their papers we have counts for
4 papers
Clarifying the Ti-V Phase Diagram Using First-Principles Calculations and Bayesian Learning
Timofei Miryashkin, Olga Klimanova, Alexander Shapeev
Conflicting experiments disagree on whether the titanium-vanadium (Ti-V) binary alloy exhibits a body-centred cubic (BCC) miscibility gap or remains completely soluble. A leading h…
Accelerating global search of adsorbate molecule position using machine-learning interatomic potentials with active learning
Olga Klimanova, Nikita Rybin, Alexander Shapeev
We present an algorithm for accelerating the search of molecule's adsorption site based on global optimization of surface adsorbate geometries. Our approach uses a machine-learning…
Bayesian inference of composition-dependent phase diagrams
Timofei Miryashkin, Olga Klimanova, Vladimir Ladygin +1
Phase diagrams serve as a highly informative tool for materials design, encapsulating information about the phases that a material can manifest under specific conditions. In this w…
Accurate melting point prediction through autonomous physics-informed learning
Olga Klimanova, Timofei Miryashkin, Alexander Shapeev
We present an algorithm for computing melting points by autonomously learning from coexistence simulations in the NPT ensemble. Given the interatomic interaction model, the method…