Machine learning search for stable binary Sn alloys with Na, Ca, Cu, Pd, and Ag
A. Thorn, Daviti Gochitashvili, Saba Kharabadze, Aleksey N. Kolmogorov
Abstract
(re)examination of previously observed M-Sn compounds that helped explain the entropy-driven stabilization of known Cu-Sn phases. The study demonstrates the benefits of guiding structure searches with machine learning potentials and significantly expands the number of predicted thermodynamically stable crystalline intermetallics achieved with this strategy so far.
Topics & Concepts
Binary numberMaterials scienceCrystallographyChemistryMathematicsArithmeticMachine Learning in Materials ScienceNuclear Materials and PropertiesThermodynamic and Structural Properties of Metals and Alloys