1 citations · 1 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2024★ 1 cited
Discovering Melting Temperature Prediction Models of Inorganic Solids by Combining Supervised and Unsupervised Learning
Vahe Gharakhanyan, Luke J. Wirth, Jose A. Garrido Torres +5
The melting temperature is important for materials design because of its relationship with thermal stability, synthesis, and processing conditions. Current empirical and computatio…
cond-mat.mtrl-sci2023
Constructing and Compressing Global Moment Descriptors from Local Atomic Environments
Vahe Gharakhanyan, Max Aalto, Aminah Alsoulah +2
Local atomic environment descriptors (LAEDs) are used in the materials science and chemistry communities, for example, for the development of machine learning interatomic potential…