34 citations · 130 across the 8 of their papers we have counts for
9 papers · 1 filter
Machine-learning enabled thermodynamic model for the design of new rare-earth compounds
Prashant Singh, Tyler Del Rose, Guillermo Vazquez +2
We employ a descriptor based machine-learning approach to assess the effect of chemical alloying on formation-enthalpy of rare-earth intermetallics. Application of machine-learning…
On the martensitic transformation in FeMnCoCr high-entropy alloy
Prashant Singh, Sezer Picak, Aayush Sharma +4
High-entropy alloys (HEAs), and even medium-entropy alloys (MEAs), are an intriguing class of materials in that structure and property relations can be controlled via alloying and…
Metric-driven search for structurally stable inorganic compounds
R. Villarreal, P. Singh, R. Arroyave
We report a facile `metric' for the identification of structurally and dynamically (positive definite phonon structure) stable inorganic compounds. The metric considers charge-imba…
Accelerated design of Fe-based soft magnetic materials using machine learning and stochastic optimization
Yuhao Wang, Yefan Tian, Tanner Kirk +5
Machine learning was utilized to efficiently boost the development of soft magnetic materials. The design process includes building a database composed of published experimental re…
Uncertainty Propagation in a Multiscale CALPHAD-Reinforced Elastochemical Phase-field Model
Vahid Attari, Pejman Honarmandi, Thien Duong +3
ICME approaches provide decision support for materials design by establishing quantitative process-structure-property relations. Confidence in the decision support, however, must b…
Probing discontinuous precipitation in U-Nb
Thien Duong, Robert E. Hackenberg, Vahid Attari +3
U-Nb's discontinuous precipitation, , is intriguing in the sense that it allows formation and growth of the…