34 citations · 130 across the 8 of their papers we have counts for
16 papers
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…
Deep Multimodal Transfer-Learned Regression in Data-Poor Domains
Levi McClenny, Mulugeta Haile, Vahid Attari +3
In many real-world applications of deep learning, estimation of a target may rely on various types of input data modes, such as audio-video, image-text, etc. This task can be furth…
Impact of Particle Arrays on Phase Separation Composition Patterns
Supriyo Ghosh, Arnab Mukherjee, Raymundo Arroyave +1
We examine the symmetry-breaking effect of fixed constellations of particles on the surface-directed spinodal decomposition of binary blends in the presence of particles whose surf…
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…