Design and validation of refractory alloys using machine learning, CALPHAD, and experiments

Data-driven inverse design of MoNbTiVWZr refractory multicomponent alloys: Microstructure and mechanical properties

L Raman, A Debnath, E Furton, S Lin… - Materials Science and …, 2024 - Elsevier
Multicomponent refractory alloys have the potential to operate in high-temperature
environments. Alloys with heterogeneous/composite microstructure exhibit an optimal …
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Consolidated database of high entropy materials (COD'HEM): An open online database of high entropy materials

M Singh, E Barr, D Aidhy - Computational Materials Science, 2025 - Elsevier
The high entropy approach to materials design has provided access to an exponentially
large compositional phase space. There are a multitude of ongoing research efforts that are …
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nimCSO: A Nim package for Compositional Space Optimization

AM Krajewski, A Debnath, WF Reinhart… - arxiv preprint arxiv …, 2024 - arxiv.org
nimCSO is a high-performance tool implementing several methods for selecting components
(data dimensions) in compositional datasets, which optimize the data availability and density …
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