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cond-mat.mtrl-sci2025
Interpretable machine learning-guided design of Fe-based soft magnetic alloys
Aditi Nachnani, Kai K. Li-Caldwell, Saptarshi Biswas +3
We present a machine-learning guided approach to predict saturation magnetization (MS) and coercivity (HC) in Fe-rich soft magnetic alloys, particularly Fe-Si-B systems. ML models…
cond-mat.mtrl-sci2025
Machine learning driven search of hydrogen storage materials
Tanumoy Banerjee, Kevin Ji, Weiyi Xia +8
The transition to a low-carbon economy demands efficient and sustainable energy-storage solutions, with hydrogen emerging as a promising clean-energy carrier and with metal hydride…
cond-mat.mtrl-sci2024
Linking Order to Strength in Metals
Nicolas Argibay, Duane D. Johnson, Michael Chandross +6
The metallurgy and materials communities have long known and exploited fundamental links between chemical and structural ordering in metallic solids and their mechanical properties…