MAPAL: A python library for mapping features and properties of alloys over compositional spaces

Compositional machine learning (ML) models have emerged as a promising high throughput approach to probe the properties and behavior of a wide variety of materials including multi-principal element alloys (MPEAs). These models use physical and thermodynamic features that are derived from some combin...

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Vydané v:	Computational materials science Ročník 262; s. 114360
Hlavní autori:	Beniwal, Dishant, Ray, Pratik K.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 30.01.2026
Predmet:	Alloy design Machine learning MAPAL python library MAPAL python library Alloy design Machine learning
ISSN:	0927-0256
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