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...

Full description

Bibliographic Details

Published in:	Computational materials science Vol. 262; p. 114360
Main Authors:	Beniwal, Dishant, Ray, Pratik K.
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 30.01.2026
Subjects:	Alloy design Machine learning MAPAL python library MAPAL python library Alloy design Machine learning
ISSN:	0927-0256
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!