The advance of multicomponent and high entropy represents a fantastic challenge as their multiple possible functions depend on a myriad of factors related to material microstructure, preparation and chemical composition. Materials science provides only hints to a possible theory for predicting the behavior, mechanical or/and multi-physics, of such complex alloys. Material informatics approaches try to bridge microstructural features of solids with their mechanical or/and multi-physics response, but they are confronted to the high level of complexity of microstructures and microscopic processes involved in materials. However, new machine learning approaches inspired from combinations of statistical physics and data science have emerged. The objective of this Special Issue is to gather interdisciplinary original contributions as well as reviews of recent advances in data science approaches to this rapidly growing field.
Submission deadline
30 November 2022
Guest Editors
Stefanos Papanikolaou, National Centre for Nuclear Research, Poland
Mikko Alava, National Centre for Nuclear Research, Poland
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