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About this Abstract
Meeting	MS&T24: Materials Science & Technology
Symposium	Frontiers of Machine Learning on Materials Discovery
Presentation Title	The Space of Phase Diagrams: Visualization Strategies for Advanced Materials
Author(s)	Jarrod Lund, Xavier Tricoche, R. Edwin García
On-Site Speaker (Planned)	Jarrod Lund
Abstract Scope	Despite over fifty years of great success in the CALculation of PHAse Diagrams (CALPHAD), our understanding on the reaches and limitations of what a thermodynamic model can and cannot do (independent of chemistry), is fragmentary at best. Furthermore, there is a lack of data analytics and visualization tools to describe phase diagrams (PDs) and their associated spaces, even though they are a necessary preamble to develop machine learning tools for accelerated material discovery and advanced device design. We propose a data-driven approach to rationalize the ability of existing and emerging models in describing materials with intuitive graphical descriptions to summarize the space of phase diagrams, as a steppingstone to understand material behavior. Spaces of PDs, described in terms of six and nine thermodynamic parameters are visualized into 2D maps, enabling the formulation of efficient optimization strategies, providing insights into the practical aspects and complexity of the space of phase diagrams.

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