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Meeting Materials Science & Technology 2020
Symposium Materials Informatics and Modeling for 21st Century Ceramics Research
Presentation Title Using Materials Informatics to Quantify Complex Correlations Linking Structure, Properties and Processing
Author(s) Jeffrey M. Rickman
On-Site Speaker (Planned) Jeffrey M. Rickman
Abstract Scope I will present several examples in which materials informatics can be used to elucidate and quantify complex correlations linking structure, properties and processing of materials. In the first example, I consider the case of high-entropy (HE) (or multi-principal element) alloys, typically comprising five or more elements. In the second example, I examine the use of a canonical correlation analysis on the ubiquitous phenomenon of grain abnormality in a microstructure, with the resulting bimodal structure often having a deleterious impact on the thermomechanical properties of a system. Finally, I will outline the use of detrended correlation analyses to interpret time series data associated with processing.
Proceedings Inclusion? Undecided

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

Coarse-grained Equation-free Time Evolution of Microstructures with Deep Learning
Predicting Stress Hotspots in Polycrystalline Materials from Microstructural Features Using Deep Learning
Using Materials Informatics to Quantify Complex Correlations Linking Structure, Properties and Processing

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