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Meeting Materials Science & Technology 2021
Symposium Accelerating Materials Science with Big Data and Machine Learning
Organizer(s) Huan Tran, Georgia Institute of Technology
Muratahan Aykol, Toyota Research Institute
Scope Materials informatics is gaining significant momentum as a new subfield of materials science and engineering, especially from the launch of Materials Genome Initiative almost a decade ago. From alloys to polymers to ceramics, a central tenet of this new approach is that possible relationships among structure, property and/or processing may be learned from data, which enable large-scale screening of untested candidates or rapid optimization of materials for a target technology. Remarkably, this strategy has led to the development of many novel materials recently synthesized and tested. Within this context, essential topics concerning materials informatics and data-driven research, including experimental and computational generation of materials data, data management and dissemination, material representations, machine learning algorithms and other predictive models for materials, closed-loop and inverse design approaches, as well as infrastructure and software tool development are all covered in this symposium. We expect this symposium to provide a forum where researchers from academia, industry, and national laboratories share recent developments in diverse application areas of materials informatics, and identify the critical areas where future research efforts should be directed to.
Abstracts Due 03/15/2021
Proceedings Plan Undecided
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