This course aims to provide a succinct overview of the emerging discipline of Materials Informatics at the intersection of materials science, computational science, and information science. Attention is drawn to specific opportunities afforded by this new field in accelerating materials development and deployment efforts. A particular emphasis is placed on materials exhibiting hierarchical internal structures spanning multiple length/structure scales and the impediments involved in establishing invertible process-structure-property (PSP) linkages for these materials. More specifically, it is argued that modern data sciences (including advanced statistics, dimensionality reduction, and formulation of metamodels) and innovative cyberinfrastructure tools (including integration platforms, databases, and customized tools for enhancement of collaborations among cross-disciplinary team members) are likely to play a critical and pivotal role in addressing the above challenges.
Offert par
Materials Data Sciences and Informatics
Georgia Institute of TechnologyÀ propos de ce cours
Compétences que vous acquerrez
- Informatics
- Materials
- Statistics
- Data Science
Offert par
Georgia Institute of Technology
The Georgia Institute of Technology is one of the nation's top research universities, distinguished by its commitment to improving the human condition through advanced science and technology.
Programme de cours : ce que vous apprendrez dans ce cours
Welcome
What you should know before you start the course
Accelerating Materials Development and Deployment
• Learn and appreciate historical paradigms of advanced materials development while emphasizing the critical need for new approaches that employ data sciences and informatics as the glue to connect computational simulation and experiments to speed up the processes of materials discovery and development.
Materials Knowledge and Materials Data Science
• Understand property, structure and process spaces
Materials Knowledge Improvement Cycles
• Learn material structure and its digital representation
Case Study in Homogenization: Plastic Properties of Two-Phase Composites
This module demonstrates a homogenization problem based on an example of two-phase composites
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Meilleurs avis pour MATERIALS DATA SCIENCES AND INFORMATICS
It's a great course that can give you a wide view of how to accelerate the development of material using computational resources. I'm a Metallurgical Engineer and I totally recommend this course.
Machine learning part and its application to material science was interesting but informative contents like material dev eco system and whole week 1 was more informative than logical
This course is very much interesting and i have learned about micro structure analysis using data sciences simulation, regression ,finding mechanical properties etc
It is a great way to combine both the branches, Material sciences, and data science. I completely loved this certification. Looking forward to learning more.
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