Materials Data Sciences and Informatics
4.2
56 ratings
Materials Data Sciences and Informatics
Georgia Institute of Technology
Informações sobre o curso
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.
Syllabus - What you will learn from this course
1
Section
Welcome
What you should know before you start the course
6 readings
6 readings
Course Syllabus10m
Frequently Asked Questions10m
Suggested Reading10m
Target Audience and Recommended Background10m
Get More from Georgia Tech10m
Consent Form10m
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.
• Learn about the emergence of key national and international 21st century initiatives in accelerated materials discovery and development and how they are expected to bring about a disruptive transformation of new product capabilities and time to market.
9 videos (Total 78 min), 1 reading, 1 quiz
9 videos
Historical Materials Development Cycles8m
How do we accelerate materials development and deployment12m
Emergence of multi-stakeholder initiatives8m
The Materials Innovation Ecosystem9m
Part 1:Multiscale Modeling and Multilevel Design of Materials8m
Part 2: Multiscale Modeling and Multilevel design of Materials5m
Decision-Making in Material Design9m
Multilevel Systems-Based Materials Design5m
1 readings
Earn a Georgia Tech Badge/Certificate/CEUs10m
1 practice exercises
Accelerating Materials Development and Deployment34m
2
Section
Materials Knowledge and Materials Data Science
• Understand property, structure and process spaces
• Learn about Process-Structure-Property Linkages
• Learn what does Materials Knowledge mean
• Learn about a role of Data Science in Materials Knowledge System
• Overview approaches and main components of Data Science
• Learn about a new discipline - Materials Data Sciences
6 videos (Total 53 min), 1 quiz
6 videos
Process-Structure-Property (PSP) Linkages7m
Role of Structures in PSP Linkages10m
Data Science Terminology6m
Main Components of Data Science5m
What is Big Data?6m
1 practice exercises
Materials Knowledge and Materials Data Science20m
3
Section
Materials Knowledge Improvement Cycles
• Learn material structure and its digital representation
• Learn how to calculate 2-point statistics
• Learn how Principal Component Analysis can be used to reduce dimensionality
• Understand Homogenization and Localization concepts
6 videos (Total 79 min), 1 quiz
6 videos
Spatial Correlations: n-Point Statistics11m
Computation and Visualization of 2-Point Spatial Correlations10m
Principal Component Analyses (PCA) for low dimensional representations12m
Principal Component Analyses (PCA) for low dimensional representation of material structure12m
Homogenization: Passing Information to Higher Length Scales16m
1 practice exercises
Materials Knowledge Improvement Cycles16m
4
Section
Case Study in Homogenization: Plastic Properties of Two-Phase Composites
This module demonstrates a homogenization problem based on an example of two-phase composites
2 videos (Total 18 min), 1 quiz
2 videos
Structure-Property Linkages using a Data Science Approach-Part 25m
1 practice exercises
Case Study in Homogenization: Plastic Properties of Two-Phase Composites4m
5
Section
Materials Innovation Cyberinfrastructure and Integrated Workflows
• Learn about materials innovation system and cyberinfrastructure
• Review Materials Databases, e-collaboration platforms and code repositories
• Learn why integrated workflows are needed
• Define Metadata, Structured and Unstructured data
• Learn about available services for e-collaborations
6 videos (Total 42 min), 2 readings, 1 quiz
6 videos
Materials Innovation Cyberinfrastucture3m
e-Collaboration Platforms/Environments6m
Materials Cyber-Infrastructure4m
Introduction to PyMKS Materials Knowledge Systems in Python7m
Materials Data Science with PyMKS14m
2 readings
PyMKS website10m
Take another course like this !10m
1 practice exercises
Materials Innovation Cyberinfrastructure and Integrated Workflows16m
4.2
Top Reviews
By BW•May 4th 2018
Great introduction of the why and how of materials informatics!
Instructor
Dr. Surya Kalidindi
ProfessorAbout 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.
Georgia Tech's campus occupies 400 acres in the heart of the city of Atlanta, where more than 20,000 undergraduate and graduate students receive a focused, technologically based education.
Frequently Asked Questions
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What will I get if I pay for this course?
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