Course Summary
This course explores the field of materials informatics, which focuses on the development and application of computational tools to materials science.Key Learning Points
- Learn the fundamentals of materials informatics
- Discover how to apply computational tools to materials science
- Explore data-driven approaches to materials discovery and design
Related Topics for further study
Learning Outcomes
- Understand the fundamentals of materials informatics
- Develop skills to apply computational tools to materials science
- Learn data-driven approaches to materials discovery and design
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of materials science
- Familiarity with programming concepts
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Introduction to Materials Science and Engineering
- Materials Science: 10 Things Every Engineer Should Know
- Materials Data Sciences and Informatics
Related Education Paths
Related Books
Description
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.
Outline
- Welcome
- Course Syllabus
- Frequently Asked Questions
- Suggested Reading
- Target Audience and Recommended Background
- Get More from Georgia Tech
- Consent Form
- Accelerating Materials Development and Deployment
- Why Accelerate Material Discovery and Development?
- Historical Materials Development Cycles
- How do we accelerate materials development and deployment
- Emergence of multi-stakeholder initiatives
- The Materials Innovation Ecosystem
- Part 1:Multiscale Modeling and Multilevel Design of Materials
- Part 2: Multiscale Modeling and Multilevel design of Materials
- Decision-Making in Material Design
- Multilevel Systems-Based Materials Design
- Earn a Georgia Tech Badge/Certificate/CEUs
- Accelerating Materials Development and Deployment
- Materials Knowledge and Materials Data Science
- Material Property, Material Structure, and Manufacturing Processes
- Process-Structure-Property (PSP) Linkages
- Role of Structures in PSP Linkages
- Data Science Terminology
- Main Components of Data Science
- What is Big Data?
- Materials Knowledge and Materials Data Science
- Materials Knowledge Improvement Cycles
- Digital Representation of Material Structure
- Spatial Correlations: n-Point Statistics
- Computation and Visualization of 2-Point Spatial Correlations
- Principal Component Analyses (PCA) for low dimensional representations
- Principal Component Analyses (PCA) for low dimensional representation of material structure
- Homogenization: Passing Information to Higher Length Scales
- Materials Knowledge Improvement Cycles
- Case Study in Homogenization: Plastic Properties of Two-Phase Composites
- Structure-Property Linkages using a Data Science Approach-Part 1
- Structure-Property Linkages using a Data Science Approach-Part 2
- Case Study in Homogenization: Plastic Properties of Two-Phase Composites
- Materials Innovation Cyberinfrastructure and Integrated Workflows
- Materials Innovation Ecosystem
- Materials Innovation Cyberinfrastucture
- e-Collaboration Platforms/Environments
- Materials Cyber-Infrastructure
- Introduction to PyMKS Materials Knowledge Systems in Python
- Materials Data Science with PyMKS
- PyMKS website
- Take another course like this !
- Materials Innovation Cyberinfrastructure and Integrated Workflows
Summary of User Reviews
Discover the fascinating world of Material Informatics with this comprehensive online course on Coursera. Learners have praised this course for its comprehensive coverage of the subject matter and its engaging teaching style.Key Aspect Users Liked About This Course
One key aspect that many users have found particularly good is the instructor's ability to break down complex concepts into easy-to-understand segments.Pros from User Reviews
- Comprehensive coverage of Material Informatics
- Engaging and interactive teaching style
- Instructor effectively breaks down complex concepts
- Plenty of practical exercises and assignments
- Suitable for learners of all levels
Cons from User Reviews
- Some learners have reported technical issues with the platform
- Course content can be challenging for beginners
- Some topics may require additional research outside of the course material
- No official certification upon completion
- Course material may not be updated regularly
Dr. Surya Kalidindi
4.5 Raiting
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