关于此课程： 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.
教学方： Dr. Surya Kalidindi, Professor
The George W. Woodruff School of Mechanical Engineering
| 级别 | Intermediate |
| 承诺学习时间 | 5 weeks of study, 2-3 hours/week |
| 语言 | English |
| 如何通过 | 通过所有计分作业以完成课程。 |
| 用户评分 |
- Reading: Course Syllabus
- Reading: Frequently Asked Questions
- Reading: Suggested Reading
- Reading: Target Audience and Recommended Background
- Reading: Get More from Georgia Tech
- Reading: Consent Form
- 视频: Historical Materials Development Cycles
- 视频: How do we accelerate materials development and deployment
- 视频: Emergence of multi-stakeholder initiatives
- 视频: The Materials Innovation Ecosystem
- 视频: Part 1:Multiscale Modeling and Multilevel Design of Materials
- 视频: Part 2: Multiscale Modeling and Multilevel design of Materials
- 视频: Decision-Making in Material Design
- 视频: Multilevel Systems-Based Materials Design
- Discussion Prompt: Assignment #1
- Discussion Prompt: Assignment #2
- Reading: Earn a Georgia Tech Badge/Certificate/CEUs
- 视频: Process-Structure-Property (PSP) Linkages
- 视频: Role of Structures in PSP Linkages
- 视频: Data Science Terminology
- 视频: Main Components of Data Science
- 视频: What is Big Data?
- 视频: Spatial Correlations: n-Point Statistics
- 视频: Computation and Visualization of 2-Point Spatial Correlations
- 视频: Principal Component Analyses (PCA) for low dimensional representations
- 视频: Principal Component Analyses (PCA) for low dimensional representation of material structure
- 视频: Homogenization: Passing Information to Higher Length Scales
- 视频: Structure-Property Linkages using a Data Science Approach-Part 2
- 视频: Materials Innovation Cyberinfrastucture
- 视频: e-Collaboration Platforms/Environments
- 视频: Materials Cyber-Infrastructure
- 视频: Introduction to PyMKS Materials Knowledge Systems in Python
- 视频: Materials Data Science with PyMKS
- Reading: PyMKS website
- Discussion Prompt: PyMKS output
- Discussion Prompt: Auto and Crosscorrelation for a microstructure
- Reading: Take another course like this !
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A great introductory course into Material Data Sciences and Informatics. Had a relatively hard time when the course turned form introduction into hardcore statistics. Moreover, it can be more helpful if there are more practical projects and tutorial on introduced tools.
Very valuable course for materials modelling enthusiast. It provides me the firm grounding and preparation for my future research work in this material modeling. This course is a fine balance of technical knowledge, its implementation and the practical approaches one needs to adopt to effectively use this knowledge of materials modeling in real world. (Anupam Purwar)
Excellent course if you are looking to understand how to design high performance materials leveraging current advances in data sciences.
Very well delivered by Dr. Surya Kalidindi and Prof McDowell. Reference to the book on the subject by Dr. Kalidindi supplemented by web search was useful.
Need to put the new skills acquired, in practice at work, where I see a huge potential.
Thanks Georgia Tech!!
BW
Great introduction of the why and how of materials informatics!