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.
Desenvolvido por: Georgia Institute of Technology
Ministrado por: Dr. Surya Kalidindi, Professor
The George W. Woodruff School of Mechanical Engineering
| Nível | Intermediário |
| Compromisso | 5 semanas de estudo,2-3 horas/semana |
| Idioma | English |
| Como ser aprovado | Seja aprovado em todas as tarefas para concluir o curso. |
| Classificação do usuário |
Programa
SEMANA 1
Welcome
What you should know before you start the course
6 leituras
- 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
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, 1 leituras
- Vídeo: Historical Materials Development Cycles
- Vídeo: How do we accelerate materials development and deployment
- Vídeo: Emergence of multi-stakeholder initiatives
- Vídeo: The Materials Innovation Ecosystem
- Vídeo: Part 1:Multiscale Modeling and Multilevel Design of Materials
- Vídeo: Part 2: Multiscale Modeling and Multilevel design of Materials
- Vídeo: Decision-Making in Material Design
- Vídeo: Multilevel Systems-Based Materials Design
- Discussion Prompt: Assignment #1
- Discussion Prompt: Assignment #2
- Reading: Earn a Georgia Tech Badge/Certificate/CEUs
Nota atribuída: Accelerating Materials Development and Deployment
SEMANA 2
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
- Vídeo: Process-Structure-Property (PSP) Linkages
- Vídeo: Role of Structures in PSP Linkages
- Vídeo: Data Science Terminology
- Vídeo: Main Components of Data Science
- Vídeo: What is Big Data?
Nota atribuída: Materials Knowledge and Materials Data Science
SEMANA 3
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
- Vídeo: Spatial Correlations: n-Point Statistics
- Vídeo: Computation and Visualization of 2-Point Spatial Correlations
- Vídeo: Principal Component Analyses (PCA) for low dimensional representations
- Vídeo: Principal Component Analyses (PCA) for low dimensional representation of material structure
- Vídeo: Homogenization: Passing Information to Higher Length Scales
Nota atribuída: Materials Knowledge Improvement Cycles
SEMANA 4
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
- Vídeo: Structure-Property Linkages using a Data Science Approach-Part 2
Nota atribuída: Case Study in Homogenization: Plastic Properties of Two-Phase Composites
SEMANA 5
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, 2 leituras
- Vídeo: Materials Innovation Cyberinfrastucture
- Vídeo: e-Collaboration Platforms/Environments
- Vídeo: Materials Cyber-Infrastructure
- Vídeo: Introduction to PyMKS Materials Knowledge Systems in Python
- Vídeo: 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 !
Nota atribuída: Materials Innovation Cyberinfrastructure and Integrated Workflows
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Desenvolvedores
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.
Classificações e avaliações
Great introduction of the why and how of materials informatics!
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)
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mg
its easy to do it