Data Sciences and Informatics for Multiscale Materials Discovery, Development and Deployment

  • Overview
  • Course Content
  • Requirements & Materials
Overview

Data Sciences and Informatics for Multiscale Materials Discovery, Development and Deployment

Course Description

This course will introduce emerging opportunities in the application of data science and informatics concepts to problems in multiscale materials discovery, development, and deployment. The material will include a general introduction for non-experts, as well as tutorials and demonstrations of specialized tools and approaches designed specifically for materials informatics. The foci will be on data accumulation, curation, and management; deriving surrogate models for materials property predictions, design, and discovery across chemical spaces; multiscale modeling under uncertainty; and the extraction of high-fidelity, reduced-order, Process-Structure-Property (PSP) linkages that constitute the essential knowledge needed to support materials innovation efforts.

Course Content

DATA MANAGEMENT, ANALYSIS AND CYBERINFRASTRUCTURE

  • Introduction to data management and cyberinfrastructure
  • Introduction to data analysis

HIGH-THROUGHPUT STRATEGIES, MULTISCALE MODELING & MACHINE LEARNING

  • High-throughput simulations for materials data generation, analysis and discovery
  • High throughput, data rich characterization
  • Uncertainty in multiscale model chains for materials design and development
  • Machine learning for materials discovery

QUANTIFICATION OF THE HIERARCHICAL MATERIAL INTERNAL STRUCTURE

  • Quantification of the hierarchical material internal structure
  • Segmentation of microstructures for digital workflows

REDUCED-ORDER PROCESS-STRUCTURE-PROPERTY (PSP) LINKAGES

  • High-throughput experimental assays for process-structure-property (PSP) linkages in
  • structural materials
  • Framework for Reduced-Order Process-Structure-Property (PSP) Linkages and PyMKS
  • Case Studies in PSP Linkages using machine learning and linear regression
Requirements & Materials

Prerequisites

Recommended

Required

  • Undergraduate background in materials science/engineering or related fields

Who Should Attend

This course is designed for current practitioners in national laboratories, industry, and academia engaged in various aspects of the discovery, development, and deployment of new/improved materials in emerging technologies. This is particularly useful for those interested in learning how to combine and leverage experiments, models, and data in accelerated materials innovation.

What You Will Learn

  • Introduction to materials data management and analytics
  • Introduction to various machine learning approaches
  • Approaches for high-throughput rapid screening of new materials
  • A new framework for process-structure-property linkages
  • Case studies in accelerated materials discovery, development, and deployment
A pipe being manufactured in a plant

How You Will Benefit

  • Understand the emerging concepts in the field of materials data sciences and informatics.
  • Learn how data science can accelerate materials innovation.
  • Learn about open source materials data and code repositories.
  • Learn how to effectively combine experiments, models, and data.
  • Learn how to apply machine learning to materials innovation.
  • Taught by Experts in the Field icon
    Taught by Experts in the Field
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    Grow Your Professional Network

The course schedule was well-structured with a mix of lectures, class discussions, and hands-on exercises led by knowledgeable and engaging instructors.

- Abe Kani
President

TRAIN AT YOUR LOCATION

We enable employers to provide specialized, on-location training on their own timetables. Our world-renowned experts can create unique content that meets your employees' specific needs. We also have the ability to deliver courses via web conferencing or on-demand online videos. For 15 or more students, it is more cost-effective for us to come to you.

  • Save Money
  • Flexible Schedule
  • Group Training
  • Customize Content
  • On-Site Training
  • Earn a Certificate
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