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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/material-informatics
课程评论：没有评论
课程名称：材料数据科学与信息学 课程概述：本课程旨在提供对材料信息学这一新兴学科的简要概述，该学科位于材料科学、计算科学和信息科学的交叉点。课程特别强调这一新领域在加速材料开发和应用方面提供的独特机遇。重点讨论具有多层次内部结构的材料以及建立可逆的工艺-结构-属性（PSP）联系所面临的挑战。课程中指出，现代数据科学（包括高级统计学、降维和元模型的构建）以及创新的网络基础设施工具（如集成平台、数据库和增强跨学科团队成员协作的定制工具）可能在解决上述挑战中发挥至关重要的作用。 课程大纲： 1. 欢迎：课程开始前需要了解的内容。 2. 加速材料开发与部署： - 学习历史上先进材料开发的范式，强调利用数据科学和信息学连接计算模拟与实验的重要性，以加快材料发现和开发的进程。 - 了解21世纪关键国家和国际加速材料发现与开发的倡议，以及它们如何预期带来新产品能力和上市时间的颠覆性转变。 3. 材料知识与材料数据科学： - 理解性质、结构与工艺空间。 - 学习工艺-结构-属性的联系。 - 了解材料知识的含义。 - 探讨数据科学在材料知识系统中的作用。 - 综述数据科学的主要方法和组成部分。 - 学习新学科——材料数据科学。 4. 材料知识改进周期： - 学习材料结构及其数字表示。 - 学习如何计算二点统计。 - 应用主成分分析进行降维。 - 理解均匀化和局部化概念。 5. 均匀化案例研究：成分的塑性特性： - 本模块基于二维相复合材料的案例展示均匀化问题。 6. 材料创新网络基础设施与集成工作流程： - 学习材料创新系统和网络基础设施。 - 回顾材料数据库、电子协作平台和代码库。 - 理解为何需要集成工作流程。 - 定义元数据、结构化数据与非结构化数据。 - 了解可用的电子协作服务。
Name:Welcome
Description:What you should know before you start the course
Name:Accelerating Materials Development and Deployment
Description:• 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.
Name:Materials Knowledge and Materials Data Science
Description:• 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
Name:Materials Knowledge Improvement Cycles
Description:• 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
Name:Case Study in Homogenization: Plastic Properties of Two-Phase Composites
Description:This module demonstrates a homogenization problem based on an example of two-phase composites
Name:Materials Innovation Cyberinfrastructure and Integrated Workflows
Description:• 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
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.
