A Strategic Approach to Machine Learning for Material Science: How to Tackle Real-World Challenges and Avoid Pitfalls-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A Strategic Approach to Machine Learning for Material Science: How to Tackle Real-World Challenges and Avoid Pitfalls

Published:2022-09-01 Issue:17 Volume:34 Page:7650-7665
ISSN:0897-4756
Container-title:Chemistry of Materials
language:en
Short-container-title:Chem. Mater.

Author:

Karande Piyush¹^ORCID,Gallagher Brian²^ORCID,Han Thomas Yong-Jin³^ORCID

Affiliation:

1. Computational Engineering Division, Lawrence Livermore National Laboratory, Livermore, California 94550, United States

2. Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, California 94550, United States

3. Materials Science Division, Lawrence Livermore National Laboratory, Livermore, California 94550, United States

Funder

Lawrence Livermore National Laboratory

Publisher

American Chemical Society (ACS)

Subject

Materials Chemistry,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemmater.2c01333

Reference54 articles.

1. Machine learning for molecular and materials science

2. Opportunities and Challenges for Machine Learning in Materials Science

3. Machine Learning for Materials Scientists: An Introductory Guide toward Best Practices

4. Recent advances and applications of machine learning in solid-state materials science

5. Machine learning in materials science

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Leveraging experimental and computational tools for advancing carbon capture adsorbents research;Environmental Science and Pollution Research;2024-09-03

2. Trust Not Verify? The Critical Need for Data Curation Standards in Materials Informatics;Chemistry of Materials;2024-08-16

3. Synthesis, properties, applications, 3D printing and machine learning of graphene quantum dots in polymer nanocomposites;Progress in Materials Science;2024-08

4. Integrating digital chemistry within the broader chemistry community;Trends in Chemistry;2024-08

5. Shape memory liquid crystalline polymers: Stimuli‐responsiveness, advanced technologies, and key applications;Polymers for Advanced Technologies;2024-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3