Metallic Metal–Organic Frameworks Predicted by the Combination of Machine Learning Methods and Ab Initio Calculations-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Metallic Metal–Organic Frameworks Predicted by the Combination of Machine Learning Methods and Ab Initio Calculations

Published:2018-07-27 Issue:16 Volume:9 Page:4562-4569
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

He Yuping¹^ORCID,Cubuk Ekin D.²,Allendorf Mark D.¹^ORCID,Reed Evan J.³

Affiliation:

1. Sandia National Laboratories, Livermore, California 94551, United States

2. Google Brain, Mountain View, California 94043, United States

3. Department of Materials Science and Engineering, Stanford University, Stanford, California 94305, United States

Publisher

American Chemical Society (ACS)

Subject

General Materials Science,Physical and Theoretical Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.8b01707

Reference56 articles.

1. Hybrid porous solids: past, present, future

2. Commensurate Adsorption of Hydrocarbons and Alcohols in Microporous Metal Organic Frameworks

3. Carbon Dioxide Capture in Metal–Organic Frameworks

4. An updated roadmap for the integration of metal–organic frameworks with electronic devices and chemical sensors

5. Electrically Conductive Porous Metal-Organic Frameworks

Cited by 87 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. From Data to Discovery: Recent Trends of Machine Learning in Metal–Organic Frameworks;JACS Au;2024-09-12

2. Combining machine learning and metal–organic frameworks research: Novel modeling, performance prediction, and materials discovery;Coordination Chemistry Reviews;2024-09

3. Current update and prospects in the development of conductive metal-organic framework electrodes for lithium-based batteries;Materials Today Sustainability;2024-09

4. Learnable features for predicting properties of metal-organic frameworks with deep neural networks;Cell Reports Physical Science;2024-08

5. Artificial Intelligence in Biomaterials: A Comprehensive Review;Applied Sciences;2024-07-28

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