Machine learning based prediction of the electronic structure of quasi-one-dimensional materials under strain-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Machine learning based prediction of the electronic structure of quasi-one-dimensional materials under strain

Published:2022-05-26 Issue:19 Volume:105 Page:
ISSN:2469-9950
Container-title:Physical Review B
language:en
Short-container-title:Phys. Rev. B

Author:

Pathrudkar Shashank^ORCID,Yu Hsuan Ming^ORCID,Ghosh Susanta^ORCID,Banerjee Amartya S.^ORCID

Funder

National Science Foundation

Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles

Extreme Science and Engineering Discovery Environment

Publisher

American Physical Society (APS)

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevB.105.195141/fulltext

Reference129 articles.

1. Opportunities and obstacles for deep learning in biology and medicine

2. Applications of Deep Learning in Biomedicine

3. Explanation and Use of Uncertainty Obtained by Bayesian Neural Network Classifiers for Breast Histopathology Images

4. Advancing Physical Chemistry with Machine Learning

5. Clinical chemistry in higher dimensions: Machine-learning and enhanced prediction from routine clinical chemistry data

Cited by 5 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. Electronic structure prediction of multi-million atom systems through uncertainty quantification enabled transfer learning;npj Computational Materials;2024-08-12

2. Resolving engineering challenges: Deep learning in frequency domain for 3D inverse identification of heterogeneous composite properties;Composites Part B: Engineering;2024-05

3. Carbon Kagome nanotubes—quasi-one-dimensional nanostructures with flat bands;RSC Advances;2024

4. Solution of the Schrödinger equation for quasi-one-dimensional materials using helical waves;Journal of Computational Physics;2024-01

5. Classification of ternary data using the ternary Allen–Cahn system for small datasets;AIP Advances;2022-06-01

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