Predicting thermal stress in binary composites through advanced generative adversarial networks

IF 1.8 4区材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY MRS Communications Pub Date : 2024-04-24 DOI:10.1557/s43579-024-00555-2

Faling Zhang, Ziping Wang, Qingfeng Wang, Qingcai Ji

引用次数: 0

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

通过高级生成式对抗网络预测二元复合材料的热应力

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

MRS Communications MATERIALS SCIENCE, MULTIDISCIPLINARY-

CiteScore

2.60

自引率

10.50%

发文量

166

审稿时长

>12 weeks

期刊介绍： MRS Communications is a full-color, high-impact journal focused on rapid publication of completed research with broad appeal to the materials community. MRS Communications offers a rapid but rigorous peer-review process and time to publication. Leveraging its access to the far-reaching technical expertise of MRS members and leading materials researchers from around the world, the journal boasts an experienced and highly respected board of principal editors and reviewers.