Chirality Detection in Scanning Tunneling Microscopy Data Using Artificial Intelligence.

导出 LinkOut

翻译打印收藏纠错

第一作者： Tim J,Seifert

第一单位： Institute of Applied Physics, TU Braunschweig, 38106, Braunschweig, Germany.

作者： Tim J,Seifert ^[1] ; Mandy,Stritzke ^[2] ; Peer,Kasten ^[1] ; Björn,Möller ^[3] ; Tim,Fingscheidt ^[3] ; Markus,Etzkorn ^[4] ; Timo,de Wolff ^[2] ; Uta,Schlickum ^[4]

作者单位： Institute of Applied Physics, TU Braunschweig, 38106, Braunschweig, Germany. ^[1] Institute of Analysis and Algebra, TU Braunschweig, 38106, Braunschweig, Germany. ^[2] Institute for Communications Technology, TU Braunschweig, 38106, Braunschweig, Germany. ^[3] Institute of Applied Physics, TU Braunschweig, 38106, Braunschweig, Germany.;Laboratory for Emerging Nanometrology, TU Braunschweig, 38106, Braunschweig, Germany. ^[4]

关键词 chiral networks machine learning molecular self‐assembly object detection scanning probe microscopy synthetic training data

DOI 10.1002/smtd.202400549

PMID 39248666

发布时间 2025-01-04

翻译满意度评价：

准确一般字义偏差语意偏离译文作用小提交

浏览0

Small methods

2024年8卷12期

e2400549页

相似文献

中文期刊
外文期刊
学位论文
会议论文

检索历史清除

Chirality Detection in Scanning Tunneling Microscopy Data Using Artificial Intelligence.

Small methods

相似文献

Small methods

相关期刊

参考文献：
指定格式：	NoteExpress EndNote RefWorks NoteFirst

检索历史 清除

Chirality Detection in Scanning Tunneling Microscopy Data Using Artificial Intelligence.

Small methods

相似文献

Small methods

相关期刊

检索历史清除