Hostname: page-component-5d59c44645-l48q4 Total loading time: 0 Render date: 2024-02-25T02:06:52.007Z Has data issue: false hasContentIssue false

Exploring Motifs and Their Hierarchies in Crystals via Unsupervised Learning

Published online by Cambridge University Press:  22 July 2022

Jiadong Dan
Affiliation:
NUS Centre for Bioimaging Sciences, National University of Singapore, Singapore Dept. of Biological Science, National University of Singapore, Singapore
Xiaoxu Zhao
Affiliation:
School of Materials Science and Engineering, Nanyang Technological University, Singapore
Qian He
Affiliation:
Dept. of Materials Science and Engineering, National University of Singapore, Singapore
N. Duane Loh*
Affiliation:
NUS Centre for Bioimaging Sciences, National University of Singapore, Singapore Dept. of Biological Science, National University of Singapore, Singapore Dept. of Physics, National University of Singapore, Singapore
Stephen J. Pennycook*
Affiliation:
Dept. of Materials Science and Engineering, University of Tennessee, Knoxville, TN, USA School of Physical Sciences, University of Chinese Academy of Sciences, Beijing, China
*
*Corresponding author: duaneloh@nus.edu.sg (N.D.L); stephen.pennycook@cantab.net (S.J.P).
*Corresponding author: duaneloh@nus.edu.sg (N.D.L); stephen.pennycook@cantab.net (S.J.P).

Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Artificial Intelligence, Instrument Automation, And High-dimensional Data Analytics for Microscopy and Microanalysis
Copyright
Copyright © Microscopy Society of America 2022

References

Granda, JM et al. , Nature 559 (2018), doi:10.1038/s41586-018-0307-8CrossRefGoogle Scholar
Brockherde, F et al. , Nature Communications 8 (2017), doi:10.1038/s41467-017-00839-3CrossRefGoogle Scholar
Zahrt, AF et al. , Science 363 (2019), doi:10.1126/science.aau5631CrossRefGoogle Scholar
S. J. P. acknowledges funding from Singapore Ministry of Education Tier 1 grant R-284-000-172-114, Tier 2 grant R-284-000-175-112. N.D.L acknowledges funding support from the National Research Foundation (grant number NRF-CRP16-2015-05), and the NUS Early Career award (A-0004744-00-00).Google Scholar