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Royal Society of Chemistry, Nanoscale, 44(14), p. 16479-16489, 2022

DOI: 10.1039/d2nr03712b

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Seeking regularity from irregularity: unveiling the synthesis–nanomorphology relationships of heterogeneous nanomaterials using unsupervised machine learning

Journal article published in 2022 by Lehan Yao ORCID, Hyosung An ORCID, Shan Zhou ORCID, Ahyoung Kim ORCID, Erik Luijten ORCID, Qian Chen ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Shape fingerprint functions and unsupervised machine learning are used to classify and analyze nanomaterial morphologies from 2D and 3D TEM data.