Unsupervised Segmentation-Based Machine Learning as an Advanced Analysis Tool for Single Molecule Break Junction Data
Author:
Affiliation:
1. Department of Chemistry and Biochemistry, University of Arizona, 1306 East University Boulevard, Tucson, Arizona 85721, United States
2. Department of Physics, University of Arizona, 1118 East Fourth Street, Tucson, Arizona 85721, United States
Funder
Division of Materials Research
Publisher
American Chemical Society (ACS)
Subject
Surfaces, Coatings and Films,Physical and Theoretical Chemistry,General Energy,Electronic, Optical and Magnetic Materials
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.0c03612
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