Machine Learning Approach to Enable Spectral Imaging Analysis for Particularly Complex Nanomaterial Systems

Jia, Haili; Wang, Canhui; Wang, Chao; Clancy, Paulette

doi:10.1021/acsnano.2c08884

Machine Learning Approach to Enable Spectral Imaging Analysis for Particularly Complex Nanomaterial Systems

Journal Article · 20 December 2022 · ACS Nano

DOI:https://doi.org/10.1021/acsnano.2c08884· OSTI ID:2422330

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Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland21218, United States; OSTI
Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland21218, United States
Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland21218, United States; Ralph O’Connor Sustainable Energy Institute, Johns Hopkins University, Baltimore, Maryland21218, United States

Not provided.

Research Organization:: Johns Hopkins Univ., Baltimore, MD (United States); Brookhaven National Laboratory (BNL), Upton, NY (United States)

Sponsoring Organization:: USDOE Advanced Research Projects Agency - Energy (ARPA-E)

DOE Contract Number:: AR0001191; SC0012704

OSTI ID:: 2422330

Journal Information:: ACS Nano, Journal Name: ACS Nano Journal Issue: 1 Vol. 17; ISSN 1936-0851

Publisher:: American Chemical Society (ACS)

Country of Publication:: United States

Language:: English

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