Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry-Reference-Cited by-同舟云学术

Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry

Published:2023 Issue:48 Volume:14 Page:14003-14019
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Anker Andy S.¹^ORCID,Butler Keith T.²,Selvan Raghavendra³⁴,Jensen Kirsten M. Ø.¹^ORCID

Affiliation:

1. Department of Chemistry and Nano-Science Center, University of Copenhagen, 2100 Copenhagen Ø, Denmark

2. Department of Chemistry, University College London, Gower Street, London WC1E 6BT, UK

3. Department of Computer Science, University of Copenhagen, 2100 Copenhagen Ø, Denmark

4. Department of Neuroscience, University of Copenhagen, 2200 Copenhagen N, Denmark

Abstract

We discuss how machine learning methods can be applied to advance analysis of spectroscopy and scattering data in materials chemistry. We give examples illustrating the state-of-the-art and identify current challenges in the field.

Funder

H2020 European Research Council

Danmarks Grundforskningsfond

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/SC/D3SC05081E

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