Automatic materials characterization from infrared spectra using convolutional neural networks-Reference-Cited by-同舟云学术

Automatic materials characterization from infrared spectra using convolutional neural networks

Published:2023 Issue:13 Volume:14 Page:3600-3609
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Jung Guwon¹²³^ORCID,Jung Son Gyo¹³⁴^ORCID,Cole Jacqueline M.¹³⁴^ORCID

Affiliation:

1. Department of Physics, Cavendish Laboratory, University of Cambridge, J. J. Thomson Avenue, Cambridge, CB3 0HE, UK

2. Scientific Computing Department, Science and Technology Facilities Council, Didcot, OX11 0FA, UK

3. Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot, Oxfordshire, OX11 OQX, UK

4. ISIS Neutron and Muon Source, STFC Rutherford Appleton Laboratory, Harwell Science and Innovation Campus, Didcot, OX11 0QX, UK

Abstract

Infrared spectroscopy is a technique used to characterize unknown materials by identifying the constituent functional groups of molecules through the analysis of obtained spectra. This analysis has now been automated using artificial intelligence.

Funder

Royal Academy of Engineering

Science and Technology Facilities Council

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/SC/D2SC05892H

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