Review of machine learning for hydrodynamics, transport, and reactions in multiphase flows and reactors

Zhu, L.-T., Chen, X.-Z. orcid.org/0000-0001-8073-5741, Ouyang, B. et al. (4 more authors) (2022) Review of machine learning for hydrodynamics, transport, and reactions in multiphase flows and reactors. Industrial & Engineering Chemistry Research, 61 (28). pp. 9901-9949. ISSN 0888-5885

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Item Type: Article
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© 2022 American Chemical Society. This is an author-produced version of a paper subsequently published in Industrial & Engineering Chemistry Research . Uploaded in accordance with the publisher's self-archiving policy.

Dates:
  • Published: 20 July 2022
  • Published (online): 7 July 2022
  • Accepted: 16 June 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Chemical and Biological Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 15 Jul 2022 10:29
Last Modified: 07 Jul 2023 00:13
Status: Published
Publisher: American Chemical Society (ACS)
Refereed: Yes
Identification Number: 10.1021/acs.iecr.2c01036
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