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  Generalizing property prediction of ionic liquids from limited labeled data: a one-stop framework empowered by transfer learning

Chen, G., Song, Z., Qi, Z., & Sundmacher, K. (2023). Generalizing property prediction of ionic liquids from limited labeled data: a one-stop framework empowered by transfer learning. Digital Discovery, 2, 591-601. doi:10.1039/D3DD00040K.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-CDEB-4 Version Permalink: https://hdl.handle.net/21.11116/0000-000E-2639-8
Genre: Journal Article

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© 2023 The Author(s). Published by the Royal Society of Chemistry. This is an open access article published under a CC BY-NC License 3.0 deed.
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https://creativecommons.org/licenses/by-nc/3.0/

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 Creators:
Chen, Guzhong1, 2, Author           
Song, Zhen2, Author
Qi, Zhiwen2, Author
Sundmacher, Kai1, 3, Author           
Affiliations:
1Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738151              
2State Key Laboratory of Chemical Engineering, School of Chemical Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, China, ou_persistent22              
3Otto-von-Guericke-Universität Magdeburg, External Organizations, ou_1738156              

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Language(s): eng - English
 Dates: 2023
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1039/D3DD00040K
Other: pubdata_escidoc:3536889
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Title: Digital Discovery
Source Genre: Journal
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Pages: - Volume / Issue: 2 Sequence Number: - Start / End Page: 591 - 601 Identifier: ISSN: 2635-098X