A scalable and integrated machine learning framework for molecular properties 
prediction

Chen, Guzhong; Song, Zhen; Qi, Zhiwen; Sundmacher, Kai

doi:10.1002/aic.18185

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A scalable and integrated machine learning framework for molecular properties prediction

Chen, G., Song, Z., Qi, Z., & Sundmacher, K. (2023). A scalable and integrated machine learning framework for molecular properties prediction. AIChE Journal, 69(10): e18185. doi:10.1002/aic.18185.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-C389-C Version Permalink: https://hdl.handle.net/21.11116/0000-000E-021D-0

Genre: Journal Article

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Creators:
Chen, Guzhong^{1, 2, 3}, Author
Song, Zhen^{2, 3}, Author
Qi, Zhiwen², Author
Sundmacher, Kai^{1, 4}, 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, Shanghai, China, ou_persistent22
3Engineering Research Center of Resource Utilization of Carbon-containing Waste with Carbon Neutrality (Ministry of Education), East China University of Science and Technology, Shanghai, China, ou_persistent22
4Otto-von-Guericke-Universität Magdeburg, External Organizations, ou_1738156

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Language(s): eng - English

Dates: Date issued: 2023

Publication Status: Issued

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Rev. Type: Peer

Identifiers: DOI: 10.1002/aic.18185
Other: pubdata_escidoc:3528768

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Title: AIChE Journal

Source Genre: Journal

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Pages: - Volume / Issue: 69 (10) Sequence Number: e18185 Start / End Page: - Identifier: ISSN: 0001-1541
ISSN: 1547-5905