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  Hybrid data-driven and mechanistic modeling approaches for multiscale material and process design

Zhou, T., Gani, R., & Sundmacher, K. (2021). Hybrid data-driven and mechanistic modeling approaches for multiscale material and process design. Engineering, 7(9), 1231-1238. doi:10.1016/j.eng.2020.12.022.

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zhou_3310847.pdf (Publisher version), 336KB
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Copyright 2021 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company.This is an open access article under the CC BY-NC-ND license

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 Creators:
Zhou, Teng1, 2, Author              
Gani, Rafiqul3, 4, Author
Sundmacher, Kai1, 2, Author              
Affiliations:
1Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society, ou_1738151              
2Otto-von-Guericke-Universität Magdeburg, External Organizations, ou_1738156              
3PSE for SPEED Co. Ltd., Allerod DK 3450, Denmark, ou_persistent22              
4Department of Chemical and Biomolecular Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea, ou_persistent22              

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Language(s): eng - English
 Dates: 2021
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.eng.2020.12.022
Other: pubdata_escidoc:3310847
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Title: Engineering
Source Genre: Journal
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Pages: - Volume / Issue: 7 (9) Sequence Number: - Start / End Page: 1231 - 1238 Identifier: ISSN: 20958099