Thermodynamically consistent machine learning model for excess Gibbs energy.
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| Title: | Thermodynamically consistent machine learning model for excess Gibbs energy. |
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| Authors: | Hoffmann M; Laboratory of Engineering Thermodynamics, RPTU University Kaiserslautern-Landau, Kaiserslautern, Germany., Specht T; Laboratory of Engineering Thermodynamics, RPTU University Kaiserslautern-Landau, Kaiserslautern, Germany., Göttl Q; Laboratory of Chemical Process Engineering, Technical University of Munich, Munich, Germany., Burger J; Laboratory of Chemical Process Engineering, Technical University of Munich, Munich, Germany., Mandt S; Department of Computer Science & Statistics, University of California, Irvine, CA, USA., Hasse H; Laboratory of Engineering Thermodynamics, RPTU University Kaiserslautern-Landau, Kaiserslautern, Germany., Jirasek F; Laboratory of Engineering Thermodynamics, RPTU University Kaiserslautern-Landau, Kaiserslautern, Germany. fabian.jirasek@rptu.de. |
| Source: | Nature communications [Nat Commun] 2026 Apr 14; Vol. 17 (1). Date of Electronic Publication: 2026 Apr 14. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Pub. Group Country of Publication: England NLM ID: 101528555 Publication Model: Electronic Cited Medium: Internet ISSN: 2041-1723 (Electronic) Linking ISSN: 20411723 NLM ISO Abbreviation: Nat Commun Subsets: MEDLINE; PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2041-1723 |
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| DOI: | 10.1038/s41467-026-71430-y |
