Making thermodynamic models of mixtures predictive by machine learning: matrix completion of pair interactions
Abstract
Embedding matrix completion methods from machine learning in classical thermodynamic models creates powerful hybrid models for predicting properties of mixtures.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2022
- Source ID
- 10.1039/d1sc07210b
Entities
People
- Fabian Jirasek
- Hans Hasse
- Marius Kloft
- Michael Bortz
- Robert Bamler
- Sophie Fellenz
- Stephan Mandt
Organizations
- Carl-Zeiss-Stiftung
- Defense Advanced Research Projects Agency
- Federal Ministry for Economic Affairs and Climate Action
- Intel Corporation
- National Science Foundation
- Office of Science
- Qualcomm
- University of California, Irvine
- University of Kaiserslautern
- University of Tübingen