Combining machine learning models and Sabatier's principle to predict the activity of homogeneous catalysts
2019
Details
Title
Combining machine learning models and Sabatier's principle to predict the activity of homogeneous catalysts
Published in
Abstracts Of Papers Of The American Chemical Society
Volume
257
Conference
National Meeting of the American-Chemical-Society (ACS), Mar 31-Apr 04, 2019, Orlando, FL
Date
2019-03-31
Publisher
Washington, AMER CHEMICAL SOC
ISSN
0065-7727
Other identifier(s)
View record in Web of Science
Record Appears in
Scientific production and competences > SB - School of Basic Sciences > ISIC - Institute of Chemical Sciences and Engineering > LCBC - Laboratory of Computational Chemistry and Biochemistry
Scientific production and competences > SB - School of Basic Sciences > ISIC - Institute of Chemical Sciences and Engineering > LCMD - Laboratory of Computational Molecular Design
Peer-reviewed publications
Conference Papers
Work produced at EPFL
Published
Scientific production and competences > SB - School of Basic Sciences > ISIC - Institute of Chemical Sciences and Engineering > LCMD - Laboratory of Computational Molecular Design
Peer-reviewed publications
Conference Papers
Work produced at EPFL
Published
Record creation date
2019-08-22