Machine Learning applied to Reactivity: combination of HDNNs with ReaxFF

Project Information

MaLeR

Grant agreement ID: 798129

DOI 10.3030/798129

Project closed

EC signature date 21 March 2018

Start date 1 December 2018

End date 30 November 2020

Funded under

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Total cost € 165 598,80

EU contribution € 165 598,80

Coordinated by

SOFTWARE FOR CHEMISTRY & MATERIALS BV
Netherlands

Publications

Peer reviewed articles (3)

New Insights into the Catalytic Activity of Cobalt Orthophosphate Co 3 (PO 4 ) 2 from Charge Density Analysis

Author(s): Helena Keil, Matti Hellström, Claudia Stückl, Regine Herbst‐Irmer, Jörg Behler, Dietmar Stalke
Published in: Chemistry – A European Journal, Issue 25/69, 2019, Page(s) 15786-15794, ISSN 0947-6539
Publisher: John Wiley & Sons Ltd.
DOI: 10.1002/chem.201902303

Temperature effects on the ionic conductivity in concentrated alkaline electrolyte solutions

Author(s): Yunqi Shao, Matti Hellström, Are Yllö, Jonas Mindemark, Kersti Hermansson, Jörg Behler, Chao Zhang
Published in: Physical Chemistry Chemical Physics, Issue 22/19, 2020, Page(s) 10426-10430, ISSN 1463-9076
Publisher: Royal Society of Chemistry
DOI: 10.1039/c9cp06479f

PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials

Author(s): Yunqi Shao, Matti Hellström, Pavlin D. Mitev, Lisanne Knijff, Chao Zhang
Published in: Journal of Chemical Information and Modeling, Issue 60/3, 2020, Page(s) 1184-1193, ISSN 1549-9596
Publisher: American Chemical Society
DOI: 10.1021/acs.jcim.9b00994