Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Hannes Kneiding"'
Autor:
Hannes Kneiding, Ruslan Lukin, Lucas Lang, Simen Reine, Thomas Bondo Pedersen, Riccardo De Bin, David Balcells
Publikováno v:
Digital Discovery.
Machine learning can make a strong contribution to accelerating the discovery of transition metal complexes (TMC). These compounds will play a key role in the development of new technologies for which there is an urgent need, including the production
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5df85c5557c66eac0c9d92a1d6d92f8a
https://doi.org/10.1039/d2dd00129b
https://doi.org/10.1039/d2dd00129b
Deep graph learning can make a strong contribution to accelerating the discovery of transition metal complexes (TMCs). TMCs will play a key role in the development of new technologies for which there is an urgent need; e.g. the production of green hy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6241f35387e415184d61ebf1e4e3f45b
https://doi.org/10.26434/chemrxiv-2022-fd43k
https://doi.org/10.26434/chemrxiv-2022-fd43k
