Zobrazeno 1 - 2
of 2
pro vyhledávání: '"Sai Mahit Vaddadi"'
Autor:
Qiyuan Zhao, Sai Mahit Vaddadi, Michael Woulfe, Lawal A. Ogunfowora, Sanjay S. Garimella, Olexandr Isayev, Brett M. Savoie
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-10 (2023)
Abstract Existing reaction transition state (TS) databases are comparatively small and lack chemical diversity. Here, this data gap has been addressed using the concept of a graphically-defined model reaction to comprehensively characterize a reactio
Externí odkaz:
https://doaj.org/article/402995be700f480f95d9da2b3060ef24
Autor:
Qiyuan Zhao, Sai Mahit Vaddadi, Michael Woulfe, Lawal Ogunfowora, Sanjay Garimella, Olexandr Isayev, Brett Savoie
Extant reaction transition state (TS) databases are comparatively small and lack chemical diversity. Here, this data gap has been addressed using the concept of a graphically-defined model reaction to comprehensively characterize a reaction space ass
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae73dcd9d6814fc479328554e3aa518e
https://doi.org/10.26434/chemrxiv-2022-1vmwv
https://doi.org/10.26434/chemrxiv-2022-1vmwv
