Machine Learning Accelerates the Discovery of Design Rules and Exceptions in Stable Metal–Oxo Intermediate Formation

Machine Learning Accelerates the Discovery of Design Rules and Exceptions in Stable Metal–Oxo Intermediate Formation

Metal-oxo moieties are important catalytic intermediates in the selective partial oxidation of hydrocarbons and in water splitting. Stable metal-oxo species have reactive properties that vary depending on the spin state of the metal, complicating the development of structure-property relationships....

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Bibliografiska uppgifter
Huvudupphovsmän: Nandy, Aditya, Zhu, Jiazhou, Janet, Jon Paul, Duan, Chenru, Getman, Rachel B., Kulik, Heather Janine
Övriga upphovsmän: Massachusetts Institute of Technology. Department of Chemistry
Materialtyp: Artikel
Språk:English
Publicerad: American Chemical Society (ACS) 2019
Länkar:https://hdl.handle.net/1721.1/122278

Internet

https://hdl.handle.net/1721.1/122278

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