Discovery of Ni(I) Complexes for CO2 Insertion Enabled by a Machine Learning-Computational-Selection Sequence

The fate of a catalyst or catalytic intermediate, i.e., its speciation, in situ is a critical aspect of the efficiency of a catalyst as well as the overall reactivity and selectivity of the catalyzed transformation. However, the precise factors that dictate catalyst speciation are...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Julian A. Hueffel (21743274) (author)
مؤلفون آخرون:	Mathilde Rigoulet (4092445) (author), Sebastian Wellig (16504745) (author), Theresa Sperger (3228054) (author), Jas S. Ward (1502479) (author), Kari Rissanen (1282326) (author), Franziska Schoenebeck (1266411) (author)
منشور في:	2025
الموضوعات:	Biophysics Biochemistry Medicine Infectious Diseases Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified sterically least hindered develop predictive tools catalytically relevant context analyzing virtual databases guide ligand selection desired metal speciation machine learning led machine learning combined depth computational rationalization dictate catalyst speciation 2 </ sub machine learning selection sequence situ </ silico </ work offers sup >( subsequently filtered subsequent application room temperature rarely understood precise factors oxidation state numerous ligands identify ligands experimentally tested e ., descriptor database critical aspect computational predictions catalyzed transformation catalytic intermediate activation barriers )</ sup
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Discovery of Ni<sup>(I)</sup> Complexes for CO<sub>2</sub> Insertion Enabled by a Machine Learning-Computational-Selection Sequence

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