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Hydrogen Evolution Reaction: Unraveling the Factors Behind the Efficiency of Hydrogen Evolution in Endohedrally Doped C60 Structures via Ab Initio Calculations and Insights from Machine Learning Models (Adv. Theory Simul. 3/2019). Issue 3 (1st March 2019)
Record Type:
Journal Article
Title:
Hydrogen Evolution Reaction: Unraveling the Factors Behind the Efficiency of Hydrogen Evolution in Endohedrally Doped C60 Structures via Ab Initio Calculations and Insights from Machine Learning Models (Adv. Theory Simul. 3/2019). Issue 3 (1st March 2019)
Main Title:
Hydrogen Evolution Reaction: Unraveling the Factors Behind the Efficiency of Hydrogen Evolution in Endohedrally Doped C60 Structures via Ab Initio Calculations and Insights from Machine Learning Models (Adv. Theory Simul. 3/2019)
Abstract : Machine learning has emerged as a powerful complementation to accurate ab intio methods. In article number1800202, Sean C. Smith and co‐workers have studied C60 metallofullerenes as catalysts for hydrogen evolution reactions. By using a number of electronic features, metallofullerenes' overpotentials can be rapidly assessed without fully resorting to time consuming ab initio calculations.