Author Archives: Arsalan Hashemi

Density functional theory and machine learning for electrochemical square-scheme prediction: an application to quinone-type molecules relevant to redox flow batteries

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Digital Discovery, 2023, 2,1565-1576
DOI: 10.1039/D3DD00091E, Paper
Open Access Open Access
Creative Commons Licence  This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.
Arsalan Hashemi, Reza Khakpour, Amir Mahdian, Michael Busch, Pekka Peljo, Kari Laasonen
Computational high-throughput is used to evaluate proton–electron transfer reactions of quinone-type compounds that are potentially useful for energy storage.
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