Journal Article

FZJ-2021-00943

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png A Data-driven Framework for the Accelerated Discovery of CO2 Reduction Electrocatalysts

Malek, A. (Corresponding author) ; Baumann, S.FZJ* ; Guillon, O.FZJ* ; Eikerling, M.FZJ* ; Malek, K. (Corresponding author)FZJ*

2021
Frontiers Media Lausanne

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Please use a persistent id in citations: http://hdl.handle.net/2128/27826  doi:10.3389/fenrg.2021.609070

Abstract: Searching for next-generation electrocatalyst materials for electrochemical energy technologies is a time-consuming and expensive process, even if it is enabled by high-throughput experimentation and extensive first-principle calculations. In particular, the development of more active, selective and stable electrocatalysts for the CO2 reduction reaction remains tedious and challenging. Here, we introduce a material recommendation and screening framework, and demonstrate its capabilities for certain classes of electrocatalyst materials for low or high-temperature CO2 reduction. The framework utilizes high-level technical targets, advanced data extraction, and categorization paths, and it recommends the most viable materials identified using data analytics and property-matching algorithms. Results reveal relevant correlations that govern catalyst performance under low and high-temperature conditions.

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Contributing Institute(s):

1. IEK-13 (IEK-13)
2. Werkstoffsynthese und Herstellungsverfahren (IEK-1)
3. JARA-ENERGY (JARA-ENERGY)

Research Program(s):

1. 123 - Chemische Energieträger (POF4-123) (POF4-123)

Appears in the scientific report 2021

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Database coverage:
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