TY  - JOUR
AU  - Malek, Ali
AU  - Baumann, Stefan
AU  - Guillon, Olivier
AU  - Eikerling, Michael
AU  - Malek, Kourosh
TI  - A Data-driven Framework for the Accelerated Discovery of CO2 Reduction Electrocatalysts
JO  - Frontiers in energy research
VL  - 9
SN  - 2296-598X
CY  - Lausanne
PB  - Frontiers Media
M1  - FZJ-2021-00943
SP  - 609070
PY  - 2021
AB  - 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.
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:000644398900001
DO  - DOI:10.3389/fenrg.2021.609070
UR  - https://juser.fz-juelich.de/record/890423
ER  -