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@ARTICLE{Malek:890423,
author = {Malek, Ali and Baumann, Stefan and Guillon, Olivier and
Eikerling, Michael and Malek, Kourosh},
title = {{A} {D}ata-driven {F}ramework for the {A}ccelerated
{D}iscovery of {CO}2 {R}eduction {E}lectrocatalysts},
journal = {Frontiers in energy research},
volume = {9},
issn = {2296-598X},
address = {Lausanne},
publisher = {Frontiers Media},
reportid = {FZJ-2021-00943},
pages = {609070},
year = {2021},
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.},
cin = {IEK-13 / IEK-1 / JARA-ENERGY},
ddc = {333.7},
cid = {I:(DE-Juel1)IEK-13-20190226 / I:(DE-Juel1)IEK-1-20101013 /
$I:(DE-82)080011_20140620$},
pnm = {123 - Chemische Energieträger (POF4-123)},
pid = {G:(DE-HGF)POF4-123},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000644398900001},
doi = {10.3389/fenrg.2021.609070},
url = {https://juser.fz-juelich.de/record/890423},
}