Hauptseite > Publikationsdatenbank > A Data-driven Framework for the Accelerated Discovery of CO2 Reduction Electrocatalysts > print |
001 | 890423 | ||
005 | 20240712113145.0 | ||
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100 | 1 | _ | |a Malek, Ali |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
245 | _ | _ | |a A Data-driven Framework for the Accelerated Discovery of CO2 Reduction Electrocatalysts |
260 | _ | _ | |a Lausanne |c 2021 |b Frontiers Media |
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520 | _ | _ | |a 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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700 | 1 | _ | |a Baumann, Stefan |0 P:(DE-Juel1)129587 |b 1 |
700 | 1 | _ | |a Guillon, Olivier |0 P:(DE-Juel1)161591 |b 2 |
700 | 1 | _ | |a Eikerling, Michael |0 P:(DE-Juel1)178034 |b 3 |
700 | 1 | _ | |a Malek, Kourosh |0 P:(DE-Juel1)181057 |b 4 |e Corresponding author |
773 | _ | _ | |a 10.3389/fenrg.2021.609070 |0 PERI:(DE-600)2733788-1 |p 609070 |t Frontiers in energy research |v 9 |y 2021 |x 2296-598X |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/890423/files/AM_etal_27012021_Frontiers_Final.pdf |y OpenAccess |
856 | 4 | _ | |u https://juser.fz-juelich.de/record/890423/files/fenrg-09-609070.pdf |y OpenAccess |
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