A DFT-based genetic algorithm search for AuCu nanoalloy electrocatalysts for CO₂ reduction.
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Decoupling strain and ligand effects in ternary nanoparticles for improved ORR electrocatalysis.Active learning with non-ab initio input features toward efficient CO2 reduction catalysts† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc03422a.Identifying systematic DFT errors in catalytic reactions
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A DFT-based genetic algorithm search for AuCu nanoalloy electrocatalysts for CO₂ reduction.
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2015 nî lūn-bûn
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name
A DFT-based genetic algorithm ...... rocatalysts for CO₂ reduction.
@en
A DFT-based genetic algorithm ...... rocatalysts for CO₂ reduction.
@nl
type
label
A DFT-based genetic algorithm ...... rocatalysts for CO₂ reduction.
@en
A DFT-based genetic algorithm ...... rocatalysts for CO₂ reduction.
@nl
prefLabel
A DFT-based genetic algorithm ...... rocatalysts for CO₂ reduction.
@en
A DFT-based genetic algorithm ...... rocatalysts for CO₂ reduction.
@nl
P2860
P50
P356
P1476
A DFT-based genetic algorithm ...... rocatalysts for CO₂ reduction.
@en
P2093
Jón S G Mýrdal
P2860
P304
28270-28276
P356
10.1039/C5CP00298B
P407
P577
2015-04-30T00:00:00Z