Insights into Pd-Nb@In2Se3 Electrocatalyst for High-Performance and Selective CO2 Reduction Reaction from DFT

The electrochemical CO2 reduction reaction (eCO2RR), driven by renewable energy, represents a promising strategy for mitigating atmospheric CO2 levels while generating valuable fuels and chemicals. Its practical implementation hinges on the development of highly efficient electrocatalysts. In this study, a novel dual-metal atomic catalyst (DAC), composed of niobium and palladium single atoms anchored on a ferroelectric α-In2Se3 monolayer (Nb-Pd@In2Se3), is proposed based on density functional theory (DFT) calculations. The investigation encompassed analyses of structural and electronic characteristics, CO2 adsorption configurations, transition-state energetics, and Gibbs free energy changes during the eCO2RR process, elucidating a synergistic catalytic mechanism. The Nb-Pd@In2Se3 DAC system demonstrates enhanced CO2 activation compared to single-atom counterparts, which is attributed to the complementary roles of Nb and Pd sites. Specifically, Nb atoms primarily drive carbon reduction, while neighboring Pd atoms facilitate oxygen species removal through proton-coupled electron transfer. This dual-site interaction lowers the overall reaction barrier, promoting efficient CO2 conversion. Notably, the polarization switching of the In2Se3 substrate dynamically modulates energy barriers and reaction pathways, thereby influencing product selectivity. Our work provides theoretical guidance for designing ferroelectric-supported DACs for the eCO2RR.

Authors

Institutions

Publication Details

Journal
Inorganics
Published
2025-05-05
DOI
https://doi.org/10.3390/inorganics13050146
Citations
1
Primary Topic
CO2 Reduction Techniques and Catalysts
Type
article
Field-Weighted Citation Impact
0.36

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Insights into Pd-Nb@In2Se3 Electrocatalyst for High-Performance and Selective CO2 Reduction Reaction from DFT

Xiao Tang, Shuli Liu, Mengya Chen, Long Chen et al.
1 citations
Inorganics
CO2 Reduction Techniques and Catalysts
0.36
article

Insights into Pd-Nb@In2Se3 Electrocatalyst for High-Performance and Selective CO2 Reduction Reaction from DFT

Xiao Tang, Shuli Liu, Mengya Chen, Long Chen, Yixin Zhang, Lin Ju
article en
1 citations

Abstract

The electrochemical CO2 reduction reaction (eCO2RR), driven by renewable energy, represents a promising strategy for mitigating atmospheric CO2 levels while generating valuable fuels and chemicals. Its practical implementation hinges on the development of highly efficient electrocatalysts. In this study, a novel dual-metal atomic catalyst (DAC), composed of niobium and palladium single atoms anchored on a ferroelectric α-In2Se3 monolayer (Nb-Pd@In2Se3), is proposed based on density functional theory (DFT) calculations. The investigation encompassed analyses of structural and electronic characteristics, CO2 adsorption configurations, transition-state energetics, and Gibbs free energy changes during the eCO2RR process, elucidating a synergistic catalytic mechanism. The Nb-Pd@In2Se3 DAC system demonstrates enhanced CO2 activation compared to single-atom counterparts, which is attributed to the complementary roles of Nb and Pd sites. Specifically, Nb atoms primarily drive carbon reduction, while neighboring Pd atoms facilitate oxygen species removal through proton-coupled electron transfer. This dual-site interaction lowers the overall reaction barrier, promoting efficient CO2 conversion. Notably, the polarization switching of the In2Se3 substrate dynamically modulates energy barriers and reaction pathways, thereby influencing product selectivity. Our work provides theoretical guidance for designing ferroelectric-supported DACs for the eCO2RR.

InorganicsVol. 13(5)
Nanjing Forestry University (CN), Anyang Normal University (CN)
Natural Science Foundation of Henan Province
Openalex Percentile: Top 44%
CO2 Reduction Techniques and Catalysts
0.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.