Shape-Dependent Electrocatalytic Reduction of CO<sub>2</sub> to CO on Triangular Silver Nanoplates
Bibliographic record
Abstract
Electrochemical reduction of CO 2 (CO 2 RR) provides great potential for intermittent renewable energy storage. This study demonstrates a predominant shape-dependent electrocatalytic reduction of CO 2 to CO on triangular silver nanoplates (Tri-Ag-NPs) in 0.1 M KHCO 3 . Compared with similarly sized Ag nanoparticles (SS-Ag-NPs) and bulk Ag, Tri-Ag-NPs exhibited an enhanced current density and significantly improved Faradaic efficiency (96.8%) and energy efficiency (61.7%), together with a considerable durability (7 days). Additionally, CO starts to be observed at an ultralow overpotential of 96 mV, further confirming the superiority of Tri-Ag-NPs as a catalyst for CO 2 RR toward CO formation. Density functional theory calculations reveal that the significantly enhanced electrocatalytic activity and selectivity at lowered overpotential originate from the shape-controlled structure. This not only provides the optimum edge-to-corner ratio but also dominates at the facet of Ag(100) where it requires lower energy to initiate the rate-determining step. This study demonstrates a promising approach to tune electrocatalytic activity and selectivity of metal catalysts for CO 2 RR by creating optimal facet and edge site through shape-control synthesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".