Rational Design of Silver Sulfide Nanowires for Efficient CO<sub>2</sub> Electroreduction in Ionic Liquid
Bibliographic record
Abstract
Electroreduction of CO 2 holds the promise for the utilization of CO 2 and the storage of intermittent renewable energy. The development of efficient catalysts for effectively converting CO 2 to fuels has never been more imperative. Herein, we successfully synthesized Ag 2 S nanowires (NWs) dominating at the facet of (121) using a modified facile one-step method and utilized them as a catalyst for electrochemical CO 2 reduction reaction (CO 2 RR). Ag 2 S NWs in ionic liquid (IL) possess a partial current density of 12.37 mA cm –2, ∼14- and ∼17.5-fold higher than those of Ag 2 S NWs and bulk Ag in KHCO 3, respectively. Moreover, it shows significantly higher selectivity with a value of 92.0% at the overpotential (η) of −0.754 V. More importantly, the CO formation begins at a low η of 54 mV. The good performance originates from not only the presence of [EMIM–CO 2 ] + complexes but also the specific facet contribution. The partial density of states (PDOS) and work functions reveal that the d band center of the surface Ag atom of Ag 2 S(121) is closer to the Fermi energy level and has a higher d-electron density than those of Ag(111) and Ag55, which lowers transition state energy for CO 2 RR. Besides, density functional theory (DFT) calculations indicate that the COOH* formation over Ag 2 S is energetically more favorable on (111) and (121) facets than that on Ag(111) and Ag55. Therefore, we conclude that the significantly enhanced performance of Ag 2 S NWs in IL synergistically originates from the solvent-assisted and specific facet-promoted contributions. This distinguishes Ag 2 S NWs in IL as an attractive and selective platform for CO 2 RR.
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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) | 0.000 | 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".