Rational Design of Silver Sulfide Nanowires for Efficient CO<sub>2</sub> Electroreduction in Ionic Liquid
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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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it