Potential-Dependent Adsorption of CO and Its Low-Overpotential Reduction to CH<sub>3</sub>CH<sub>2</sub>OH on Cu(511) Surface Reconstructed from Cu(pc): Operando Studies by Seriatim STM-EQCN-DEMS
Bibliographic record
Abstract
Operando scanning tunneling microscopy first revealed that application of a CO 2 -reduction potential to a Cu(pc) electrode in 0.1 M KOH resulted in the reconstruction of the selvedge to an x-layer stack of well-ordered Cu(100) terraces, Cu(pc)-x[Cu(100)]. Subsequent Cu↔Cu 2 O oxidation-reduction cycles between −0.90 V and 0.10 V SHE converted the reconstructed region to a stepped Cu(S)-[3(100) × (111)], or Cu(511), surface. Differential electrochemical mass spectrometry showed that reduction of CO produced only CH 3 CH 2 OH at the lowest overpotential. Later application of STM and surface infrared spectroscopy uncovered a potential, above which no CO adsorption occurs. In this study, electrochemical quartz crystal nanobalance was combined with STM and DEMS as a prelude to the acquisition of CO coverages as continuous functions of concentration and potential; in heterogeneous catalysis, surface coverage are important since the reaction rate are functions of those quantities. Also equally critical is the knowledge of the packing arrangement at the onset of the reaction because, if "CO dimers" were indeed the precursors to C 2+ products, reduction can only be initiated when the adlayer consists of closely packed CO; otherwise, dimerization will not transpire if the molecules were far apart. The results indicate that the catalysis lags the adsorption, and starts only when CO adsorption is saturated.
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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".