Evaluating the ATR-SEIRAS performance of electrodeposited copper CO<sub>2</sub> reduction catalysts using a flow-through spectroelectrochemical cell
Bibliographic record
Abstract
The attenuated total reflection-surface-enhanced infrared absorption spectroscopy (SEIRAS) activity of electrodeposited Cu nanoparticles on indium tin oxide-modified Si internal reflection elements is reported. The solution in the cell is easily, and repeatedly, exchanged between a copper deposition bath and a solution containing 4-methoxypyridine through the use of a flow-through spectroelectrochemical cell. 4-methoxypyridine is a convenient SEIRAS probe molecule exhibiting potential-dependent adsorption/desorption on the copper surface. Successive amounts of copper are deposited and then evaluated for electrochemical SEIRAS activity without the need to expose the Cu surface to ambient conditions. It is found that copper deposition charge densities of approximately 60 mC cm−2 exhibit the largest amplitude and most symmetric IR absorption peaks of the investigated electrodeposition conditions. Scanning electron microscopy images of the different Cu charge density films are correlated with the SEIRAS results and establish that close-packed two-dimensional, percolated arrays of oblate, ellipsoidal Cu nanoparticles are responsible for ideal SEIRAS performance and three-dimensional aggregates of larger particles should be avoided. Textured films of Cu nanoparticles are used to determine the adsorbed species present on the copper surface during CO2 electroreduction at low overpotentials. Evidence of adsorbed CO and COH is found at lower overpotentials than those described in previous reports.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".