In Situ Electrochemistry of Formate on Cu Thin Films Using ATR-FTIR Spectroscopy and X-ray Photoelectron Spectroscopy
Bibliographic record
Abstract
Formate (HCOO – ) is the most dominant intermediate identified during carbon dioxide electrochemical reduction (CO 2 ER). While previous studies showed that copper (Cu)-based materials that include Cu(0), Cu 2 O, and CuO are ideal catalysts for CO 2 ER, challenges to scalability stem from low selectivity and undesirable products in the −1.0–1.0 V range. There are few studies on the binding mechanism of intermediates and products for these systems as well as on changes to surface sites upon applying potential. Here, we use an in situ approach to study the redox surface chemistry of formate on Cu thin films deposited on Si wafers using a VeeMAX III spectroelectrochemical (SEC) cell compatible with attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). Spectra for surface species were collected in real time as a function of applied potential during cyclic voltammetry (CV) experiments. Results showed the reproducibility of CV curves on freshly prepared Cu/Si wafers with relatively high signal-to-noise ATR-FTIR absorbance features of surface species during these electrochemical experiments. The oxidation reaction of HCOO – to bicarbonate (HCO 3 – ) was observed using ATR-FTIR at a voltage of 0.27 V. Samples were then subjected to reduction in the CV, and the aqueous phase products below the detection limit of the SEC-ATR-FTIR were identified using ion chromatography (IC). We report the formation of glycolate (H 3 C 2 O 3 – ) and glyoxylate (HC 2 O 3 – ) with trace amounts of oxalate (C 2 O 4 2– ), indicating that C–C coupling reactions proceed in these systems. Changes to the oxidation state of surface Cu were measured using X-ray photoelectron spectroscopy, which showed a reduction in Cu(0) and an increase in Cu(OH) 2, indicating surface oxidation.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".