Electrochemical reduction of CO<sub>2</sub> in an aqueous electrolyte employing an iridium/ruthenium‐oxide electrode
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
Abstract Electrochemical reduction of CO2 in an aqueous electrolyte (Briton Robinson buffer, pH = 5.82) was investigated using an Ir/Ru‐oxide coating deposited on a titanium substrate, as a function of electrode potential and temperature. The results demonstrated that the Ir/Ru‐oxide electrode can efficiently be used for the electrochemical conversion of CO2 into different valuable organic molecules at high faradaic efficiency, 85 % and 96 % at 295 K and 277 K, respectively. Ethanol was found to be the major electrochemical reduction product remained in the liquid phase, with a minor contribution of methanol, acetone and acetaldehyde. The amount of formed products and the corresponding faradaic efficiency were found to be strongly dependent on electrode potential. A maximum in both was obtained at −1.7 V (vs. MSE). At this potential, lowering the reaction temperature from 295 K to 277 K was found to increase the CO2 reduction kinetics only at short electrolysis times, while the corresponding faradaic efficiency increased significantly. The presented work demonstrates that the Ir/Ru‐oxide electrode can be considered as a good electrode candidate for the electrochemical conversion of CO2 into usable organic molecules at atmospheric pressure and in aqueous electrolytes.
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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 | 0.001 | 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".