Elaboration of Cu−Pd Films by Coelectrodeposition: Application to Nitrate Electroreduction
Bibliographic record
Abstract
In this study, nanocrystalline copper−palladium films were synthesized over a wide range of compositions by coelectrodeposition of Pd and Cu in a 1 M NaCl solution containing both CuCl 2 and PdCl 2 in various proportions. The deposition potential was fixed at −0.5 V versus a saturated calomel electrode (SCE). These coatings were characterized by scanning electron microscopy coupled to energy dispersive X-ray analysis (SEM−EDX), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). These analyses revealed a fine and homogeneous distribution of Pd and Cu within and over the whole surface of the film. Depending upon the Cu(II)/Pd(II) ratio in solution, monophased Pd-rich films (Pd 95 Cu 5 or Pd 88 Cu 12 alloys) or biphased films (containing Pd 80 Cu 20 and Cu phases in different proportions) were obtained. Theses materials were tested as electrocatalysts for nitrate reduction in alkaline media. Electrochemical measurements showed that biphasic (Pd 80 Cu 20 + Cu) materials displayed the best electrocatalytic activity toward nitrate reduction. Results of prolonged electrolysis also proved that the selectivity of the modified electrodes clearly depends not only on the applied potential but also on their structure and chemical composition. At −1.3 V versus Hg/HgO, all the electrodes (except pure palladium, which is inactive for nitrate reduction) mainly produced ammonia. However, at −0.93 V versus Hg/HgO, biphasic Cu−Pd electrode composed of 77% Pd 80 Cu 20 + 23% Cu successfully reduced nitrate to nitrogen with a current efficiency approaching 76%.
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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 | 0.000 | 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 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".