Coordination Structure Modulation in Group‐VIB Metal Doped Ag <sub>3</sub> PO <sub>4</sub> Augments Active Site Density for Electrocatalytic Conversion of N <sub>2</sub> to NH <sub>3</sub>
Bibliographic record
Abstract
Abstract Doping is considered a promising material engineering strategy in electrochemical nitrogen reduction reaction (NRR), provided the role of the active site is rightly identified. This work concerns the doping of group VIB metal in Ag 3 PO 4 to enhance the active site density, accompanied by d‐p orbital mixing at the active site/N 2 interface. Doping induces compressive strain in the Ag 3 PO 4 lattice and inherently accompanies vacancy generation, the latter is quantified with positron annihilation lifetime studies (PALS). This eventually alters the metal d‐electronic states relative to Fermi level and manipulate the active sites for NRR resulting into side‐on N 2 adsorption at the interface. The charge density deployment reveals Mo as the most efficient dopant, attaining a minimum NRR overpotential, as confirmed by the detailed kinetic study with the rotating ring disk electrode (RRDE) technique. In fact, the Pt ring of RRDE fails to detect N 2 H 4 , which is formed as a stable intermediate on the electrode surface, as identified from in‐situ attenuated total reflectance‐infrared (ATR‐IR) spectroscopy. This advocates the complete conversion of N 2 to NH 3 on Mo/Ag 3 PO 4 ‐10 and the so‐formed oxygen vacancies formed during doping act as proton scavengers suppressing hydrogen evolution reaction resulting into a Faradaic efficiency of 54.8% for NRR.
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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".