Diamonds in the Rough: Direct Surface Enhanced Infrared Spectroscopic Evidence of Nitrogen Reduction on Boron-Doped Diamond Supported Metal Catalysts
Bibliographic record
Abstract
In situ investigations of electrocatalytic processes of increasing societal interest such as the nitrogen reduction reaction (NRR) require aggressive experimental conditions that are not readily compatible with surface sensitive techniques such as attenuated total reflection surface enhanced infrared absorption spectroscopy (ATR-SEIRAS). A method for performing ATR-SEIRAS studies at very negative potentials where conventional IR-active films delaminate and fail is reported. The method relies on a thin film of very robust boron-doped diamond deposited on a micromachined Si wafer, which provides extended mid-IR transparency at long wavelengths. SEIRAS activity is achieved by electrodepositing gold nanoparticles onto the conductive BDD layer. The Au@BDD layers are shown to sustain prolonged periods of electrolysis at negative potentials, with no degradation of the modifying layer. The efficacy of these substrates for electrocatalysis is demonstrated by studying the reduction of N 2 at −1.5 V vs Ag/AgCl in an aqueous-based electrolyte. Under these conditions, direct spectroscopic evidence of both NH 3 and hydrazine formed from the nitrogen reduction reaction (NRR) is provided.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".