Employable Electrocatalysts: a DFT Investigation of NORR using Porphyrin-Based Transition Metal SACs
Bibliographic record
Abstract
Nitric Oxide (NO) is an airborne pollutant released into the atmosphere by the combus- tion of fossil fuels. Its toxicity has short- and long term effects, including respiratory toxicity, DNA damage, and interference with the oxygen-delivery capacity of blood heme. Here, the reduction of Nitric Oxide to ammonia (NORR) by transition metal single atom cat- alysts within an unreactive porphyrin structure is examined theoretically. Density Func- tional Theory calculations are used to investigate the energetic relationships between reac- tion steps and to assess the overall catalytic ability of each catalyst. The adsorption and reaction pathways for NO reduction on a series of metalloporphyrin catalysts are iden- tified. Among several catalysts examined here, Cr-porphyrin emerges as the most likely NORR candidate, demonstrating exergonic adsorption of NO and minimum overpotential. The adsorption of NO is identified as the critical step, and the associated change in free energy is found to heavily influence the energy landscape of the overall reduction reaction. These insights establish Cr metalloporphyrins as potential NORR catalysts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".