Time to move beyond transition metal — <scp>N</scp> — <scp>C</scp> catalysts for oxygen reduction
Bibliographic record
Abstract
Abstract FeNC and CoNC electrocatalysts have been studied for many years by numerous research groups. Various synthesis routes, involving different precursors, different temperatures, etc., have been employed, but “successful” catalysts share the common features of Fe or Co, N, and C and a heat‐treatment step to around 800 °C. It is our contention that the thermodynamics, not the details of the precursors or synthesis steps, determines the local atomic arrangement of Fe, N, and C or Co, N, and C in these catalysts after heating and, as such, the catalysts prepared by all researchers in this field are basically the same. In this article, compelling evidence for this contention is presented. These catalysts, presumably all, share the same advantages, which include reasonable activity, and disadvantages, which include short lifetime. Therefore, the study of FeNC and CoNC catalysts is overpopulated by researchers, and most should probably shift their focus to the search for new nonnoble metal catalysts involving other elements in the periodic table.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".