Co–Pyridinic-N Bond Constructed at the Interface of Co<sub><i>x</i></sub>P and N-Doped Carbon to Effectively Facilitate Oxygen Reduction
Bibliographic record
Abstract
The construction of bonding interfaces between cobalt-base phosphides and N-doped carbon is considered an effective means to promote ORR catalytic performance. However, the role of different nitrogen configurations in promoting the ORR performance of cobalt-base phosphides is currently unknown. Herein, the honeycomb-like Co x P@N-doped carbon catalyst was constructed to systematically investigate the effect of different nitrogen configurations on improving the catalytic performance of Co x P. Systematic experimental investigations and density functional theory (DFT) calculations indicate that the interaction of Co with pyridinic-N not only regulates the atomic Co coordination environment but also induces strong orbital hybridization between N-p orbitals and Co-d orbitals, significantly increasing the electron density on pyridinic-N sites, which greatly increases the attraction to oxygen-containing intermediates and lowers the reaction energy barrier, thus promoting the catalytic activity for ORR. Furthermore, honeycomb morphology not only reduces the internal diffusion resistance of reactants and products as well as the relative concentration of surface reactants but also exposes more accessible active sites and increases the contact area with the electrolyte, thus greatly enhancing the oxygen reduction reaction. As expected, the as-prepared catalyst exhibits ultrahigh ORR activity with a half-wave potential of 0.88 V, which is superior to that of the noble metal Pt and most previously reported non-noble metal catalysts. This study perfectly explains why cobalt-base phosphide embedded in N-doped carbon can improve its ORR catalytic performance.
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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".