Constructing Asymmetrical Coordination Microenvironment with Phosphorus‐Incorporated Nitrogen‐Doped Carbon to Boost Bifunctional Oxygen Electrocatalytic Activity
Bibliographic record
Abstract
Abstract Carbon‐based metal‐free electrocatalysts have been recognized as inexpensive alternatives to afford excellent activity in oxygen reduction/evolution reactions (ORR/OER). Nevertheless, precisely identifying the local active sites and tailoring the corresponding electronic properties to enhance the reaction kinetics remain challenging. Herein, a facile strategy to create a metal‐free electrocatalyst comprised of a mesoporous nitrogen‐doped carbon matrix with phosphorus incorporation (NPC) is described. The as‐prepared NPC‐950 electrocatalyst demonstrates superior ORR activity under alkaline and acidic conditions with half‐wave potentials of 0.88 and 0.72 V, respectively, comparable to commercial Pt/C (0.85 and 0.76 V) and overwhelmingly superior to other N‐doped carbon catalyst materials. In addition, a remarkable promotion of OER activity under alkaline conditions is observed. Notably, a zinc–air battery equipped with this NCP‐950 electrocatalyst exhibits exceptional performance in peak power density, specific capacity, and long‐term operation durability. Theoretical calculations uncover that the incorporation of phosphorus in NC material results in effective charge density redistribution, thus modulating the electronic properties of active sites to achieve optimum adsorption and desorption of ORR intermediates. The work provides a deep understanding of active sites in heteroatom‐doped carbon materials and highlights the importance of the electronic properties modulation in oxygen bifunctional electrocatalytic activity.
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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".