Strengthening absorption ability of Co–N–C as efficient bifunctional oxygen catalyst by modulating the d band center using MoC
Bibliographic record
Abstract
Co–N–C is a promising oxygen electrochemical catalyst due to its high stability and good durability. However, due to the limited adsorption ability improvement for oxygen-containing intermediates, it usually exhibits inadequate catalytic activity with 2-electron pathway and high selectivity of hydrogen peroxide . Herein, the adsorption of Co–N–C to these intermediates is modulated by constructing heterostructures using transition metals and their derivatives based on d -band theory. The heterostructured nanobelts with MoC core and pomegranate-like carbon shell consisting of Co nanoparticles and N dopant (MoC/Co–N–C) are engineered to successfully modulate the d band center of active Co–N–C sites, resulting in a remarkably enhanced electrocatalysis performance. The optimally performing MoC/Co–N–C exhibits outstanding bi-catalytic activity and stability for the oxygen electrochemistry , featuring a high wave-half potential of 0.865 V for the oxygen reduction reaction (ORR) and low overpotential of 370 mV for the oxygen evolution reaction (OER) at 10 mA cm −2 . The zinc air batteries with the MoC/Co–N–C catalyst demonstrate a large power density of 180 mW cm −2 and a long cycling lifespan (2000 cycles). The density functional theory calculations with Hubbard correction (DFT + U ) reveal the electron transferring from Co to Mo atoms that effectively modulate the d band center of the active Co sites and achieve optimum adsorption ability with “single site double adsorption” mode.
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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 | 0.000 |
| 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 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".