Improving Electrocatalytic Oxygen Evolution through Local Field Distortion in Mg/Fe Dual‐site Catalysts
Bibliographic record
Abstract
Abstract Transition metal single atom electrocatalysts (SACs) with metal‐nitrogen‐carbon (M−N−C) configuration show great potential in oxygen evolution reaction (OER), whereby the spin‐dependent electrons must be allowed to transfer along reactants (OH − /H 2 O, singlet spin state) and products (O 2 , triplet spin state). Therefore, it is imperative to modulate the spin configuration in M−N−C to enhance the spin‐sensitive OER energetics, which however remains a significant challenge. Herein, we report a local field distortion induced intermediate to low spin transition by introducing a main‐group element (Mg) into the Fe−N−C architecture, and decode the underlying origin of the enhanced OER activity. We unveil that, the large ionic radii mismatch between Mg 2+ and Fe 2+ can cause a FeN 4 in‐plane square local field deformation, which triggers a favorable spin transition of Fe 2+ from intermediate (d xy 2 d xz 2 d yz 1 d z2 1 , 2.96 μ B ) to low spin (d xy 2 d xz 2 d yz 2 , 0.95 μ B ), and consequently regulate the thermodyna‐mics of the elementary step with desired Gibbs free energies. The as‐obtained Mg/Fe dual‐site catalyst demonstrates a superior OER activity with an overpotential of 224 mV at 10 mA cm −2 and an electrolysis voltage of only 1.542 V at 10 mA cm −2 in the overall water splitting, which outperforms those of the state‐of‐the‐art transition metal SACs.
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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) | 0.000 | 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 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".