Regulating the Spin Polarization of NiFe Layered Double Hydroxide for the Enhanced Oxygen Evolution Reaction
Bibliographic record
Abstract
The oxygen evolution reaction (OER) is an electrochemical process that involves the spin-dependent conversion of singlet OH – /H 2 O to triplet O 2 . However, the sluggish dynamics associated with this reaction severely limits its efficiency in electrochemical water splitting. Fortunately, the utilization of a magnetic field can significantly enhance the spin selectivity and accelerate reaction kinetics. Herein, we report a unique strategy to regulate the spin polarization of NiFe layered double hydroxide (NiFe-LDH) by harnessing an internal magnetic field induced by a built-in magnetic core. The exchange bias effect between the magnetic core and NiFe-LDH can selectively remove electrons with opposite magnetic moments, thereby reducing magnetoresistances and minimizing spin scattering during electron transport. Benefiting from this bias effect, the obtained catalyst exhibits excellent OER performance with a low overpotential of 196 mV at a current density of 30 mA cm –2 . Furthermore, density functional theory (DFT) calculations further confirm that the exchange bias effect can increase the hybrid strength of Fe-3d and O-2p orbitals while decreasing the adsorption energy of the reactant intermediates, thus accelerating the generation of paramagnetic oxygen.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".