Boosting Nitrogen Reduction to Ammonia on FeN 4 Sites by Atomic Spin Regulation
Bibliographic record
Abstract
Understanding the relationship between the electronic state of active sites and N2 reduction reaction (NRR) performance is essential to explore efficient electrocatalysts. Herein, atomically dispersed Fe and Mo sites are designed and achieved in the form of well-defined FeN4 and MoN4 coordination in polyphthalocyanine (PPc) organic framework to investigate the influence of the spin state of FeN4 on NRR behavior. The neighboring MoN4 can regulate the spin state of Fe center in FeN4 from high-spin (dxy2 dyz1 dxz1dz21dx2-y21 ) to medium-spin (dxy2 dyz2 dxz1dz21 ), where the empty d orbitals and separate d electron favor the overlap of Fe 3d with the N 2p orbitals, more effectively activating N≡N triple bond. Theoretical modeling suggests that the NRR preferably takes place on FeN4 instead of MoN4 , and the transition of Fe spin state significantly lowers the energy barrier of the potential determining step, which is conducive to the first hydrogenation of N2 . As a result, FeMoPPc with medium-spin FeN4 exhibits 2.0 and 9.0 times higher Faradaic efficiency and 2.0 and 17.2 times higher NH3 yields for NRR than FePPc with high-spin FeN4 and MoPPc with MoN4 , respectively. These new insights may open up opportunities for exploiting efficient NRR electrocatalysts by atomically regulating the spin state of metal centers.
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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) | 0.000 | 0.001 |
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".