Engineering Molecular Heterostructured Catalyst for Oxygen Reduction Reaction
Bibliographic record
Abstract
Introducing a second metal species into atomically dispersed metal–nitrogen–carbon (M–N–C) catalysts to construct diatomic sites (DASs) is an effective strategy to elevate their activities and stabilities. However, the common pyrolysis-based method usually leads to substantial uncertainty for the formation of DASs, and the precise identification of the resulting DASs is also rather difficult. In this regard, we developed a two-step specific-adsorption strategy (pyrolysis-free) and constructed a DAS catalyst featuring FeCo “molecular heterostructures” (FeCo-MHs). In order to rule out the possibility of the two apparently neighboring (in the electron microscopy image) Fe/Co atoms being dispersed respectively on the top/bottom surfaces of the carbon support and thus forming “false” MHs, we conducted in situ rotation (by 8°, far above the critical angle of 5.3°) and directly identified the individual FeCo-MHs. The formation of FeCo-MHs could modulate the magnetic moments of the metal centers and increase the ratio of low-spin Fe(II)–N 4 moiety; thus the intrinsic activity could be optimized at the apex of the volcano-plot (a relationship as a function of magnetic moments of metal–phthalocyanine complexes and catalytic activities). The FeCo-MHs catalyst displays an exceptional ORR activity ( E 1/2 = 0.95 V) and could be used to construct high-performance cathodes for hydroxide exchange membrane fuel cells and zinc–air batteries.
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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 | 0.001 |
| 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".