Nanocasting SiO2 into metal–organic frameworks imparts dual protection to high-loading Fe single-atom electrocatalysts
Bibliographic record
Abstract
Abstract Single-atom catalysts (SACs) have sparked broad interest recently while the low metal loading poses a big challenge for further applications. Herein, a dual protection strategy has been developed to give high-content SACs by nanocasting SiO 2 into porphyrinic metal–organic frameworks (MOFs). The pyrolysis of SiO 2 @MOF composite affords single-atom Fe implanted N-doped porous carbon (Fe SA –N–C) with high Fe loading (3.46 wt%). The spatial isolation of Fe atoms centered in porphyrin linkers of MOF sets the first protective barrier to inhibit the Fe agglomeration during pyrolysis. The SiO 2 in MOF provides additional protection by creating thermally stable FeN 4 /SiO 2 interfaces. Thanks to the high-density Fe SA sites, Fe SA –N–C demonstrates excellent oxygen reduction performance in both alkaline and acidic medias. Meanwhile, Fe SA –N–C also exhibits encouraging performance in proton exchange membrane fuel cell, demonstrating great potential for practical application. More far-reaching, this work grants a general synthetic methodology toward high-content SACs (such as Fe SA , Co SA , Ni SA ).
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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) | 0.001 | 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 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".