A rational synthesis of hierarchically porous, N-doped carbon from Mg-based MOFs: understanding the link between nitrogen content and oxygen reduction electrocatalysis
Bibliographic record
Abstract
Controlled mixtures of novel Mg-based metal-organic frameworks (MOFs) were prepared, with H(+) or K(+) as counterions. A linear relation was found between synthesis pH and K/H ratio in the resultant mixture, establishing the tunability of the synthesis. Upon pyrolysis, these precursor mixtures yield nitrogen-doped, hierarchically porous carbons, which have good activity towards the oxygen reduction reaction (ORR) at pH 13. The nitrogen content varies significantly along the homologous carbon series (>400%, 1.3 at% to 5.7 at%), to a much greater extent than microstructural parameters such as surface area and graphitization. This allows us to isolate the positive correlation between nitrogen content and electrocatalytic oxygen reduction ORR activity in this class of metal-free, N-doped, porous carbons.
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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) | 0.001 | 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 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".