Non-precious electrocatalysts synthesized from metal–organic frameworks
Bibliographic record
Abstract
Proton exchange membrane fuel cells (PEMFCs) are considered as clean and efficient energy conversion devices with great potential to replace currently used internal combustion engines (ICEs) in the near future. Developing high-performance and less expensive non-precious metal electrocatalysts for oxygen reduction reaction (ORR) at the cathode side is crucial for widespread application of PEMFCs. Herein an Fe-containing metal–organic framework (MOF) was employed as the sole precursor for preparing a cathode electrocatalyst. The Fe-MOF was synthesized and subsequently subjected to thermolysis under a non-reactive gas atmosphere followed by acid leaching and heat treatment under NH3 at different temperatures between 700 and 1000 °C. Upon pyrolysis, iron–nitrogen containing carbon active sites (Fe/N/C) were formed in parallel with development of an electronically conductive carbon medium produced through pyrolytic carbonization of the organic component of the MOF material. The prepared electrocatalysts were characterized by XRD, N2 physisorption, TEM and XPS. In a H2SO4 (pH = 1) electrolyte, the ORR onset potential of 0.915 V, and the half-wave potential of 0.811 V are achieved using the most promising electrocatalyst (C700/950). The membrane electrode assemblies (MEAs) made of these electrocatalysts were also tested as a cathode in a H2/air single fuel cell. The most promising electrocatalyst (C700/950) demonstrated an open circuit voltage of 0.945 V and a maximum power density of 0.302 W cm−2 reached at 0.391 V.
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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".