Biologically Inspired Highly Durable Iron Phthalocyanine Catalysts for Oxygen Reduction Reaction in Polymer Electrolyte Membrane Fuel Cells
Bibliographic record
Abstract
In the present work, we have designed and synthesized a new highly durable iron phtalocyanine based nonprecious oxygen reduction reaction (ORR) catalyst (Fe-SPc) for polymer electrolyte membrane fuel cells (PEMFCs). The Fe-SPc, with a novel structure inspired by that of naturally occurring oxygen activation catalysts, is prepared by a nonpyrolyzing method, allowing adequate control of the atomic structure and surface properties of the material. Significantly improved ORR stability of the Fe-SPc is observed compared with the commercial Fe-Pc catalysts. The Fe-SPc has similar activity to that of the commercial Fe-Pc initially, while the Fe-SPc displays 4.6 times higher current density than that of the commercial Fe-Pc after 10 sweep potential cycles, and a current density that is 7.4 times higher after 100 cycles. This has been attributed to the incorporation of electron-donating functional groups, along with a high degree of steric hindrance maintaining active site isolation. Nonprecious Fe-SPc is promising as a potential alternative ORR electrocatalyst for PEMFCs.
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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) | 0.000 | 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 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".