Synthesis and Characterization of 20% Pt-Fe/C Alloy as a Cathode Catalyst for Oxygen Reduction Reaction PEMFCs
Bibliographic record
Abstract
Proton exchange membrane fuel cells (PEMFCs) are highly efficient and non-polluting electrical power generators based on two electrochemical reactions. Therefore, PEMFCs are considered to be alternative electricity sources for electric vehicles, portable applications and stationary power systems due to their high power density and eco-friendly environment. However, PEMFCs are associated with many problems for their commercialization such as the high price of electrode catalyst and the slow rate of oxygen reduction reaction (ORR). In this study, two different reducing agents NaBH4 and HCHO were used in the synthesis of carbon supported Pt-Fe catalysts (Pt-Fe/C-HCHO and Pt-Fe/C-NaBH4). Both catalysts were characterized using x-ray diffraction (XRD), transmission electron microscopy (TEM) and cyclic voltametry in the range 0.05 -1.2 V vs. SHE. It was observed that reducing agent HCHO is more effective than NaBH4. In order to reduce amount of platinum, the 20% Pt-Fe/C catalyst was prepared by using Fe. The catalysts were heat treated up to 600 °C for improve the activity and stability. It was found that a temperature of 500 °C yielded the best catalyst morphology and ORR activity at 0.9 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".