Two-Step Dry Synthesis of Binderless 3D Low Pt-Loading Electrocatalysts for Direct Alkaline Methanol Fuel Cell Anodes
Bibliographic record
Abstract
Three-dimensional (3D) porous electrocatalysts of low platinum loading were synthesized by gas-phase pulsed laser ablation (PLA) and deposited on multiwalled carbon nanotubes (MWCNTs) directly grown on a stainless steel mesh current collector by catalyst-free chemical vapor deposition (Pt/MWCNT/SS). The performance of the developed electrocatalysts was evaluated for the methanol oxidation reaction (MOR). The PLA chamber pressure and ablation time were optimized to achieve the highest methanol oxidation current per Pt loading and electrochemically active surface area while maintaining structural stability. The most robust electrocatalyst, obtained with PLA at 10 –5 Torr for 5 min, exhibited a 50% higher methanol oxidation current compared to the commercial Pt/C with similar Pt loading. In addition, it showed the lowest loss of active sites after stability tests while maintaining its structural integrity. Increasing the electrolyte temperature from 0 to 80 °C significantly improved the methanol oxidation current on Pt/MWCNT/SS by 13 times compared to 5.8 times for Pt/C. Electrochemical impedance spectroscopy confirmed the faster kinetics of MOR and accelerated oxidation of adsorbed CO on the surface of the Pt/MWCNT/SS relative to the Pt/C.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".