Microwave Synthesis of Polymer-Embedded Pt−Ru Catalyst for Direct Methanol Fuel Cell
Bibliographic record
Abstract
Platinum-ruthenium nanoparticles stabilized within a conductive polymer matrix are prepared using microwave heating. Polypyrrole di(2-ethylhexyl) sulfosuccinate, or PPyDEHS, has been chosen for its known electrical conductivity, thermal stability, and solubility in polar organic solvents. A scalable and quick two-step process is proposed to fabricate alloyed nanoparticles dispersed in PPyDEHS. First a mixture of PPyDEHS and metallic precursors is heated in a microwave under reflux conditions. Then the nanoparticles are extracted by centrifugation. Physical characterization by TEM shows that crystalline and monodisperse alloyed nanoparticles with an average size of 2.8 nm are obtained. Diffraction data show that crystallite size is around 2.0 nm. Methanol electro-oxidation data allow us to propose these novel materials as potential candidates for direct methanol fuel cells (DMFC) application. The observed decrease in sulfur content in the polymer upon incorporation of PtRu nanoparticles may have adversely affected the measured catalytic activity by decreasing the conductivity of PPyDEHS. Higher concentration of polymer leads to lower catalyst activity. Design and synthesis of novel conductive polymers is needed at this point to enhance the catalytic properties of these hybrid materials.
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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 | 0.001 |
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".