Silica-based Composite Membranes for Methanol Fuel Cells Operating at High Temperature
Bibliographic record
Abstract
In this work, composite membranes were prepared from a mixture of Nafion® ionomer with mesoporous (SBA-15) and microstructured silica (SiO2). The silica-based materials were synthesized using the sol-gel technique and their properties were characterized by TEM, BET, SEM and XRD. A glass cell with two chambers was used to evaluate the permeability of methanol of the composite membranes and its performance was compared with a commercial Nafion 115 membrane. The composite membranes showed smaller value of methanol permeability (around 19%) than that obtained when was used a commercial membrane. In terms of the fuel cell performance, the composite membranes showed a larger maximum power density (62 and 29 mWcm-2 for the SiO2 and SBA-15 composite membrane respectively) than that obtained for the commercial membrane at high temperature conditions (100°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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".