Is Fine‐Grained Simulation Able to Propose New Polyelectrolyte Membranes?
Bibliographic record
Abstract
Abstract An extensive understanding in the molecular motions that occur in Nafion® should lead to important development of improved proton exchange membrane for use in fuel cells (PEMFC). As water molecules are added in the system, changes within the Nafion® chain definitely take place. To visualize such a process, molecular dynamics is especially useful. Can information gained at this level of details be useful to propose new molecules, with ultimately better physical properties, such as higher proton conductivity? For this purpose, we first computed non‐bond parameters stemming from the study of the trifluorosufonic acid. They are inserted in the pcff force field. We then applied the procedure developed in our lab to extract the glass transition temperature of Nafion® with different water uptakes. The plasticization effect is first confirmed, fostering a molecular analysis. The particular behavior of the sulfur‐sulfur distance is revealed, guiding the design of new monomers.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".