Nano-Scale Transport Phenomena and Thermal Effect of the PEMFC Electrolyte
Bibliographic record
Abstract
This paper employed molecular dynamics (MD) simulation to investigate the transport phenomena and thermal effect at nano-scale inside fuel cell electrolyte. The material of the electrolyte was chosen to be Nafion® which is the most commonly used material for proton exchange membrane fuel cell (PEMFC). The transport of protons inside the electrolyte is one of the major issues that influencing the fuel cell performance. The structure of the Nafion® includes carbon-fluorine back bones and side chains (with SO3− attached at the end). Simulation results show that the transport of protons was confined to some specific regions. These specific regions (hydrophilic phase region) consist of water molecules, protons and sulfonated acid groups. Different hydration levels (3, 61.25, 9 and 15.375 H2O/SO3−) was also studied to test the sensitivity of the electrolyte water content on proton conduction. Higher water content shows greater proton mobility due to the larger water cluster size and more water clusters. The influence of the temperatures (333K, 343K and 353K) on proton mobility was due to different sizes of hydrophilic phase regions. Diffusion coefficients at various operation conditions were also evaluated and showed satisfactory agreement with the published experimental data.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".