Cost analysis for durable proton exchange membrane in PEM fuel cells
Bibliographic record
Abstract
Proton exchange membranes (PEMs) are a major determinant of fuel cell lifetime. For automotive applications, standards call for high levels of operation stability, reportedly 5,500 hours for cars and over 20,000 hours for buses. In addition to durability, membranes should also meet a certain price target for fuel cells to be competitive with incumbent gasoline and diesel internal combustion engines. A techno-economic analysis has been performed to explore different membrane designs which are proposed to enhance durability. For this reason, a cost analysis platform has been created. The technical-economic cost model (TCM) developed depicts how the production cost per unit varies depending on the different fabrication methods, production rate limitations, material selection, labor distribution, energy consumption, financial parameters and the target production volume. This platform enables the efficient exploration of each potential design solution and identification of the key factors for each design. By using such an approach in the design, research time and resources can be saved by prioritizing RD the effect of additive on the overall cost is minor especially when the production process is unchanged. Comparing the results to existing market standards, we found that current industry standard assumptions are intended for conservative investment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".