Application of High Volume Manufacturing Practices to Fuel Cell Manufacturing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Polymer electrolyte membrane fuel cells (PEMFC) hold the promise of clean power generation in the future. PEMFC will be used in a wide spectrum of applications, such as transportation, back-up power for telecommunication, and portable applications such as laptop computers and cell phones. Most fuel cells are currently manufactured in low volumes, and on manual intensive production lines. These production lines create high costs and low uniformity, which leads to reduced quality and durability. Clearly prior to widespread commercialization there is a need to lower manufacturing costs with automation while improving uniformity and quality. This paper shall review several important fuel cell components and manufacturing processes for key elements such as the membrane, the Gas Diffusion Layer (GDL), and the application of the catalyst layer. Additionally, an investigation into the possibility of applying technologies currently in use in the electronics manufacturing industry to manufacture of these components shall be pursued. This work shall also focus on automated processes applicable for large scale manufacturing which should lead to the lowering of the cost of fuel cell stacks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it