3D-printed fuel-cell bipolar plates for evaluating flow-field performance
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 In the last decade, many researchers have focused on developing fuel-cell flow-field designs that homogeneously distribute reactants with an optimum pressure drop. Most of the previous studies are numerical simulations and the few experimental studies conducted have used very simple flow-field geometries due to the limitations of the conventional fabrication techniques. 3D printing is an excellent rapid prototyping method for prototyping bipolar plates (BPPs) to perform experiments on new flow-field designs. The present research investigates the applicability of different 3D-printed BPPs for studying fluid-dynamic behaviour. State-of-the-art flow-field designs are fabricated using PolyJet 3D printing, stereolithographic apparatus (SLA) 3D printing and laser-cutter technologies, and the pressure-drop and velocity profiles are measured for each plate. The results demonstrate that SLA BPPs have great promise in serving as a screening tool in modifying flow-field design with a small feature size.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it