Multiwall Carbon Nanotube-Based Microporous Layers for Polymer Electrolyte Membrane Fuel Cells
Bibliographic record
Abstract
The presence of multiwall carbon nanotubes (MWCNTs) corresponded to a dispersion of carbon black particles in the microporous layer (MPL) of the polymer electrolyte membrane (PEM) fuel cell. The gas diffusion layer (GDL) with a MWCNT-based MPL exhibited larger pores and a higher porosity compared to a conventional GDL, and less MPL intrusion into the GDL substrate was observed with the MWCNTs-based MPL. The GDLs were evaluated in operando in a fuel cell that was customized for concurrent liquid water visualization (synchrotron X-ray radiography) and electrochemical characterization. The MWCNT-based fuel cell exhibited higher power densities and lower mass transport resistances compared to the fuel cell with the conventional GDL; however, a higher liquid water saturation was observed for the MWCNT-based GDL. Although the liquid water saturation in the MWCNT-based GDL was higher, its higher effective porosity led to superior performance compared to the conventional fuel cell. The use of the MWCNTs-based MPL resulted in improved oxygen transport in the fuel cell, particularly at high current densities.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".