A 2023 update on the performance of ionic-liquid proton-exchange-membrane fuel cells
Bibliographic record
Abstract
A mini-review is provided of the literature concerning the performance of proton-exchange-membrane fuel cells (PEMFCs) containing (immobilized) ionic liquids as possible electrolytes, focusing on papers reporting performance metrics (power and current densities). For over a decade, and especially for combined heat and power applications, there has been a drive to design an ionic-liquid-holding membrane that could operate well under non-humidifying (water-free) conditions above 100°C. Such a goal has not yet been achieved: reported power densities are still below those of traditional low-temperature fuel cells. Other recent reviews have already pointed to three main issues: poor conductivity, poor cathode (oxygen-reduction) kinetics, and seepage of the liquid from the membrane. In this review, IL-PEMFCs are grouped into three IL classes (protic, aprotic, and polymerized), performance metric data are summarized, the cases producing the top ten peak power densities of the last 5 years are discussed, and the conductivity mechanisms of the leading cases are elucidated. Purely vehicular protic ILs appear to be too slow, and the trend toward enhanced Grotthuss H+ relays via polymerized ILs is revealed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.009 |
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".