Transport/kinetic limitations and efficiency losses
Bibliographic record
Abstract
Abstract The following contribution explores many of the fundamental aspects of the direct methanol fuel cell (DMFC). In particular, the electrochemical and physical processes that occur in the unit cell and the techniques used to study these phenomena are discussed. This information leads to a clearer picture of the breakdown and relative importance of the various contributions to the overall efficiency loss in a DMFC. The short introduction provides a brief perspective on the historical development of the DMFC and compares the present day performance to the conventional hydrogen/air fuel cell. A discussion of some of the analytical tools used to study the DMFC and probe the various processes, particularly under automotive operating conditions, follows. Techniques such as a.c. impedance spectroscopy under operating load conditions and gas chromatography for measuring methanol and carbon dioxide crossover, will be discussed in detail. The unit cell processes that typically dominate the performance characteristics of a DMFC under automotive operating conditions include: kinetic limitations at the anode and to a lesser extent at the cathode, mass transport limitations at the cathode and methanol and water crossover through the membrane from the anode to the cathode. By quantifying the various cell processes occurring by considering the overall mass flow and material balance, a more complete quantitative picture of the performance limitations of the DMFC expressed in terms of the relative contributions of the efficiency losses can be formulated. The contributions of the anode and cathode to the total efficiency losses are roughly comparable, unlike hydrogen/air fuel cells. Finally, in conclusion, this contribution will summarize some of the key findings and provide an outlook to the future.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".