A Review on Most Recent Development of Electrode Structures for Proton Exchange Membrane Fuel Cell Application with Upcoming Prospects
Bibliographic record
Abstract
To decarbonize the energy system, proton exchange membrane fuel cells (PEMFCs) have been proven to be the most viable device. Electrocatalysts used in the membrane electrode assembly (MEA) are vital parts facilitating the electrochemical reactions determining the overall performance of PEMFCs. The exposure of triple phase boundaries (TPBs) where these electrochemical reactions occurred is mostly dependent on electrode structure. Along with the promising aspects of PEMFCs, some issues regarding electrode durability, lower catalyst utilization, circuitous mass transport pathways in conventional electrodes are also raising concern. Unfortunately, half of the cost of a single cell is covered by electrocatalysts, which triggers the importance of its maximum utilization. The deployment of an innovative design in the electrode structure can eliminate those issues. Researchers have been trying to achieve higher power density and durability by modifying the architecture of the electrode introducing the different fabrication techniques. In this review, we attempted to illustrate current efforts to upgrade electrode architecture, highlighting the advanced design from macro-scale to nanoscale of electrode modification. The current status of the most common types of modified electrode structures, such as, template-based pattern, porous agglomerates, 3D ordered pattern, macropattern, micropattern, thin film, electrospinning, pore augmentation of the electrodes are discussed in details in this review. A brief description is also included to guide future R&D regarding the electrodes of PEMFCs. In addition, the functional mechanism of the modified electrode, fabrication routes, and comparative performance are also covered in detail. At the end, a summary of current research work is discussed with the aim of guiding future research prospects to upgrade electrodes for next generation PEMFC applications.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".