Designing Electrodes with No Ionomers: A Perspective on Ionomer-Free Electrodes for Proton-Exchange-Membrane Water Electrolyzers
Bibliographic record
Abstract
Proton-exchange-membrane water electrolyzer (PEMWE) is a promising technology for producing clean hydrogen as it offers high current operation, compact design, and ability to operate with intermittent renewable energy. However, high costs related to platinum group metal (PGM) usage and titanium components pose a bottleneck in further scale-up of PEMWEs. This perspective introduces an ionomer-free PEMWE system as a viable approach to facilitate scale-up and cost reduction of PEMWEs. In conventional PEMWEs, ionomers serve as binders for the electrodes as well as a medium to conduct protons. However, most ionomers used in PEMWEs rely on perfluoroalkyl and polyfluoroalkyl substances, which complicate the manufacturing processes of the catalyst layers and cause a potential concern to the environment. Shifting to ionomer-free electrodes alleviates these challenges and simplifies scale-up processes; however, the application of ionomer-free electrodes remains at an early stage of research, and this perspective provides a guidance on the future direction based on previous research endeavors conducted in the field.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".