Impact of cell design and conditioning on polymer electrolyte membrane water electrolyzer operation
Bibliographic record
Abstract
Integration of polymer electrolyte membrane water electrolyzers (PEMWEs) for clean hydrogen generation requires a robust understanding of the impact cell designs and conditioning protocols have on operation and stability. Here, catalyst-coated electrode and catalyst-coated membrane cells employing Pt/C cathode catalyst layer , an IrO 2 anode catalyst layer, with a platinized titanium mesh or a carbon paper with a microporous layer as the porous transport layer were developed. The impact of cell conditioning above and below 0.25 A cm −2 was investigated using advanced electrochemical impedance spectroscopy analyses and microscopic imaging, with the electrochemical response related to physicochemical processes. Operation below 0.25 A cm −2 prior to operation above 0.25 A cm −2 resulted in anode corrosion and titanium cation contamination, increasing the cell voltage at 1 A cm −2 by 200 mV compared to uncontaminated cells. Conditioning above 0.25 A cm −2 led to non-negligible hydrogen transport resistances due to cathode flooding that resulted in a ca. 50 mV contribution at 1 A cm −2 and convoluted with the anode impedance response. The presence of a microporous layer increased catalyst utilization but increased the cell voltage by 300 mV at 1 A cm −2 due to increased anodic mass transport resistances. These results yield critical insights into the impact of PEMWE cell design and operation on corresponding cell performance and stability while highlighting the need for application dependent standardized operating protocols and operational windows.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".