Degradation modelling and the impact of intermittent operation on proton exchange membrane electrolyzers
Bibliographic record
Abstract
This paper investigates membrane thinning with fluoride release rate as the indicator for chemical degradation in PEM electrolyzers when coupled with intermittent energy sources. Continuous and intermittent operating scenarios are modelled to predict and compare chemical degradation over long-term operation. Predicted degradation is less for continuous operation (with a rate of 2.69 nm h −1 ), whereas intermittent operation increases the predicted degradation rate to 5.86 nm h −1 . Four distinct intermittency patterns over a 48-h period are also investigated, highlighting the role of downtime and scheduling on degradation. Results indicate that differences in cumulative degradation are primarily determined by the length and sequencing of OFF periods. The results provide insights into operational strategies, indicating that accounting for electrolyzer performance degradation in operational planning can mitigate degradation and improve performance in intermittent renewable energy applications. • Predictions over the operational life of a PEM electrolyzer with intermittent use. • Intermittent operation is significant for membrane degradation. • Intermittent operation causes non-linear membrane degradation. • Irregular cycling can increase predicted membrane thinning.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".