Impact of Pre-Exchanging Anion-Exchange Polymer for Water Electrolysis and Fuel Cell Applications
Bibliographic record
Abstract
Pretreatment of anion-exchange membranes (AEMs) prior to their use in AEM fuel cells (AEMFCs) and AEM water electrolyzers (AEMWEs) is typically required to replace the anions with hydroxide (OH – ). Herein, hexamethyl- p -terphenyl poly(benzimidazolium) iodide (HMT-PMBI) (I – ) was used as a model AEM to investigate the exchange process. The exchanging solution (containing I –, released from AEMs) was first examined by silver ions, where we found that no more precipitates can be visually observed after 3 exchanges. Moreover, we developed a quantitative method based on UV–vis spectroscopy, which is able to show that ∼61, 84, and 87% of the original I – was removed after 1, 2, and 3 exchanges in 3 M KOH. In operando electrochemical studies revealed that current–voltage characteristics of AEMFCs are sensitive to residual iodide within the membrane, requiring at least three exchange cycles (>90% removal of iodide) to reach maximum performance. In contrast, AEMWEs are less sensitive to the exchange process, with trace iodide being effectively flushed during electrolysis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".