Development of Hydroxide-Stable Anion-Conducting Functional Groups
Bibliographic record
Abstract
Immobilized benzimidazolium cations as functional groups in anion exchange polymers can be used in alkaline anion exchange membrane fuel cells (AAEM-FCs), electrolyzers, or water purification systems, but are prone to hydroxide attack. Steric protection by proximal methyl groups has been shown to drastically increase hydroxide stability (A. Wright, S. Holdcroft ACS Macro Lett. 2014, 3, 444-447.). To further improve stability, model compounds, representing the ion exchange sites of AAEMs, were investigated for their hydroxide stability. By means of density functional theory (DFT), we studied degradation mechanisms, such as de-methylating SN2 reaction of methylated benzimidazolium cations with hydroxide ions and the attack of hydroxide on the C2 position of the benzimidazolium. Some of these results have also been compared to experimental stability tests of model compounds and polymers (A. G. Wright, T. Weissbach, S. Holdcroft Angew. Chem. Int. Ed. 2016, 55, 4818-4821.). The findings of this study enable the design of new materials for AAEM-FCs.
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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) | 0.000 | 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) | 0.001 | 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".