Exploring properties of hyperbranched polymers in anion exchange membranes for fuel cells and its potential integration for water electrolysis: A review
Why this work is in the frame
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Bibliographic record
Abstract
The graphical abstract highlights the hyperbranched anion exchange membranes with linear, dendritic, and terminal units for efficient hydrogen production in water electrolysis. Anion-exchange membrane water electrolysers (AEMWEs) and fuel cells (AEMFCs) are critical technologies for converting renewable resources into green hydrogen (H 2 ), where anion-exchange membranes (AEMs) play a vital role in efficiently transporting hydroxide ions (OH − ) and minimizing fuel crossover, thus enhancing overall efficiency. While conventional AEMs with linear, side-chain, and block polymer architectures show promise through functionalization, their long-term performance remains a concern. To address this, hyperbranched polymers offer a promising alternative due to their three-dimensional structure, higher terminal functionality, and ease of functionalization. This unique architecture provides interconnected ion transport pathways, fractional free volume, and enhanced long-term stability in alkaline environments. Recent studies have achieved conductivities as high as 304.5 mS cm −1 , attributed to their improved fractional free volume and microphase separation in hyperbranched AEMs. This review explores the chemical, mechanical, and ionic properties of hyperbranched AEMs in AEMFCs and assesses their potential for application in AEMWEs. Strategies such as blending and structural functionalisation have significantly improved the properties by promoting microphase separation and increasing the density of cationic groups on the polymer surface. The review provides essential insights for future research, highlighting the challenges and opportunities in developing high-performance hyperbranched AEMs to advance hydrogen energy infrastructure.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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 it