Controlling Crystallinity in Graft Ionomers, and Its Effect on Morphology, Water Sorption, and Proton Conductivity of Graft Ionomer Membranes
Bibliographic record
Abstract
To gain insight into the role of crystallinity and morphology on proton transport through solid polymer electrolytes, we synthesized graft copolymers, poly(vinylidene difluoride- co -chlorotrifluoroethylene)- g -polystyrene [P(VDF- co -CTFE)- g -PS], consisting of a hydrophobic, fluorous backbone and styrenic graft chain of varied length (DP styrene = 39, 62, and 79), by graft atom transfer radical polymerization (ATRP). The polystyrene graft chains were subsequently sulfonated to different degrees to provide three series of polymers with controlled ion exchange capacity (IEC). The crystallinity and morphology of solution-cast membranes were examined by XRD and TEM, respectively. The grafting of the parent side chain is found to hinder crystallization of the fluorous backbone and the impact of the degree of sulfonation of the side chain on the crystallinity of the polymer is dependent on the graft length: No impact is found for medium and long graft lengths, but for short graft length copolymers (PS 39 ), the degree of crystallinity in the sulfonated membranes is twice that of the unsulfonated membrane. A phase-separated morphology consisting of 2–5 (±1) nm ion-rich domains is observed for all of the graft copolymers. These graft copolymers allow access to very high IEC membranes (>3 mmol/g), which are insoluble in water. The shorter graft length series, P(VDF- co -CTFE)- g -SPS 39, swells less in the intermediate IEC range (<3.0 mmol/g) because of its higher degree of crystallinity and lower PS to VDF ratio, and provides membranes with exceptionally high proton conductivity. Two graft series possessing similar weight fraction of PS but different graft density were also examined in order to evaluate the effect of graft density. It was found that lower graft density copolymers possess higher crystallinity and more contiguous PVDF domains, which allow high IEC membranes to be prepared that swell to lower extents.
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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) | 0.000 | 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 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".