Conductivity and Morphology Correlations of Ionic-Liquid/Lithium-Salt/Block Copolymer Nanostructured Hybrid Electrolytes
Bibliographic record
Abstract
The most daunting challenge in solid-state polymer electrolyte membranes (PEMs) is to achieve high ionic conductivity close to that of the liquid electrolytes, while maintaining enhanced thermal and mechanical performances. The ionic conductivity in relation to the morphology of PEMs composed of diblock copolymer (polystyrene- block -poly(ethylene oxide); PS- b -PEO), lithium salt (lithium trifluoromethanesulfonate; LiTf), and ionic liquid (1-ethyl-3-methylimidazolium trifluoromethanesulfonate; EMIMTf) is investigated. The optimized functional nanostructured PEMs are achieved with room-temperature ionic conductivities higher than a 1 mS cm –1 benchmark. The morphology of these microphase-separated electrolytes is composed of a major soft high ionic-conductive PEO/LiTf/IL matrix with minor glassy high-modulus PS nanodomains. The ionic-liquid upload in hybrid electrolytes inhibits the PEO crystallization, reduces the PEO glass transition temperature, promotes an extended PEO chain conformation, and enhances the solubilization of the non-dissociated lithium salt at the PS–PEO domain interfaces. These intrinsic properties caused by the ionic-liquid loading serve to achieve stable and robust nanostructured electrolyte membranes and can explain the achieved benchmark conductivity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".