Linking Local Ionic Conductivity, Microstructure, and Nanomechanical Properties to Bulk Performance for Enhanced Design of Solid Polymer Electrolytes
Bibliographic record
Abstract
Poly(ethylene oxide) (PEO)-based solid polymer electrolytes (SPEs) incorporating LiTFSI and LiClO 4 are widely studied, yet the impact of salt type on Li + ion transport and morphology remains poorly understood. Here, we use current-sensing atomic force microscopy (CS-AFM) to probe the Li + migration and nanomechanical properties in SPEs with varying salt loadings. Topological and ionic current mapping over 80 × 80 μm 2 under 0.5 V bias reveals that LiClO 4 induces rapid spherulitic growth, expelling salt and causing spatial heterogeneity in conductivity. In contrast, LiTFSI yields more homogeneous structures and conduction. Elemental and nanomechanical mapping confirms these patterns, showing distinct moduli and hardness between crystalline and amorphous regions in LiClO 4 -based SPEs, while LiTFSI-based systems remain more uniform. These spatial variations adversely affect electrode contact and long-term stability. Our findings highlight the importance of understanding multiscale ionic transport and morphology to guide the design of next-generation SPEs for solid-state batteries.
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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 | 0.001 |
| 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".