Correlating Structure and Properties of Super‐Concentrated Electrolyte Solutions: <sup>17</sup>O NMR and Electrochemical Characterization
Bibliographic record
Abstract
Abstract Super‐concentrated electrolyte solutions are of increasing interest for safer and more stable lithium and post‐lithium batteries. The combination of 7Li and 17O (at natural abundance) nuclear magnetic resonance (NMR) and electrochemical characterization is proposed here as an effective approach to investigate the Li+ solvation structures and properties of electrolytes featuring tetraethylene glycol dimethyl ether (TEGDME) and lithium‐bis(trifluoromethane sulfonyl) imide (LiTFSI). Five different formulations from salt‐in‐solvent to solvent‐in‐salt with LiTFSI at different concentrations (0.1 m, 0.5 m, 2 m, 4 m, 5 m) are investigated. The NMR results, also supported by physico‐chemical characterizations such as thermal gravimetric analyses, differential scanning calorimetry, specific conductivity and viscosity, give information about the association of Li+ ions with anion and solvent molecules, allowing a deeper knowledge on the relationships among structure and functional properties of super‐concentrated solutions.
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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".