Combined NMR and molecular dynamics modeling study of transport properties in sulfonamide based deep eutectic lithium electrolytes: LiTFSI based binary systems
Bibliographic record
Abstract
The trend toward Li-ion batteries operating at increased (>4.3 V vs. Li/Li(+)) voltages requires the development of novel classes of lithium electrolytes with electrochemical stability windows exceeding those of LiPF6/carbonate electrolyte solutions. Several new classes of electrolytes have been synthesized and investigated over the past decade, in the search for LIB electrolytes with improved properties (increased hydrolytic stability, improved thermal abuse tolerance, higher oxidation voltages, etc.) compared with the present state-of-the-art LiPF6 and organic carbonates-based formulations. Among these are deep eutectic electrolytes (DEEs), which share many beneficial characteristics with ionic liquids, such as low vapor pressure and large electrochemical stability windows, with the added advantage of a significantly higher lithium transference number. The present work presents the pulsed field gradient NMR characterization of the transport properties (diffusion coefficients and cation transport numbers) of binary DEEs consisting of a sulfonamide solvent and lithium bis(trifluoromethanesulfonyl)imide salt. Insights into the structural and dynamical properties, which enable one to rationalize the observed ionic conductivity behavior were obtained from a combination of NMR data and MD simulations. The insights thus gained should assist the formulation of novel DEEs with improved properties for LIB applications.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".