Physical and Electrochemical Properties of Some Phosphonium-Based Ionic Liquids and the Performance of Their Electrolytes in Lithium-Ion Batteries
Bibliographic record
Abstract
In this work, three ionic liquids with two different cations and two different anions: trimethyl propyl phosphonium bis-fluorosulfonyl imide (P 1113 FSI), trimethyl isobutyl phosphonium bis-fluorosulfonyl imide (P 111 i 4 FSI) and trimethyl isobutyl phosphonium bis-trifluoromethylsulfonyl imide (P 111 i 4 TFSI) have been characterized and evaluated as electrolytes in lithium ion half-cells. It is found that ionic liquids with FSI − anion have superior properties over their TFSI − counterparts and those with the smaller cation, P 1113 , have better conductivity and viscosity. The two ionic liquids with FSI anion, P 1113 FSI and P 111 i 4 FSI, are liquid at room temperature and show high conductivities and low viscosities, reaching 10.0 mS/cm and 30 cP at room temperature for P 1113 FSI. They also exhibit electrochemical windows higher than 5 V and thermal stability exceeding 300°C. Mixing the ionic liquids with 0.5 M LiPF 6 increases viscosities, lowers conductivities but improves electrochemical cathodic stability. The electrolyte mixtures have been evaluated in graphite/Li half cells, Li/LiFePO 4 and Li/LiMn 1.5 Ni 0.5 O 4 at C/12 for 100 cycles and at different rates: C/6, C/3, C and 2C for rate capabilities. Battery testing shows that unlike their TFSI − counterparts both ionic liquids with FSI − anion perform well with graphite anode and LiFePO 4 cathode but fail with the higher voltage LiMn 1.5 Ni 0.5 O 4 cathode.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".