Beyond Organic Electrolytes: An Analysis of Ionic Liquids for Advanced Lithium Rechargeable Batteries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The fast-growing area of battery technology requires the availability of highly stable, energy-efficient batteries for everyday applications. This, in turn, calls for research into new battery materials, especially with regard to a battery’s main component: the electrolytes. Besides the demands associated with solid ionic conduction and appropriate electrochemical behaviour, considerable effort will be necessary to thoroughly reduce safety risks in terms of flammability, leakage, and thermal runaway. Consequently, completely new classes of electrolytes need to be developed that are compatible with energy storage systems. Despite the progress made in solid polymer electrolytes, such materials have suffered from limitations to their real-world application. Now, ionic liquids are considered a class of electrolytes with the most potential for the creation of more advanced and safer lithium–ion batteries. In recent decades, ILs have been widely explored as potential electrolytes in the search for new breakthroughs in the ESS field, such those associated with fuel cells, lithium–ion batteries, and supercapacitors. The present review will discuss ILs that present high ionic conductivity, a lower melting point below 100 °C, and which feature up to 5–6 V wide electrochemical potential windows vs. Li+/Li. Furthermore, ILs exhibit good thermal stability, non-flammability, and low volatility—all of which are attributes realized by appropriate cation–anion combinations. This paper seeks to review the status of research concerning ILs, along with the advantages and challenges yet to be overcome in their development.
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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 | 0.001 |
| 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) | 0.000 | 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 it