Electrochemistry and transport properties of electrolytes modified with ferrocene redox-active ionic liquid additives
Bibliographic record
Abstract
Used in their pure, undiluted form, ionic liquids usually result in Li-ion battery electrolytes with inadequate performance due low Li + transport numbers (t Li+ ). Alternatively, they can be used as additives dissolved in carbonates to maintain a high t Li+ while providing the electrolyte with additional properties such as resistance to combustion, current collector passivation, and decreased Li dendritic growth. Additional properties can be imparted to the ionic liquid via the modification of their structure. Ionic liquids modified with electroactive moieties such as ferrocene (Fc-IL) can be used as an additive in Li-ion battery (LiB) electrolytes to prevent cathode over-oxidation via the redox shuttle mechanism. The aim of the present work is to evaluate the properties of LiB electrolytes modified with such Fc-IL at different concentrations. At low concentrations (0.3–0.5 mol/L), the redox-active ionic liquid behaves as expected for a redox shuttle. We show that at 1 mol/L, however, the redox ionic liquid yields a different discharge behavior after the overcharging step, providing an increase in discharge capacity. This behavior is linked to the deposition of the ferrocenium-IL at the positive electrode. Such electrolyte is non-flammable and is highly efficient to achieve shuttling of excess charge. Based on this principle, it is expected that novel ionic liquids can be designed for development of other types of additives and contribute to developing safer battery electrolytes. As a part of this commemorative issue, this contribution highlights the type of collaborative research currently being done on energy storage devices at the Department of Chemistry at the Université de Montréal.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".