Sustainable Substitutes for Fluorinated Electrolytes in Electrochemical Capacitors
Bibliographic record
Abstract
Nowadays, researchers are working hard to design and developmethods to store electricity for the future demands of zero-emission energy production methods and transportation. Many efforts have been made to improve the safety of portable electronic devices. In this regard, many researchers have studied different materials to develop non-flammable electrolytes for electrochemical double-layer capacitors (EDLC) and lithium-ion batteries (LIBs), which power electronic devices. The need to develop efficient and fire-safe energy storage devices has led to the widespread use of fluorinated electrolytes as a substitute for ionic liquid-based electrolytes. Although fluorinated electrolytes have many advantages over other electrolytes, their widespread usage created new challenges, especially environmental problems. Thus, the electrolytes of devices that store electricity are widely studied. Since lithium-ion batteries contain fluorinated organic compounds, many studies have focused on them. Thus, in this chapter, fluorinated electrolytes and their advantages and disadvantages will be overviewed, and at the end, environment-friendly and fluorine-free alternatives to fluorinated electrolytes will be discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".