New Concepts in Electrolytes
Bibliographic record
Abstract
Over the past decades, Li-ion battery (LIB) has turned into one of the most important advances in the history of technology due to its extensive and in-depth impact on our life. Its omnipresence in all electric vehicles, consumer electronics and electric grids relies on the precisely tuned electrochemical dynamics and interactions among the electrolytes and the diversified anode and cathode chemistries therein. With consumers' demand for battery performance ever increasing, more and more stringent requirements are being imposed upon the established equilibria among these LIB components, and it became clear that the state-of-the-art electrolyte systems could no longer sustain the desired technological trajectory. Driven by such gap, researchers started to explore more unconventional electrolyte systems. From superconcentrated solvent-in-salt electrolytes to solid-state electrolytes, the current research realm of novel electrolyte systems has grown to unprecedented levels. In this review, we will avoid discussions on current state-of-the-art electrolytes but instead focus exclusively on unconventional electrolyte systems that represent new concepts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".