Directing the Lithium–Sulfur Reaction Pathway via Sparingly Solvating Electrolytes for High Energy Density Batteries
Bibliographic record
Abstract
The lithium-sulfur battery has long been seen as a potential next generation battery chemistry for electric vehicles owing to the high theoretical specific energy and low cost of sulfur. However, even state-of-the-art lithium-sulfur batteries suffer from short lifetimes due to the migration of highly soluble polysulfide intermediates and exhibit less than desired energy density due to the required excess electrolyte. The use of sparingly solvating electrolytes in lithium-sulfur batteries is a promising approach to decouple electrolyte quantity from reaction mechanism, thus creating a pathway toward high energy density that deviates from the current catholyte approach. Herein, we demonstrate that sparingly solvating electrolytes based on compact, polar molecules with a 2:1 ratio of a functional group to lithium salt can fundamentally redirect the lithium-sulfur reaction pathway by inhibiting the traditional mechanism that is based on fully solvated intermediates. In contrast to the standard catholyte sulfur electrochemistry, sparingly solvating electrolytes promote intermediate- and short-chain polysulfide formation during the first third of discharge, before disproportionation results in crystalline lithium sulfide and a restricted fraction of soluble polysulfides which are further reduced during the remaining discharge. Moreover, operation at intermediate temperatures ca. 50 °C allows for minimal overpotentials and high utilization of sulfur at practical rates. This discovery opens the door to a new wave of scientific inquiry based on modifying the electrolyte local structure to tune and control the reaction pathway of many precipitation-dissolution chemistries, lithium-sulfur and beyond.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".