Polysulfide Rejection Layer for High Performance Lithium Sulfur Batteries
Bibliographic record
Abstract
Polysulfide (PS) shuttle has been an impediment to the development of lithium-sulfur batteries with high capacity and cycling stability. Previous efforts to mitigate PS shuttle were mainly focused on 1) the suppression of diffusion of dissolved PS out of the cathode by geometrically trapping PS in porous carbons or adsorbing PS on oxides and conducting polymers and 2) protection of the Li anode from reaction with PS by forming a passivation layer on the Li metal surface or a hybrid anode structure. Here, we report a new strategy to remedy the problem using a polymeric polysulfide rejection layer via in situ or ex situ routes. The key concept of this strategy is to form a thin layer which selectively rejects PS anions but permeates lithium ion, mimicking cell membrane. The in situ formed PS rejection layer, which was developed on the sulfur cathode surface from an electrolyte additive during the first discharge, effectively prevented PS shuttle and consequently enhanced discharge capacity and cycling stability owing to an electrochemical equilibrium between the PS-containing cathode electrolyte and the PS rejection layer. In detail, the discharge capacity at the third cycle was 995 mAh g-1 for the cell with the in situ PS rejection layer and 829 mAh g-1 for the reference cell. At the 200th cycle, the PS rejection layer cell delivered a reversible 787 mAh g-1. In contrast, the discharge capacity of the reference cell dropped to 575 mAh g-1after 200 cycles, which was 73% of the discharge capacity of the cell with the PS rejection layer. Using the ex situ formed layer, which exhibited a similar polysulfide rejection behavior as the in situ layer did, the influence of chemical structure of the layer and battery architecture including the layer were investigated. Battery performances were highly dependent on the chemical nature and physical configuration of the layer. In particular, the layer inserted in the interface of cathode and bulk electrolyte phase improved reversible capacity, whereas, that in the interface of anode and bulk electrolyte phase increased cycling efficiency.
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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 | 0.000 | 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 | 0.001 |
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".