Manipulating Li2S2/Li2S mixed discharge products of all-solid-state lithium sulfur batteries for improved cycle life
Bibliographic record
Abstract
Abstract All-solid-state lithium-sulfur batteries offer a compelling opportunity for next-generation energy storage, due to their high theoretical energy density, low cost, and improved safety. However, their widespread adoption is hindered by an inadequate understanding of their discharge products. Using X-ray absorption spectroscopy and time-of-flight secondary ion mass spectrometry, we reveal that the discharge product of all-solid-state lithium-sulfur batteries is not solely composed of Li2S, but rather consists of a mixture of Li2S and Li2S2. Employing this insight, we propose an integrated strategy that: (1) manipulates the lower cutoff potential to promote a Li2S2-dominant discharge product and (2) incorporates a trace amount of solid-state catalyst (LiI) into the S composite electrode. This approach leads to all-solid-state cells with a Li-In alloy negative electrode that deliver a reversible capacity of 979.6 mAh g−1 for 1500 cycles at 2.0 A g−1 at 25 °C. Our findings provide crucial insights into the discharge products of all-solid-state lithium-sulfur batteries and may offer a feasible approach to enhance their overall performance.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".