Unveiling the autocatalytic growth of Li2S crystals at the solid-liquid interface in lithium-sulfur batteries
Bibliographic record
Abstract
Electrocatalysts are extensively employed to suppress the shuttling effect in lithium-sulfur (Li-S) batteries. However, it remains challenging to probe the sulfur redox reactions and mechanism at the electrocatalyst/LiPS interface after the active sites are covered by the solid discharge products Li2S/Li2S2. Here, we demonstrate the intrinsic autocatalytic activity of the Li2S (100) plane towards lithium polysulfides on single-atom nickel (SANi) electrocatalysts. Guided by theoretical models and experimental data, it is concluded that LiPS dissociates into Li2S2 and short-chain LiPS on the Li2S (100) plane. Subsequently, Li2S2 undergoes further lithiation to Li2S on the Li2S (100) surface, generating a new Li2S (100) layer, thus enabling the autocatalytic formation of a new Li2S (100) surface. Benefiting from the autocatalytic growth of Li2S, the concentration of LiPS in the electrolyte remains at a lower level, enabling Li-S batteries under high loading and low electrolyte conditions to exhibit superior electrochemical performance. This study reveals the autocatalytic growth of Li2S crystals at the solid-liquid interface in lithium-sulfur batteries enabling good electrochemical performance under high loading and low electrolyte conditions.
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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".