Improved Air Stability of Sulfide Electrolytes for All-Solid-State Li Batteries
Bibliographic record
Abstract
Sulfide-based solid electrolytes (SEs) are receiving increasing attention due to their high ionic conductivities (up to 10-2 S cm-1 at room temperature) that can be comparable to the liquid electrolytes.1 However, the air stability of sulfide SEs is very poor.2, 3 Most developed sulfide SEs are prone to turn bad when exposed to the moisture. The generated H2S is dangerous, which places the commercialization of sulfide SEs into a challenging situation. 2, 3 In our work, to improve the air stability of sulfide SEs, we employed element substitution (Sn and Sb) for the problematic element (P) in conventional sulfide SEs (Li3PS4, Li6PS5I, Li10GeP2S12) based on the hard and soft acid and base theory (HSAB).4, 5, 6 Our results suggest that Sn and Sb-substituted sulfide SEs show significantly improved air stability compared with the pristine sulfides. Meanwhile, it is found that the Sn or Sb element substitution effectively enhance the ionic conductivity as well as Li metal compatibility in some cases. Various structural (e.g., X-ray diffraction, X-ray absorption near edge spectroscopy, solid-state nuclear magnetic resonance) and electrochemical characterizations are employed to identify the mechanism of the improvements are related to the Sn/Sb substitution-derived crystal structure, reinforced bonding energy, and the optimized electrode/electrolyte interfaces. Our studies provide a new idea of designing functional sulfide composition to realize improved air stability coupling with other essential properties. Re ferences N. Kamaya, R. Kanno*, et al. A lithium superionic conductor, Nat. Mater. 2011, 10, 682-686. C. Yu, F. Zhao, J. Luo, X. Sun*. Recent Development of lithium argyrodite solid-state electrolytes for solid-state batteries: synthesis, structure, stability and dynamics. Nano Energy 2021, 83, 105858. F. Zhao, S. Zhang, Y. Li*, X. Sun*. Emerging characterization techniques to understand electrode interfaces in all-solid-state lithium batteries. Small Struct. 2021, DOI: 10.1002/sstr.202100146. F. Zhao, J. Liang, X. Sun*, et al. A Versatile Sn-Substituted Argyrodite Sulfide Electrolyte for All-Solid-State Li Metal Batteries, Adv. Energy Mater. 2020, 10, 1903422. F. Zhao, X. Sun*, et al. An Air-Stable and Li-Metal-Compatible Glass-Ceramic Electrolyte enabling High-Performance All-Solid-State Li-Metal Batteries. Adv. Mater. 2021, 33, 2006577. J. Liang, X. Sun*, et al. Li10Ge(P1–xSbx)2S12 Lithium-Ion Conductors with Enhanced Atmospheric Stability, Chem. Mater. 2020, 32, 2664-2672.
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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 | 0.000 |
| 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".