Creating Vacancy Strong Interaction to Enable Homogeneous High‐Throughput Ion Transport for Efficient Solid‐State Lithium Batteries
Bibliographic record
Abstract
Abstract Solid polymer electrolytes are emerging as a key component for solid‐state lithium metal batteries, offering a promising combination of large‐scale processability and high safety. However, challenges remain, including limited ion transport and the unstable solid electrolyte interphase, which result in unsatisfactory ionic conductivity and uncontrollable lithium dendrite growth. To address these issues, a high‐throughput Li‐ion transport pathway is developed by incorporating tungsten sulfide enriched with sulfur vacancies (SVs) into a poly(vinylidene fluoride‐co‐hexafluoropropylene)‐based composite polymer electrolytes (CPEs). The SVs strong interaction in the CPEs facilitates homogeneous high‐throughput Li‐ion transport 1.9 × 10 −3 S cm −1 at 25 °C) by enhancing the dissociation of lithium salts and effectively creates ample interfaces with the polymer chains to reduce the formation of inner vacuities. Moreover, the SVs confine FSI − anions, while the electron‐rich environment induced by sulfur atoms promotes the preferential degradation of bis(trifluoromethanesulfonyl)imide anions, ensuring uniform lithium deposition. This fosters the formation of inorganic nanocrystals on the lithium anode and effectively suppresses dendrite growth, enabling an ultra‐long lifetime of over 5500 h in Li||Li symmetric cells. When paired with sulfurized polyacrylonitrile cathode, a pouch cell capacity of 0.524 Ah is achieved, demonstrating the effectiveness of a homogeneous, high‐throughput Li‐ions transport mechanism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".