Long‐life lithium batteries enabled by a pseudo‐oversaturated electrolyte
Bibliographic record
Abstract
Abstract The specific energy of Li metal batteries (LMBs) can be improved by using high‐voltage cathode materials; however, achieving long‐term stable cycling performance in the corresponding system is particularly challenging for the liquid electrolyte. Herein, a novel pseudo‐oversaturated electrolyte (POSE) is prepared by introducing 1,1,2,2‐tetrafluoroethyl‐2,2,3,3‐tetrafluoropropyl ether (TTE) to adjust the coordination structure between diglyme (G2) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). Surprisingly, although TTE shows little solubility to LiTFSI, the molar ratio between LiTFSI and G2 in the POSE can be increased to 1:1, which is much higher than that of the saturation state, 1:2.8. Simulation and experimental results prove that TTE promotes closer contact of the G2 molecular with Li+ in the POSE. Moreover, it also participates in the formation of electrolyte/electrode interphases. The electrolyte shows outstanding compatibility with both the Li metal anode and typical high‐voltage cathodes. Li||Li symmetric cells show a long life of more than 2000 h at 1 mA cm−2, 1 mAh cm−2. In the meantime, Li||LiNi0.8Co0.1Mn0.1O2 (NCM811) cell with the POSE shows a high reversible capacity of 134.8 mAh g−1 after 900 cycles at 4.5 V, 1 C rate. The concept of POSE can provide new insight into the Li+ solvation structure and in the design of advanced electrolytes for LMBs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".