Simultaneously Blocking Chemical Crosstalk and Internal Short Circuit via Gel‐Stretching Derived Nanoporous Non‐Shrinkage Separator for Safe Lithium‐Ion Batteries
Bibliographic record
Abstract
Abstract The separator, an ionic permeable and electronic insulating membrane between cathode and anode, plays a crucial role in the electrochemical and safety performance of batteries. However, commercial polyolefin separators not only suffer from inevitable thermal shrinkage at elevated temperature, but also fail to inhibit the hidden chemical crosstalk of reactive gases such as O2, leading to often reported thermal runaway (TR) and hence preventing large‐scale implementation of high‐energy‐density lithium‐ion batteries. Herein, a nanoporous non‐shrinkage separator (GS‐PI) is fabricated via a novel gel‐stretching orientation approach to eliminate TR. In situ synchrotron small angle X‐ray scattering during heating clearly shows that the as‐prepared thin GS‐PI separator exhibits superior mechanical tolerance at high temperature, thus effectively preventing internal short circuit. Meanwhile, the unique nanoporous structure design further blocks chemical crosstalk and the associated exothermic reactions. Accelerating rate calorimetry tests reveal that the practical 1 Ah LiNi0.6Co0.2Mn0.2O2 (NCM622)/graphite pouch cell using GS‐PI nanoporous separator show a maximum temperature rise (dT/dtmax) of only 3.7 °C s−1 compared to 131.6 °C s−1 in the case of Al2O3@PE macroporous separator. Moreover, despite the reduced pore size, the GS‐PI separator demonstrates better cycling stability than conventional Al2O3@PE separator at high temperature without sacrificing specific capacity and rate capability.
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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".