<scp>High‐Performance Quasi‐Solid‐State</scp> Pouch Cells Enabled by in situ Solidification of a Novel Polymer Electrolyte
Bibliographic record
Abstract
Conventional lithium‐ion batteries (LIBs) with liquid electrolytes are challenged by their big safety concerns, particularly used in electric vehicles. All‐solid‐state batteries using solid‐state electrolytes have been proposed to significantly improve safety yet are impeded by poor interfacial solid–solid contact and fast interface degradation. As a compromising strategy, in situ solidification has been proposed in recent years to fabricate quasi‐solid‐state batteries, which have great advantages in constructing intimate interfaces and cost‐effective mass manufacturing. In this work, quasi‐solid‐state pouch cells with high loading electrodes (≥3 mAh cm−2) were fabricated via in situ solidification of poly(ethylene glycol)diacrylate‐based polymer electrolytes (PEGDA‐PEs). Both single‐layer and multilayer quasi‐solid‐state pouch cells (2.0 Ah) have demonstrated stable electrochemical performance over 500 cycles. The superb electrochemical stability is closely related to the formation of robust and compatible interphase, which successfully inhibits interfacial side reactions and prevents interfacial structural degradation. This work demonstrates that in situ solidification is a facile and cost‐effective approach to fabricate quasi‐solid‐state pouch cells with both excellent electrochemical performance and safety.
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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".