Multifunctional Polyol Electrolyte Design toward Long Lifespan Aqueous Zinc‐Ion Batteries
Bibliographic record
Abstract
Abstract Aqueous zinc batteries have garnered significant attention due to their inherent safety and low cost. However, its large‐scale application is still hindered by critical challenges such as interfacial corrosion, hydrogen evolution reactions, and the formation of by‐products. To address these issues, this study introduces polyol (2‐hydroxymethyl‐1,3‐propylene glycol)(2H13P) in ZnSO 4 electrolyte as solvation structure regulator, which not only regulates the Zn 2+ solvation structure to achieve rapid desolvation kinetics but also promotes the in situ formation of a dense zincophilic organic layer, effectively isolating the side reaction occurred on Zn anode. Consequently, the Zn‐based battery demonstrates exceptional reversibility, maintains a remarkably high CE of 99.7% after 700 cycles. Furthermore, the Zn||Zn symmetric cell achieves an impressive cycle life of 4700 h at a current density of 1 mA cm −2 and maintains stability for over 400 h with high depth of discharge of 42.47%. In addition, the 2H13P can effectively suppress polyiodide ion shuttling in Zn‐I 2 battery, enabling remarkable capacity retention of 96.0% over 12 000 cycles at 10 C and 94.5% over 48 000 cycles at 25 C. Additionally, the pouch cell demonstrates a decent lifespan of 300 cycles at 1 C, highlighting its unlimited potential for practical applications.
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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) | 0.001 | 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 | 0.001 |
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".