Paraffin Based Cathode–Electrolyte Interface for Highly Reversible Aqueous Zinc-Ion Battery
Bibliographic record
Abstract
In aqueous rechargeable zinc-ion batteries (ARZIBs), aqueous electrolytes tend to initiate structure changes of metal oxides and conductive agents of the electrode, which leads to rapid capacity degradation. In this work, we report an artificial cathode–electrolyte interface (CEI) composed of paraffin that provides a trade-off between Zn 2+ intercalation kinetics and stability of the cathode materials. Such paraffin-based CEI can either suppress Mn 2+ dissolution and hence stabilize MnO 2, or prevent water contact with conductive graphite to maintain its morphology and carbonaceous structure. As a result, the assembled aqueous Zn//MnO 2 and Zn//ZnMn 2 O 4 full battery with paraffin-based CEI delivered a superior capacity retention of 82% and 81% after 1000 cycles, 67% and 48% higher than the battery without CEI, respectively. More importantly, both Zn//MnO 2 and Zn//ZnMn 2 O 4 full battery also exhibit exceptional cycling stability even at a very high cathode mass loading of 23.6 and 25.2 mg cm –2, respectively, which offers an ideal capacity retention of 73% and 78% after 5000 cycles. Such a unique CEI design on the cathode surface provides a general strategy to improve the cycle life of ARZIBs.
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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 | 0.001 | 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".