A True Non-Newtonian Electrolyte for Rechargeable Hybrid Aqueous Battery
Bibliographic record
Abstract
The rechargeable aqueous hybrid battery is a unique system in which the Li-ion mechanism dominates the cathode while the first-order metal reaction of stripping/depositing regulates the anode. This battery inherits the advantages of the low-cost anode while possessing the capability of the Li-ion cathode. One of the major challenges is to design a proper electrolyte to nourish such strengths and alleviate the downsides, because two different mechanisms are functioning separately at the node–electrolyte and the cathode–electrolyte interfaces. In this work, we design a non-Newtonian electrolyte which offers many advantages for a Zn/LiMn2O4 battery. The corrosion is kept low while almost non-dendritic zinc deposition is confirmed by chronoamperometry and ex situ microscopy. The gel strength and gelling duration of such non-Newtonian electrolytes can be controlled. The ionic conductivity of such gels can reach 60 mS⋅cm−1. The battery exhibits reduced self-discharge, 6–10% higher specific discharge capacity than the aqueous reference battery, high rate capability, nearly 80% capacity retention after 1000 cycles, and about 100 mAh⋅g−1 of specific discharge capacity at cycle No. 1000th. Negligible amorphization on the cathode surface and no passivation on the anode surface are observed after 1000 cycles, evidenced by X-ray diffraction and scanning electron microscopy on the post-run battery electrodes.
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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".