Competitive Coordination Structure Regulation in Deep Eutectic Electrolyte for Stable Zinc Batteries
Bibliographic record
Abstract
Abstract Rechargeable zinc‐based batteries are finding their niche in energy storage applications where cost, safety, scalability matter, yet they are plagued by rapid performance degradation due to the lack of suitable electrolytes to stabilize Zn anode. Herein, we report a competitive coordination structure to form unique quaternary hydrated eutectic electrolyte with ligand‐cation‐anion cluster. Unraveled by experiment and calculation results, the competing component can enter initial primary coordination shell of Zn2+ ion, partially substituting Lewis basic eutectic ligands and reinforcing cation‐anion interaction. The hydration‐deficient complexes induced between competing eutectic as hydrogen bond donor‐accepter and water also broaden the electrochemical window and confine free water activity. The altered coordination further leads to robust hybrid organic‐inorganic enriched solid electrolyte interphase, enabling passivated surface and suppressed dendrite growth. Noticeably, stable Zn plating/stripping for 8000 cycles with high Coulombic efficiencies of 99.6 % and long cycling life of 10000 cycles for Zn‐organic batteries are obtained. Even under harsh conditions (small N/P ratio, low temperature), the profits brought by the competitive eutectic electrolyte are still very prominent. This design principle leveraged by eutectic electrolytes with competitive coordination offers a new approach to improve battery performance.
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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 | 0.001 |
| 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".