Evolution of Frustrated Coordination in Eutectic Electrolyte Driven by Ligand Asymmetry toward High‐Performance Zinc Batteries
Bibliographic record
Abstract
Abstract Eutectic electrolytes hold promise for aqueous zinc metal batteries in sustainable energy storage chemistries, yet improvement from perspective of molecule configurational engineering are ambiguous. Herein, we propose design strategy of increasing asymmetric molecular geometry in organic ligands to regulate frustrated coordination and disordered structure for eutectic electrolytes toward enhanced zinc metal batteries. The introduced asymmetry in eutectic component gives rise to relatively weak coordination strength and configurational disorder interaction among cation‐anion‐ligand, leading to suppressed local aggregation, steady eutectic phase and improved Zn 2+ diffusion kinetics. Such highly frustrated coordination state also enables disruption of hydrogen bonding network and reinforcement of anion participation, which results in confined side reactions, decreased water activity and the formation of inorganic‐enriched solid electrolyte interphase. In comparison to highly symmetric ligands, asymmetric ligand‐involved eutectic electrolytes with configurational disorder deliver high Coulombic efficiency of 99.4 %, stabilized Zn plating/stripping of 5000 h and impressive rate capability even under harsh conditions such as small N/P, low temperature. The rationale in this work advances the deep understanding of asymmetric molecular engineering in eutectic electrolytes and showcases suitability of frustrated coordination to achieve high‐performance zinc metal batteries.
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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 | 0.000 |
| 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".