Adjusting Interface Dynamics: A New Insight into the Role of Electrolyte Additive in Facilitating Highly Reversible (002)‐Textured Zinc Anode at High Current and Areal Densities
Bibliographic record
Abstract
Abstract Facilitating (002)‐textured zinc growth is crucial for achieving dendrite‐free zinc deposition in zinc‐ion batteries. Electrolyte engineering holds promise in directing zinc electrodeposition toward this desired orientation. However, despite the (002) plane's lower surface energy compared to other facets, it remains unclear why this plane does not dominate zinc crystal faces during electrodeposition under normal conditions. This knowledge gap underscores the need to better understand zinc electrodeposition behaviors and the influence of electrolyte compositions on its crystallographic texture. This study explores different tetraazamacrocycle derivatives as electrolyte additives. It reveals that achieving (002)‐textured zinc deposition is not solely dictated by thermodynamic equilibrium but also significantly influenced by interface dynamics. In typical ZnSO4 electrolytes, imbalanced kinetics among reduction, ion diffusion, and adatom diffusion processes lead to electroconvection and disorderly zinc accumulation, hindering proper zinc growth. In contrast, introducing specific tetraazamacrocycle derivative in the electrolyte regulates reduction rate, enhances limiting current density, and expedites adatom diffusion, mitigating hydrodynamic instability and dendrite growth. This regulation restores the thermodynamically favorable flat (002)‐textured zinc deposition, extending the zinc anode's lifespan to 1800 h at 5 mA cm−2 and 5 mAh cm−2, enabling the fabrication of a high‐performance zinc ion hybrid capacitor prototype capable of stable operation for 40 000 cycles.
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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".