Interfacial Engineering of Amorphous TiO <sub>2</sub> Coatings for Dendrite-Free and Highly Reversible Zinc Metal Anodes
Bibliographic record
Abstract
The commercialization of aqueous zinc-ion batteries (AZIBs) is limited by uncontrollable dendrite growth and interfacial side reactions. To tackle this critical issue, we propose a surface engineering strategy involving the deposition of a zincophilic amorphous titanium dioxide (AS-TiO 2 ) protective layer onto the zinc anode. The resulting Zn@AS-TiO 2 anode demonstrates remarkable electrochemical performance, achieving exceptional cycling stability over 3750 h at 1 mA cm –2 while maintaining near-ideal Coulombic efficiency (99.5%) and outstanding deposition/stripping reversibility. Mechanistic studies reveal that the enhanced performance primarily stems from the significantly higher binding energy of Zn adsorption on amorphous TiO 2 compared to those on crystalline TiO 2 and bare Zn, which endows the Zn@AS-TiO 2 anode with superior zincophilicity and substantially reduces the Zn 2+ nucleation overpotential. In addition, the amorphous structure facilitates a more homogeneous electric field distribution at the electrode–electrolyte interface, effectively regulating Zn 2+ flux and promoting uniform Zn deposition. As a result, dendrite formation is efficiently suppressed even during prolonged cycling. This interface modification strategy, which integrates zincophilic surface engineering with electric field regulation, offers valuable mechanistic insights into dendrite suppression and presents a promising pathway for the development of durable metal anodes in next-generation aqueous energy storage systems.
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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".