Electrode Interface Engineering of Hydrophilic and Zincophilic Bifunctionality for High‐Efficiency and Low‐Polarization Zn Anodes
Bibliographic record
Abstract
Abstract Aqueous rechargeable Zn batteries offer a promising technological route as a safe and low‐cost energy storage system for grid energy storage. However, major challenges of Zn dendrites and parasitic side reactions upon cycling in aqueous environments remain unsolved. Here, a design of a bifunctional electrode interface consisting of heterostructured zinc hydroxide chloride (ZHC) and Cu, as well as their synergy in promoting high‐efficiency and low‐polarization Zn deposition is reported. Hydrophilic/zincophobic ZHC promotes the desolvation of hydrated Zn2+ prior to Zn nucleation, meanwhile adjacent Cu acts as a zincophilic site for subsequent nucleation and deposition. Consequently, the reduction polarization of Zn2+ at the bifunctional layer (ZHC‐Cu) features ten times lower nucleation overpotential of 3 mV than bare Zn. Meanwhile, the water‐induced hydrogen evolution side reactions on Zn are significantly hindered by the bifunctionality of the electrode interface. Accordingly, the ZHC‐Cu@Zn symmetric cells exhibit a superior cycling stability for over 3500 cycles at 10 mA cm−2/3 mAh cm−2. The ZHC‐Cu@Zn full‐cell with MnO2 cathode can stably operate for low C‐rate cycling with a high average Coulombic efficiency of 99.5% over 600 cycles. This work provides an effective approach to rational design of heterostructured bifunctional electrode interfaces to obtain high‐efficiency and low‐polarization Zn anodes.
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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) | 0.000 | 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".