Aqueous Zinc‐Based Batteries: Active Materials, Device Design, and Future Perspectives
Bibliographic record
Abstract
Abstract Aqueous zinc‐based batteries (AZBs) are emerging as a compelling candidate for large‐scale energy storage systems due to their cost‐effectiveness, environmental friendliness, and inherent safety. The design and development of high‐performance AZBs have thus been the focus of considerable study efforts; yet, certain properties of electrode materials and electrolytes still limit their development. Here, a comprehensive overview and evaluation of the current progress, existing limitations, and potential solutions for electrode materials to achieve long‐cycle stability and fast kinetics in AZBs is provided. Detailed analyses of the structural design, electrochemical behavior, and zinc‐ion storage mechanisms of various materials are presented. Additionally, key issues and research directions related to the design of zinc anodes and the selection of electrolytes are systematically discussed to guide the future design of AZBs with superior electrochemical performance. Finally, this review provides a comprehensive outlook on the future development of AZBs, highlighting key challenges and opportunities, to foster their continued rapid advancement and broader practical applications in the field.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".