Dendrite Suppression in Zn Batteries through a Heteroepitaxial Residual Stress Shield
Bibliographic record
Abstract
Dendrite formation is a long-standing problem for the commercial application of aqueous zinc ion batteries (AZIBs). Here, we investigate the effect of heteroepitaxial residual stresses due to layered coatings on dendrite suppression. We found that atomic and molecular layered coatings can substantially reduce dendritic growth in AZIBs by providing shielding due to residual stresses, even at a single layer or a few layers of coatings. Through a combined experimental and numerical approach, we demonstrate that the residual stresses developed due to the coating of the Zn anodes significantly reduced the chemical potential polarization around dendrite embryos, forcing the deposition of zinc in the regions adjacent to the protuberances. This, in turn, results in a slower rate of dendritic growth and, eventually, dendrite suppression. The fundamental understanding of the effect of residual stresses due to coatings demonstrated herein can be extended to various metal anode batteries, such as Li or Na.
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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".