Suppression of Dendrite Formation and Corrosion on Zinc Anode of Secondary Aqueous Batteries
Bibliographic record
Abstract
Novel zinc anodes are synthesized via electroplating with organic additives in the plating solution. The selected organic additives are cetyltrimethylammonium bromide (CTAB), sodium dodecyl sulfate (SDS), polyethylene-glycol (PEG-8000), and thiourea (TU). The synthesized zinc anode materials, namely, Zn-CTAB, Zn-SDS, Zn-PEG, and Zn-TU, are characterized by powder X-ray diffraction and scanning electron microscopy. The results show that each additive produces distinctively different crystallographic orientation and surface texture. The surface electrochemical activity is characterized by linear polarization when the zinc is in contact with the battery's electrolyte. Tafel fitting on the linear polarization data reveals that the synthetic zinc materials using organic additives all exhibit 6-30 times lower corrosion currents. When using Zn-SDS as the anode in the rechargeable hybrid aqueous battery, the float current decreases as much as 2.5 times. The batteries with Zn-SDS, Zn-PEG, and Zn-TU anodes display the capacity retention of 79%, 76%, and 80% after 1000 cycles of charge-discharge at 4C rate, whereas only 67% obtained from the batteries using the anode prepared from commercial zinc foil. Among these electroplated anodes, Zn-SDS is the most suitable for aqueous batteries thanks to its low corrosion rate, low dendrite formation, low float current, and high capacity retention after 1000 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) | 0.000 | 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".