Bio-Derived Electrodes Based on a Vitamin K Cathode Material and a Mussel-Inspired Binder for Sustainable Aqueous Zinc-Ion Batteries
Bibliographic record
Abstract
Due to the higher volumetric capacity of Zinc (Zn) (5855 mAh cm –3 ), greater earth abundance, safer and more stable operation, aqueous Zn-ion batteries are a promising alternative to Lithium-ion batteries. Furthermore, using organic compounds as the components of Zn-ion batteries is an appealing option for developing low-cost and sustainable batteries. With this in mind, we describe the design and application of a novel polymer based on Vitamin K ( POxaVK ) (Q theo = 176 mAh g –1 ) as a cathode material for Zn-ion batteries. Due to the poor conductivity of the polymer, we sought to improve the performance of POxaVK by combining it with a bioderived mussel-inspired polymer binder, POxaD. POxaVK electrodes prepared with the POxaD binder result in improved specific capacities, capacity retentions, and decreased resistance compared to those prepared with the canonical binder, polyvinylidene fluoride (PVDF). For example, the POxaVK cathode material with the POxaD binder gives a higher reversible capacity (101 mAh g –1 for POxaD binder vs 45 mA h g –1 for PVDF binder), improved capacity retention (88% vs 56%) and better zinc-ion diffusion (1.56 × 10 –8 cm 2 s –1 vs 1.09 × 10 –9 cm 2 s –1 ). These achievements can be ascribed to the better binding ability of the dopamine moieties of POxaD, thus resulting in overall improved structural integrity and conductivity compared to PVDF. This work highlights the potential of Vitamin K electrodes combined with a bioderived binder for improved performance relative to fluorinated binders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".