Highly porous cellulose acetate separators for zinc-ion batteries
Bibliographic record
Abstract
With the growing interest in aqueous zinc-ion batteries (ZIBs), it is important to address the challenges they face, such as Zn dendrite formation, capacity fade, and side reactions. Many approaches are under development to mitigate these challenges, including design of Zn anodes, Zn regulation through electrolyte additives, and separator fabrication. In this work, a free standing cellulose acetate (CA) separator film was prepared using pore forming agents, as an alternative to traditional separators made from non-woven fibres. The porosity of CA films is adjustable by using different solvents, non-solvents, and plasticisers as pore-forming agents, including water, acetone, and glycerol. Solvents that evaporate at room temperature during wet casting with a doctor blade eliminated the need for further processing. This method resulted in highly porous films with tunable thickness. The CA-3 separator is about 6 times thinner than traditional glass fibre separators (100 µm vs. 600 µm) and can be bent, rolled, or compressed without damage after soaking in the electrolyte, making it a potential alternative separator for ZIBs. Preliminary full cell testing demonstrated their ability to retain almost 70% of the initial capacity after 170 h, although further processing and structural refinement is required to improve the overall capacity.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".