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Record W4417024913 · doi:10.1080/00084433.2025.2598968

Highly porous cellulose acetate separators for zinc-ion batteries

2025· article· en· W4417024913 on OpenAlexafffund
Brian D. Adams, Douglas G. Ivey

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvanced battery technologies research
Canadian institutionsUniversity of Alberta
FundersMitacs
KeywordsPorosityCellulose acetateCelluloseAqueous solution

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.250
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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