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Record W4414984946 · doi:10.1038/s41467-025-64061-2

Cellulose-mediated ionic liquid crystallization enables tough-stiff switchable ionogels

2025· article· en· W4414984946 on OpenAlexafffund
Siheng Wang, Huayu Liu, Zhengyang Yu, Xinle Ren, Qi Hua, Mahyar Panahi‐Sarmad, Pu Yang, Chuhang Liu, Scott Renneckar, He Liu, Feng Jiang

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
FundersChina Scholarship CouncilGovernment of Jiangsu ProvinceCanada Research Chairs
KeywordsCrystallizationIonic liquidToughnessModulusPolymerSolventIonic bondingPhase (matter)

Abstract

fetched live from OpenAlex

Nature has inspired to fabricate mechanically switchable materials for applications in various aspects, which is, however, unique but challenging to achieve reversible phase transitions using common ionic liquids in ionogels with ambient temperature-triggered crystallization feature. Here, we develop a tough-stiff switchable ionogel through a reversible solvent crystallization design. Cellulose acts as a chemical regulator, competitively binding with polymers to promote the formation of ionic liquid crystals. This results in a tough ionogel with a bulk toughness of 25.7 MJ m−3 and a fracture toughness of 47.1 kJ m−2, which can switch into a stiff ionogel with a tensile modulus of 134.6 MPa and a compressive modulus of 48.9 MPa. Upon heating, the crystallized ionogel reverts to its unconfined as ionic liquid crystals melt. This phase-driven structural and rigidity transition enables dynamical programming, with rapid, reversible and repeatable shape recovery through heating. Our study demonstrates solvent crystallization in ionogels, offering a strategy for creating intelligent, reconfigurable, and performance-switchable materials with customizable functions. Current ionic liquid-based switchable ionogels rely on fluorinated chemicals and require cooling to low temperatures to induce crystallization. Here, the authors use an ionic liquid to create a cellulose containing ionogel with tough-stiff switchable properties through a reversible room temperature crystallization process.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.019
GPT teacher head0.318
Teacher spread0.299 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations15
Published2025
Admission routes2
Has abstractyes

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