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Record W4413970909 · doi:10.1039/d5mh00912j

Electro-switchable cellulose nanocrystal films with chiroptical properties

2025· article· en· W4413970909 on OpenAlexafffund
Yota Neagari, Miguel A. Soto, Yinghao Zhang, Zongzhe Li, Carl A. Michal, Mark J. MacLachlan

Bibliographic record

VenueMaterials Horizons · 2025
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
FundersFPInnovationsBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaCanada Research ChairsCanada Foundation for Innovation
KeywordsNanocrystalMaterials scienceCelluloseNanotechnologyChemical engineering

Abstract

fetched live from OpenAlex

A series of stable electro-switchable cellulose nanocrystal (CNC) films is fabricated by the covalent functionalization of preassembled chiral nematic CNC substrates with electro-active molecules. Through this approach, we anchor siloxy-group-containing viologens (SV) to the surface of CNCs in a preformed film. Unlike conventional premixing strategies that typically disrupt chiral self-assembly of CNCs, this method produces films that retain the structural color and chiroptical properties of the chiral nematic CNC substrate, while exhibiting stable electrochromic performance. Our films show responses not only to voltage but also to light, heat and alkaline environments, demonstrating their potential as multi-responsive materials. This methodology extends beyond chiral nematic CNCs to other nanostructured substrates such as mesoporous chiral nematic silica. The resulting materials show potential for smart optical applications, including dynamic information display and security technologies, enabling tunable visibility and encryption/decryption technologies.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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 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

Citations4
Published2025
Admission routes2
Has abstractyes

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