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Record W4220660414 · doi:10.1002/mame.202100991

Liquid Crystalline Composite Stabilized by Epoxy Polymer with Boscage‐Like Morphology for Energy‐Efficient Smart Windows with High Stability

2022· article· en· W4220660414 on OpenAlexaff
Gang Chen, Junmei Hu, Jianjun Xu, Jian Sun, Jiumei Xiao, Lanying Zhang, Xiao Wang, Wei Hu, Huai Yang

Bibliographic record

VenueMacromolecular Materials and Engineering · 2022
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsMinistry of Education and Child Care
FundersNational Natural Science Foundation of China
KeywordsMaterials scienceEpoxyComposite numberSmart materialComposite materialPolymerAcrylateMonomer

Abstract

fetched live from OpenAlex

Abstract Smart windows, which can provide comfortable indoor conditions for cars or buildings and protect the privacy of people, have attracted much attention. Traditional acrylate‐based smart windows have the disadvantages of high energy consumption and poor stability. Herein, an energy‐efficient smart window based on a liquid crystalline composite stabilized by an epoxy polymer with boscage‐like morphology is reported. This epoxy polymer is prepared by cationic polymerization of the liquid crystalline epoxy monomer E6M in vertically oriented negative nematic liquid crystals. The orientation of the liquid crystals is controlled by the epoxy polymer, which makes the composite film transparent and switchable to scattering by an electric field. Therefore, the composite film can be used in an energy‐efficient reverse‐mode smart window. The reverse‐mode smart window has better cycling stability than does acrylate, owing to the better mechanical properties endowed by the polymer matrix with a unique morphology and high stress tolerance.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.006
GPT teacher head0.203
Teacher spread0.197 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

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