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Record W4220810675 · doi:10.1002/macp.202100418

Regulating Surface Topography of Liquid‐Crystalline Polymers by External Stimuli

2022· article· en· W4220810675 on OpenAlexaff
Yufan Ji, Bowen Yang, Feng Cai, Haifeng Yu

Bibliographic record

VenueMacromolecular Chemistry and Physics · 2022
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials and Mechanics
Canadian institutionsMinistry of Education and Child Care
FundersNational Natural Science Foundation of China
KeywordsPolymerNanotechnologyLiquid crystallineSurface (topology)Materials scienceAnisotropyAdhesionDeformation (meteorology)FabricationComputer sciencePhysicsComposite materialOptics

Abstract

fetched live from OpenAlex

Abstract Many polymer materials can respond to external stimuli, so their surface topographies can be regulated in order to achieve specific functions, such as fabrication of lens arrays, control of cell adhesion, and manipulation of object movement. Among them, liquid‐crystalline polymers are the most promising because their unique properties of self‐organization, molecular ordering, and physical anisotropy enable themselves to generate complicated deformation when external stimuli are applied. Here, this work focuses on the principle of topographical deformation of liquid‐crystalline polymers induced by various external stimuli, giving some examples about how to modulate these surface patterns. Accordingly, potential applications of switchable surface topography are presented in the field of photonics, biology, and mechanics. Finally, the existing problems are proposed and future directions in this topic are given an outlook. This review is anticipated to offer new insights and guidelines for developing stimuli‐responsive polymer materials with broader applications.

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 categoriesnone
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 score0.064
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.004
GPT teacher head0.193
Teacher spread0.189 · 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

Citations10
Published2022
Admission routes1
Has abstractyes

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