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Record W2146353398 · doi:10.1073/pnas.1508865112

Capillary-induced giant elastic dipoles in thin nematic films

2015· article· en· W2146353398 on OpenAlexaff
Haïfa Jeridi, Mohamed Amine Gharbi, Tahar Othman, Christophe Blanc

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2015
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsMcGill University
Fundersnot available
KeywordsLiquid crystalCapillary actionDipoleElasticity (physics)Materials scienceNanotechnologyChemical physicsThin filmTexture (cosmology)Colloidal particleColloidCondensed matter physicsComputer scienceChemistryPhysicsOptoelectronicsComposite materialPhysical chemistryArtificial intelligence

Abstract

fetched live from OpenAlex

Directed and true self-assembly mechanisms in nematic liquid crystal colloids rely on specific interactions between microparticles and the topological defects of the matrix. Most ordered structures formed in thin nematic cells are thus based on elastic multipoles consisting of a particle and nearby defects. Here, we report, for the first time to our knowledge, the existence of giant elastic dipoles arising from particles dispersed in free nematic liquid crystal films. We discuss the role of capillarity and film thickness on the dimensions of the dipoles and explain their main features with a simple 2D model. Coupling of capillarity with nematic elasticity could offer ways to tune finely the spatial organization of complex colloidal systems.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.085
GPT teacher head0.351
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2015
Admission routes1
Has abstractyes

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