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Record W2557641984 · doi:10.1103/physreve.94.052704

Dynamics of disk pairs in a nematic liquid crystal

2016· article· en· W2557641984 on OpenAlexafffund
Alena Antipova, Colin Denniston

Bibliographic record

VenuePhysical review. E · 2016
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEquidistantLiquid crystalCondensed matter physicsMagnetic fieldPhysicsLattice Boltzmann methodsFerromagnetismDistortion (music)Rotating magnetic fieldMaterials scienceOpticsMechanicsGeometryOptoelectronics

Abstract

fetched live from OpenAlex

We use a hybrid lattice Boltzmann method to study the behavior of sets of ferromagnetic colloidal disks in a nematic liquid crystal. When a weak rotating magnetic field acts on the system, the disks rotate following the magnetic field. This leads to a distortion in the liquid crystal that drives translational motion of the disks. If the concentration of disks is high, disks get locked together: a stable chain configuration is created, where each disk lays on the nearest neighbor. For intermediate concentrations of disks, a different behavior is observed. When disks are rotated by the magnetic field by more than 90^{∘} from their initial orientation, the distortion in the liquid crystal leads to a simultaneous flip of both disks. The final disk positions depends only weakly on the initial configuration. Consecutive rotations of magnetic field push disks towards an equidistant configuration. Periodicity of the systems studied and analysis of the flipping motion of a single disk imply that one can use weak rotating magnetic fields to create stable crystal structures of disks.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.352
Teacher spread0.332 · 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

Citations6
Published2016
Admission routes2
Has abstractyes

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