MétaCan
Menu
Back to cohort
Record W2149283045 · doi:10.1039/c3sm52034j

Dynamic wetting model for the isotropic-to-nematic transition over a flat substrate

2014· article· en· W2149283045 on OpenAlexafffund
Alejandro D. Rey, E. E. Herrera‐Valencia

Bibliographic record

VenueSoft Matter · 2014
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsMcGill University
FundersBasic Energy SciencesForeign Affairs and International Trade CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsWetting transitionWettingPhase transitionMaterials scienceContact angleIsotropyPhase (matter)Liquid crystalSupercoolingThermodynamicsMechanicsCondensed matter physicsOpticsChemistryComposite materialPhysics

Abstract

fetched live from OpenAlex

Phase ordering over solid substrates is a ubiquitous and important soft material transformation process whose description incorporates wetting, anchoring and phase transition kinetics. In this paper the kinetics of the isotropic-to-nematic isothermal phase transition over a flat solid surface in a growing spherical drop is analyzed based on the Landau-de Gennes Q-tensor order parameter equations. The model, based on a previously derived interface force balance and a newly derived contact line force balance, is shown to be consistent with the generic model of conservative interface and contact line motions. The advancing dynamic contact angle equation is extracted from kinematic compatibility between the moving isotropic-nematic interface and contact line. A tractable surface phase transition kinetic model obtained by focusing on the dominant phase transition and wetting driving forces yields: (i) the constant advancing dynamic contact angle θ, and (ii) the contact line speed as a function of undercooling ΔT. It is shown that as undercooling increases, the surface phase transition mode approaches the bulk phase transition mode, such that θ approaches π. The elastic and wetting parameters that control the phase transformation process are identified and experiments for their determination are defined. These dynamic wetting and surface phase transition results significantly expand existing characterization methods of LC-substrate interfaces based on static phase transition droplet methods.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.001

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 head0.016
GPT teacher head0.292
Teacher spread0.276 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueSoft MatterSame topicLiquid Crystal Research AdvancementsFrench-language works237,207