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Record W2087916752 · doi:10.1103/physreve.77.031702

High-resolution x-ray study of nematic–smectic-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>A</mml:mi></mml:math>and smectic-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mi>A</mml:mi></mml:math>–reentrant-nematic transitions in liquid-crystal–aerosil gels

2008· article· en· W2087916752 on OpenAlexaff
M. Ramazanoglu, Sophie LaRochelle, C. W. Garland, R. J. Birgeneau

Bibliographic record

VenuePhysical Review E · 2008
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsMcMaster UniversityUniversity of Toronto
FundersU.S. Department of Energy
KeywordsMathematicsAlgorithm

Abstract

fetched live from OpenAlex

We have studied the effects of quenched random disorder created by dispersed aerosil nanoparticle gels on the nematic to smectic- A (N- SmA ) and smectic- A to reentrant nematic ( SmA -RN) phase transitions of thermotropic liquid-crystal mixtures of hexyloxycyanobiphenyl (6OCB) and octyloxycyanobiphenyl (8OCB). These effects are probed using high-resolution synchrotron x-ray diffraction techniques. We find that the reentrant characteristics of the system are largely unchanged by the presence of the aerosil gel network. By comparing measurements of the smectic static structure amplitude for this 8OCB- 6OCB+aerosil system with those for butyloxybenzilidene-octylaniline (4O.8)+aerosil gels, we find that the short-range smectic order in the smectic- A phase is significantly weaker in the reentrant system. This result is consistent with the behavior seen in pure 8OCB-6OCB mixtures. The strength of the smectic ordering decreases progressively as the 6OCB concentration is increased. Detailed line shape analysis shows that the high- and low-temperature nematic phases (N and RN) are similar to each other.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.958
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.025
GPT teacher head0.283
Teacher spread0.257 · 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 designSimulation or modeling
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

Citations12
Published2008
Admission routes1
Has abstractyes

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