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Record W2023911004 · doi:10.1103/physreve.81.051706

Nematic biaxiality in a bent-core material

2010· article· en· W2023911004 on OpenAlexaff
Hyung Guen Yoon, Shin‐Woong Kang, Ronald Y. Dong, Alberto Marini, K. A. Suresh, Mohan Srinivasarao, Satyendra Kumar

Bibliographic record

VenuePhysical Review E · 2010
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsUniversity of British Columbia
FundersBasic Energy SciencesU.S. Department of Energy
KeywordsMesogenLiquid crystalCondensed matter physicsMaterials scienceOrder (exchange)Phase (matter)Bent molecular geometryPhase transitionCore (optical fiber)OpticsPhysicsCrystallographyLiquid crystallineChemistryQuantum mechanics

Abstract

fetched live from OpenAlex

The results of a recent investigation of the nematic biaxiality in a bent-core mesogen (A131) are in apparent disagreement with earlier claims. Samples of mesogen A131 used in the two studies were investigated with polarized optical microscopy, conoscopy, carbon-13 NMR, and crossover frequency measurements. The results demonstrate that textural changes associated with the growth of biaxial nematic order appear at ∼149 °C. The Maltese cross observed in the conoscopic figure gradually splits into two isogyres at lower temperatures indicating phase biaxiality. Presence of the uniaxial to biaxial nematic phase transition is further confirmed by temperature trends of local order parameters based on 13C chemical shifts in NMR experiments. Frequency switching measurements also clearly reveal a transition at 149 °C. Differences between the two reports appear to be related to the presence of solvent, impurities, and/or adsorbed gases in samples of A131 used in the study of Van Le [Phys. Rev. E 79, 030701 (2009)].

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 head0.045
GPT teacher head0.393
Teacher spread0.348 · 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

Citations51
Published2010
Admission routes1
Has abstractyes

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