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Record W2030327346 · doi:10.1080/02678292.2011.628703

Chiral induction in thioester and oxoester liquid crystals by dispersed carbon nanotubes

2011· article· en· W2030327346 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLiquid Crystals · 2011
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaSwinburne University of TechnologyU.S. Department of Energy
KeywordsLiquid crystalThioesterMaterials scienceCarbon nanotubeChirality (physics)MoleculeCrystallographyNanotechnologyChemical physicsOrganic chemistryChemistryPhysicsOptoelectronicsChiral symmetry

Abstract

fetched live from OpenAlex

Abstract Multi-walled carbon nanotubes were dispersed at low concentrations into various achiral liquid crystals having either a thioester or oxoester linkage group in the core. The presence of the carbon nanotubes resulted in chiral signatures being observed in the liquid crystals, including an electroclinic effect (a rotation of the liquid crystal director perpendicular to, and linear in, an applied electric field) in both the nematic and smectic A phases, and a macroscopic helical twist of the liquid crystal director in the nematic phase. For both experiments the chiral signatures for the thioester liquid crystals were found to be an order of magnitude larger than those of the oxoesters. We speculate that the much larger strength of the thioester's chiral properties is a result of stronger non-covalent interactions between the liquid crystal molecule and carbon nanotube. Keywords: chiral inductionestercarbon nanotubetwistelectroclinic Acknowledgements The authors are grateful to Dr Michael D. Wand for useful conversations and to Professor Peter Collings for the LC. RB and CR were supported by the US Department of Energy under grant DE-FG02-01ER45934 and RPL by a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada.

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.

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)0.001
metaresearch head score (Gemma)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.027
GPT teacher head0.269
Teacher spread0.242 · 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