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Record W1977572246 · doi:10.1063/1.1286962

Molecular dynamics in a mixture of 8OCB-d17 and 6OCB showing nematic and reentrant nematic phases: A deuterium nuclear magnetic resonance study

2000· article· en· W1977572246 on OpenAlexaff
Ronald Y. Dong, Ming Cheng

Bibliographic record

VenueThe Journal of Chemical Physics · 2000
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsBrandon UniversityUniversity of Manitoba
Fundersnot available
KeywordsLiquid crystalChemistryDeuteriumMolecular dynamicsRelaxation (psychology)Phase (matter)Zeeman effectMoleculeNuclear magnetic resonance spectroscopyCrystallographyNuclear magnetic resonanceComputational chemistryCondensed matter physicsMagnetic fieldStereochemistryOrganic chemistryPhysicsAtomic physics

Abstract

fetched live from OpenAlex

A deuteron NMR study of the molecular dynamics of 4-n-octyloxy-4′-cyanobiphenyl (8OCB) in the mixture of 72 wt % of 8OCB and 28 wt % of 4-n-hexyloxy-4′-cyanobiphenyl is presented. The mixture has the same composition as the one used before (Shen and Dong, 1998) except in the deuteration of the component molecule. The deuteron Zeeman and quadrupolar spin-lattice times and quadrupolar splittings were measured in the nematic, smectic A, and reentrant nematic phases at 15.1 and 46 MHz. The additive potential method was employed to construct the potential of mean torque based on the observed splittings. The spectral density data from the relaxation times were interpreted in terms of the internal conformational motions of the chain decoupled from the molecular small-step rotational diffusion and the order director fluctuations. The latter motion was found to be essential to the fit of experimental results in the nematic phase. The fitting parameters obtained using a global target fitting method are acceptable when compared with those obtained from other deuteron and proton NMR studies of the same mesophases.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.157
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.010
GPT teacher head0.265
Teacher spread0.255 · 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.

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

Citations15
Published2000
Admission routes1
Has abstractyes

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