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Record W2030281573 · doi:10.1021/cm047860p

Directed Metalation-Cross Coupling Route to Ferroelectric Liquid Crystals with a Chiral Fluorenol Core:  The Effect of Intermolecular Hydrogen Bonding on Polar Order

2005· article· en· W2030281573 on OpenAlexaff
J. Adam McCubbin, Xia Tong, Yue Zhao, Victor Snieckus, Robert P. Lemieux

Bibliographic record

VenueChemistry of Materials · 2005
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsQueen's UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsHydrogen bondIntermolecular forceMesogenDipoleChemistryFerroelectricityCrystallographyLiquid crystalPolarChemical physicsPhase (matter)Materials scienceMoleculeOrganic chemistryDielectricLiquid crystalline

Abstract

fetched live from OpenAlex

The chiral fluorenol mesogen ( R )-2-(1-octyloxy)-7-((4-undecyloxybenzoyl)oxy)fluoren-9-ol (( R )- 3 ) was synthesized using a combined directed metalation-cross coupling strategy. The SmC* liquid crystal phase formed by the fluorenol mesogen is more stable and has a wider temperature range than that formed by the fluorenone presursor, which may be ascribed to intermolecular hydrogen bonding. The spontaneous polarization ( P S ) of ( R )- 3 at 10 K below the SmC*-I phase transition temperature is −10.7 nC/cm 2 . Molecular modeling based on the Boulder model suggests that the intrinsic conformational bias favoring one orientation of the fluorenol dipole moment along the polar axis of the SmC* phase is very subtle and implies that self-assembly via hydrogen bonding may play a role in enhancing polar order. Results from FT-IR spectroscopy, dilution with achiral SmC additives, and deuterium exchange experiments suggest that the spontaneous polarization is enhanced by the formation of fluorenol dimers via OH−O C hydrogen bonding. Such self-assembly should increase the rotational order about the long molecular axis and, therefore, the orientational bias of the fluorenol transverse dipole moment along the polar axis that gives rise to P S .

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)0.001
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 score0.003
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.011
GPT teacher head0.288
Teacher spread0.277 · 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

Citations32
Published2005
Admission routes1
Has abstractyes

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