MétaCan
Menu
Back to cohort
Record W1534397826 · doi:10.1002/mrc.4101

NMR of guest‐host systems: 8CB in chiral nematic porous glasses

2014· article· en· W1534397826 on OpenAlexafffund
Alan P. Manning, Michael Giese, Andrea S. Terpstra, Mark J. MacLachlan, Wadood Y. Hamad, Ronald Y. Dong, Carl A. Michal

Bibliographic record

VenueMagnetic Resonance in Chemistry · 2014
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsFPInnovationsUniversity of British Columbia
FundersMedical Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsLiquid crystalChemistryMesoporous materialChemical physicsMesoporous silicaIsotropyPulsed field gradientProton NMRCrystallographyMaterials scienceOrganic chemistryMoleculeOptoelectronicsOpticsPhysics

Abstract

fetched live from OpenAlex

Liquid crystals confined to porous materials often have different critical phenomena and ordering than in the bulk. Through the selection of pore size, structure and guest liquid crystal, these systems could enable a variety of functional materials for applications such as sensors and displays. A recent example of such a system is chiral nematic mesoporous films infiltrated with liquid crystal 4-cyano-4'-n-octylbiphenyl (8CB), which has reversible thermal switching of its optical bandgap. The optical bandgap is lost when the ordered 8CB guests are heated above ∼50 °C, where the 8CB becomes isotropic. In this study, we have used NMR cryoporometry and pulsed-field gradient diffusion measurements to determine the pore sizes and structures of various chiral nematic mesoporous silica and organosilica films. Temperature and orientation-dependent wideline (15)N NMR spectra of films infiltrated with (15)N-labelled 8CB guests show that the ordering of the 8CB mesogens is consistent with an average orientation parallel to the chiral nematic pore axes. Inclusion of a large, orientation-dependent shift was necessary to fit the spectra, probably due to susceptibility differences between the 8CB guests and the organosilica host.

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 score0.045
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueMagnetic Resonance in ChemistrySame topicLiquid Crystal Research AdvancementsFrench-language works237,207