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Record W4313365333 · doi:10.1134/s0036024422130209

Influence of Methylene Blue on Optical and Thermal Properties of Dye-Doped Hydrogen-Bonded Liquid Crystal Mixture

2022· article· en· W4313365333 on OpenAlexaff
T. Vasanthi, V. Balasubramanian, S. Balamuralikrishnan, V. N. Vijayakumar

Bibliographic record

VenueRussian Journal of Physical Chemistry A · 2022
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsMethylene blueDopingThermalLiquid crystalMaterials scienceHydrogenMethyleneCrystal (programming language)Chemical engineeringChemistryOrganic chemistryOptoelectronicsThermodynamics

Abstract

fetched live from OpenAlex

Dye-doped hydrogen-bonded liquid crystals (HBLC) have been prepared using the ultrasonication method and are characterized to explore the optical and thermal properties. Polarizing optical microscopic (POM) analysis reveals the thermochromic effect in nematogen and smectogen of the mixtures. Thermal properties such as LC transition temperature, entropy, enthalpy, order transition, thermic stability, and phase width are analyzed using differential scanning calorimetric (DSC) studies. The noteworthy observation of (RGBY) color changes in nematogen and smectogen are observed in the Methylene Blue (MB) doped mesogens. It is noticed that the bandgap energy (Eg) value decreases substantially in the dye-doped HBLC mixture when compared to dye-doped LC. In addition to that quenching of different smectic phases into a single smectic C phase in the dye-doped HBLC is also reported. It is important to notice that the MB doped 4-dodecyloxy benzoic acid (12OBA) and diglycolic acid (DGA) comprised HBLC mixture exhibit thermochromic effect with extended mesophase width.

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)0.000
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 score0.009
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

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 science0.0010.000
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 head0.257
Teacher spread0.245 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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