MétaCan
Menu
Back to cohort
Record W2332791988 · doi:10.1021/jp5011605

New Insights into the Thermal Stability of the Smectic C Phase

2014· article· en· W2332791988 on OpenAlexafffund
François Porzio, Etienne Levert, Richard Vadnais, Armand Soldera

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2014
Typearticle
Languageen
FieldMaterials Science
TopicLiquid Crystal Research Advancements
Canadian institutionsUniversité de Sherbrooke
FundersCompute Canada
KeywordsMesophasePhase (matter)Chemical physicsMoleculeMaterials scienceFerroelectricityRange (aeronautics)Thermal stabilityAtmospheric temperature rangePhase diagramMolecular dynamicsLiquid crystalCrystallographyNanotechnologyChemistryThermodynamicsComputational chemistryPhysicsOrganic chemistryOptoelectronicsComposite material

Abstract

fetched live from OpenAlex

Subtle differences in the molecular structure of mesogens can lead to very different experimental polymorphisms. The smectic C (SmC) phase can actually be exhibited by one isomer and not the other, or the range of temperature can be completely different. Unveiling the deep connection between atomic structure and the very existence of the SmC phase will lead to the design of new performing liquid crystalline materials for ferroelectric or nonlinear optical applications. Our approach is based on running molecular dynamics simulation from an initial SmC arrangement of molecules. When the temperature is increased, the molecules automatically adjust in a more favorable organization. Such modification in the imposed initial self-assembly is governed by values of the nonbonded energies. Thanks to the combined use of simulation and experimental phase diagrams, we have unveiled part of the deep connection between atomic structure and the very existence of the SmC phase. The actual display of the SmC mesophase stems from a subtle balance between short-range interactions, which reveal arrangement of molecules within a smectic layer, and long-range interactions, which disclose organization of layers.

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 score0.005
Threshold uncertainty score0.254

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 head0.017
GPT teacher head0.306
Teacher spread0.289 · 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

Citations8
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry BSame topicLiquid Crystal Research AdvancementsFrench-language works237,207