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Record W3209004790 · doi:10.32920/ryerson.14649669.v1

A Computational Study of Structure Development and Texture Formation in Carbonaceous Mesophase Fibers

2021· preprint· en· W3209004790 on OpenAlexaff
Shujuan Hong

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldChemistry
TopicAdvanced Physical and Chemical Molecular Interactions
Canadian institutionsToronto Metropolitan UniversityDow Chemical (Canada)
Fundersnot available
KeywordsMesophaseDiscotic liquid crystalLiquid crystalTexture (cosmology)Materials scienceRelaxation (psychology)ThermalMoleculeQuenching (fluorescence)Composite materialExtrusionChemical physicsTransverse planeCondensed matter physicsThermodynamicsOpticsChemistryOrganic chemistryPhysicsOptoelectronics

Abstract

fetched live from OpenAlex

In this thesis, thermal relaxation phenomena after the melt-extrusion of a rigid discotic uniaxial nematic mesophase pitch were studied using mathematical modeling and computer simulation. The Eriksen and Landau-de Gennes continuum theories were used to investigate the structure development and texture formation across mesophase pitch based carbon fibers. It is found that during the thermal relaxation, discotic nematic molecules stored elastic free energy decays. The distorted nematic molecular profile reoriented to release the stored elastic free energy. The difference in time scales for molecular reorientation and thermal relaxation resulted in different transverse textures. The rate at which the fibers are cooled is the main factor in controlling the structure development. A slow cooling rate would permit nemiatic discotic molecules to reorient to a well developed (radial or onion) texture. The random texture is a result of rapid quenching. The numerical results are consistent with published experimental observations.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.599
Threshold uncertainty score0.613

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 science0.0000.000
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 head0.009
GPT teacher head0.260
Teacher spread0.251 · 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
Published2021
Admission routes1
Has abstractyes

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