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Study on the Preparation of Mesophase Pitch from Modified Naphthenic Vacuum Residue by Direct Thermal Treatment

2016· article· en· W2394974900 on OpenAlexaff
Dong Liu, Bin Lou, Ming Li, Fengjiao Qu, Ran Yu, Yuanxi Yang, Chongchong Wu

Bibliographic record

VenueEnergy & Fuels · 2016
Typearticle
Languageen
FieldEngineering
TopicFiber-reinforced polymer composites
Canadian institutionsUniversity of Calgary
FundersNatural Science Foundation of Shandong ProvinceFundamental Research Funds for the Central UniversitiesMinistry of Education of the People's Republic of China
KeywordsMesophaseCarbonizationRaw materialThermal treatmentQuinolineChemical engineeringResidue (chemistry)Yield (engineering)Materials scienceOrganic chemistryCarbon fibersChemistryComposite material

Abstract

fetched live from OpenAlex

Two feedstocks (LPA and HPA) obtained from modification of naphthenic vacuum residues were selected to prepare mesophase pitch by direct thermal treatment. The influence of reaction temperature, soaking time, reaction pressure, and molecular structures of the feedstock on mesophase development was systematically investigated by analyzing variations in carbonization yield, carbon residue, quinoline insolubles (QI) content, density, optical textures, crystal structure, and surface morphology of derived products. It is found that the mesophase development and the properties of resultant mesophase products were closely related to the molecular structure of the original materials and preparation conditions. Compared with LPA, HPA was the preferable feedstock for thermal treatment because of its high degree of aromaticity and a large proportion of naphthenic carbon, and the resultant product obtained under the optimum conditions showed large flow domain mesophase, fewer alkyl side chains, and a high degree of molecular orientation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.014
GPT teacher head0.232
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations40
Published2016
Admission routes1
Has abstractyes

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