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Record W2033760971 · doi:10.1021/ie049055q

Carbonaceous Material Deposition from Heavy Hydrocarbon Vapors. 1. Experimental Investigation

2005· article· en· W2033760971 on OpenAlexafffund
Wenxing Zhang, A. P. Watkinson

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2005
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of British Columbia
FundersSyncrudeNatural Sciences and Engineering Research Council of CanadaMcKnight Foundation
KeywordsHydrocarbonDeposition (geology)AsphaltCokeChemical vapor depositionCondensationCoker unitAsphalteneChemical engineeringChemistryMaterials scienceMetallurgyOrganic chemistryComposite materialGeology

Abstract

fetched live from OpenAlex

The unwanted deposition of carbonaceous layers can compromise the efficient operation of processing equipment, particularly for the upgrading of heavy hydrocarbons. An experimental investigation was undertaken to study deposition from the vapor in a tubular test section downstream of a bench-scale continuous bitumen coking reactor. Results of the effects on deposition of coker reactor temperature, steam addition, vapor velocity, and heating or cooling of the produced vapor are presented. Evidence suggests that physical condensation of heavy hydrocarbon species rather than vapor-phase chemical reaction is the primary cause of deposit formation. Entrained droplets of partially converted bitumen also contribute to the deposit. Morphological and chemical characteristics of the deposits are described. Preliminary data are presented on the aging of the amorphous hydrocarbon deposit into coke.

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)0.001
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.046
GPT teacher head0.293
Teacher spread0.247 · 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

Citations13
Published2005
Admission routes2
Has abstractyes

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