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Record W2326295654 · doi:10.1021/ef5008227

Characterization and Refining Pathways of Straight-Run Heavy Naphtha and Distillate from the Solvent Extraction of Lignite

2014· article· en· W2326295654 on OpenAlexaff
Toluwanise Adesanwo, Moshfiqur Rahman, Rajender Gupta, Arno de Klerk

Bibliographic record

VenueEnergy & Fuels · 2014
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNaphthaChemistryFraction (chemistry)HydrodesulfurizationCoalDistillationOrganic chemistryDiesel fuelBoiling pointFuel oilKeroseneJet fuelWaste managementCatalysis

Abstract

fetched live from OpenAlex

Coal liquids were produced by solvent extraction of Bienfait lignite at 415 °C and 4 MPa H 2 for 1 h with a hydrotreated coal tar distillate in a 2:1 solvent to coal ratio. Detailed characterization was performed on four straight-run distillation fractions of the coal liquids in the 120–370 °C boiling range. It was found that the coal liquids contained very little aliphatic material. Most of the compounds were aromatics, with aromatic compounds having no alkyl substituents dominating the composition. The aromatic carbon content increased with boiling fraction from 80 wt % in the 120–250 °C fraction to 94 wt % in the 343–370 °C fraction. Major compounds identified in the coal liquids were acenaphthene, phenanthrene, fluoranthene, and pyrene, which constituted 62 wt % of the total product. The coal liquids also contained heteroatom species. Interestingly, the nitrogen content did not monotonically increase with an increase in boiling point. The maximum nitrogen content was found in the 300–343 °C boiling fraction as a result of a high concentration of carbazole. The refining pathways for transportation fuel production were evaluated. It was found that the naphtha fraction could be upgraded to a motor gasoline blending component just by hydrotreating. No subsequent catalytic reforming was necessary because of the low aliphatic content of the naphtha. The kerosene required severe hydrotreating in order to be acceptable as a jet fuel blending component, mainly because of the high dinuclear aromatic content of the straight-run kerosene. The distillate made a poor feed material for diesel fuel and required severe hydrotreating to achieve an acceptable cetane number. In general, the coal-derived distillate would benefit from ring opening to reduce its density. The prognosis for transportation fuel production from the coal liquids was not favorable. The production of aromatic chemicals was a better fit with the properties of the coal liquids.

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 score0.030
Threshold uncertainty score0.271

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 head0.188
Teacher spread0.179 · 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

Citations9
Published2014
Admission routes1
Has abstractyes

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