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Partial Upgrading of Bitumen by Thermal Conversion at 150–300 °C

2018· article· en· W2793132639 on OpenAlexafffund
Lina M. Yañez Jaramillo, Arno de Klerk

Bibliographic record

VenueEnergy & Fuels · 2018
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Resources CanadaHelmholtz-Alberta InitiativeHelmholtz-GemeinschaftUniversity of Alberta
KeywordsAsphalteneViscosityChemistryAsphaltCrackingThermodynamicsHydrogenChemical engineeringOrganic chemistryMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Bitumen produced from oilsands deposits has a high viscosity, which presents a challenge to pipeline transport. Ways to reduce the viscosity at low incremental production cost are desirable. Thermal conversion of oilsands-derived bitumen at temperatures in the range of 150–300 °C was explored as a potential strategy for viscosity reduction. Viscosity increased compared to the bitumen feed following thermal treatment of bitumen at 150 and 200 °C but decreased following thermal treatment at 250 and 300 °C. At all temperatures studied, changes in the chemical and physical nature of the product were observed within 1 h of reaction time, and changes continued as reaction time was extended to a period of 8 h. Hydrogen transfer and methyl transfer were important reactions. These transfer reactions appeared to be concerted in nature and did not involve cracking to release free hydrogen or methyl radicals. In fact, thermal cracking was a minor reaction. The olefin content of the liquid was low, there was little gas-make, and the H 2 S concentration in the gaseous product was low. The n -pentane insoluble (asphaltenes) content of the liquid, with a few exceptions, increased during thermal conversion, but it was poorly correlated to viscosity. It is unlikely that the change in viscosity can be attributed to a single factor. The two most important factors appeared to be (i) the formation of heavier molecules that caused an increase in “excluded volume” with a concomitant increase in viscosity and slight decrease in density and (ii) a change in the phase behavior of the product due to chemical changes in the product.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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

Citations30
Published2018
Admission routes2
Has abstractyes

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