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Thermo-Oxidative Decomposition Behaviors of Different Sources of <i>n</i>-C<sub>7</sub> Asphaltenes under High-Pressure Conditions

2020· article· en· W3032280334 on OpenAlexaff
Oscar E. Médina, Jaime Gallego, Nashaat N. Nassar, Sócrates Acevedo, Farid B. Cortés, Camilo A. Franco

Bibliographic record

VenueEnergy & Fuels · 2020
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
FundersUniversidad Nacional de ColombiaDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)
KeywordsThermogravimetric analysisAsphalteneChemistryThermal decompositionDecompositionX-ray photoelectron spectroscopyAnalytical Chemistry (journal)Fourier transform infrared spectroscopyOxygenOrganic chemistryNuclear magnetic resonanceChemical engineering

Abstract

fetched live from OpenAlex

Effects of pressure on thermo-oxidative decomposition of different sources of n-C7 asphaltenes were investigated at high pressure using a thermogravimetric analyzer under an air atmosphere. The n-C7 asphaltenes were extracted from different heavy and extra-heavy crude oils around the world and were thoroughly characterized by elemental analysis (EA), vapor pressure osmometry (VPO), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), and nuclear magnetic resonance (NMR) techniques. A high-pressure thermogravimetric analyzer coupled to a mass spectrometer was employed to obtain thermograms at 0.084, 3.0, and 6.0 MPa, and gaseous products were obtained by asphaltene decomposition. Kinetic analyses were performed for thermo-oxidative multistep reactions and compared based on the trends of pre-exponential factor and effective activation energies using an approximation of the Ozawa, Flynn, and Wall (OFW) isoconversional method. The n-C7 asphaltene decomposition profile was determined by four thermal events, namely, oxygen chemisorption (OC), desorption/decomposition of chemisorbed oxygen functional groups (DCO), and first and second combustion (FC and SC, respectively). We found that the amount of chemisorbed oxygen depends not so much on the oxygen percentage present in the n-C7 asphaltenes and aggregates but on whether it is found in a greater proportion as COO groups, independent of the used pressure. In addition, as the aromatization degree increases and the alkylation degree decreases, the amount of oxygen atoms chemisorbed also increases. As for the DCO region, it was corroborated that the increase in pressure from 0.084 to 6.0 MPa has a positive influence on the mass loss in this region for all samples used. The n-C7 asphaltenes with a higher chemisorption in the previous region showed a higher decomposition or loss of oxygenated compounds during DCO because there are more oxygenated groups in the basal plane of aromatic structures; therefore, the kinetics of the carbonaceous material consumption is increased. According to XPS analysis, n-C7 asphaltenes with a higher content of sulfur as thioethers show facilitated decomposition, due to the low energy required for their oxidation and subsequent cracking, throughout the range of evaluated pressures. Further, the higher content of hydrogen on α carbons to aromatic rings suggests that some of their small alkyl side chains are cracked in this zone due to the easy decomposition of α-methyl, α-methylene, and α-methine structures. As for the FC region, up to 3.0 MPa, a greater mass loss occurs in n-C7 asphaltenes with a high content of short aliphatic chains. Nevertheless, at 6.0 MPa, the mass loss percentage decreases in similar measures for all samples, indicating that under these conditions there is greater ease of breaking the functional groups located both in the basal plane of the aromatic rings and on the periphery of the molecule. Finally, during high-temperature oxidation reactions (SC), the higher aromaticity degree increases the percentage of mass loss. These findings suggest that n-C7 asphaltene mass loss is controlled by the sequential reaction mechanisms characterized by the four thermal events, especially under high-pressure conditions.

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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 score0.003
Threshold uncertainty score0.715

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 head0.010
GPT teacher head0.237
Teacher spread0.228 · 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".

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Citations41
Published2020
Admission routes1
Has abstractyes

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