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Record W2319707192 · doi:10.1021/ef4018543

Adsorption and Subsequent Oxidation of Colombian Asphaltenes onto Nickel and/or Palladium Oxide Supported on Fumed Silica Nanoparticles

2013· article· en· W2319707192 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy & Fuels · 2013
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
FundersUniversidad Nacional de ColombiaDepartamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)
KeywordsAsphalteneFumed silicaAdsorptionFreundlich equationSorptionChemical engineeringThermogravimetric analysisMaterials scienceLangmuirNickelPalladiumCatalysisInorganic chemistryChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

High asphaltene content in heavy crude oil normally generates adverse rheological properties that affect the flow through the reservoir, preventing optimal hydrocarbon production. It has been demonstrated that using nanoparticles may improve the mobility of oil. Nanoparticles may be used as adsorbents and catalysts in the oil industry for in situ upgrading. The main objective of this study was to investigate the sorption kinetics and the thermodynamic equilibrium for asphaltene sorption onto nickel and/or palladium oxides supported on fumed silica that was nanoparticulated at different times, temperatures, and concentrations. After adsorption, thermally cracked asphaltenes from Colombian crude oil were investigated using catalytic oxidation. The asphaltenes adsorbed onto the selected nanoparticles were subjected to thermal decomposition up to 700 °C in a thermogravimetric analyzer. This study was realized using an experimental design with a measured simplex–centroid of the three components by varying the wt % of the palladium and nickel oxides as well as the fumed silica as the support. The silica nanoparticles were characterized using N 2 adsorption at 196 °C and X-ray diffraction. The Langmuir and Freundlich models were used to correlate the experimental sorption equilibrium data. The experimental asphaltene adsorption isotherm data were adequately adjusted using the Freundlich model. The adsorption of asphaltenes on NiO and/or PdO supported on fumed silica was much higher than that over fumed silica over the range of the tested equilibrium concentrations. Pseudo-first- and pseudo-second-order kinetic models were applied to the experimental data obtained at different asphaltene concentrations from 100 to 1500 mg/L for the virgin fumed silica (S) and fumed silica-supported materials (SHSs); better fits were found for the pseudo-second-order model. However, the nanoparticles significantly decreased the asphaltene decomposition temperature and activation energy. The catalyst kinetics was calculated using the Ozawa–Flynn–Wall Model (OFW). All of the nanoparticles demonstrated high catalytic activity toward asphaltene decomposition in the following order at 0.2 mg/m 2 asphaltene concentration on nanoparticle surfaces: SNi1 < SNi1Pd1< SNi0.66Pd0.66 < SPd1 < SPd2 < SNi2 < S. Consequently, using nanoparticles significantly enhanced the thermal decomposition of asphaltenes, improving the mobility of heavy oils in situ.

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.

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 score0.016
Threshold uncertainty score0.548

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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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