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Record W2324734691 · doi:10.1021/ef502078n

Density Functional Theory Study of the Effects of Substituents on the Carbon-13 Nuclear Magnetic Resonance Chemical Shifts of Asphaltene Model Compounds

2014· article· en· W2324734691 on OpenAlexafffund
Jackeline S. C. Oliveira, Leonardo Moreira da Costa, Stanislav R. Stoyanov, Peter Rudolf Seidl

Bibliographic record

VenueEnergy & Fuels · 2014
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsNational Institute for NanotechnologyUniversity of Alberta
FundersDepartment of Mechanical Engineering, University of AlbertaNational Research Council CanadaFundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de JaneiroUniversity of AlbertaGovernment of CanadaGaussianWestern Canada Research GridNational Institute for NanotechnologyStrykerGovernment of AlbertaNational Institute of Advanced Industrial Science and Technology
KeywordsAsphalteneDensity functional theoryChemical shiftCarbon fibersChemistryComputational chemistryNuclear magnetic resonancePhysical chemistryOrganic chemistryThermodynamicsMaterials sciencePhysics

Abstract

fetched live from OpenAlex

Petroleum asphaltenes are a complex mixture of organic molecules containing mainly fused polyaromatic and naphthenic systems and pendant chains, polar moieties with heteroatoms (S, N, and O), and transition metals. A variety of spectroscopic techniques has been employed to characterize asphaltenes, but their structures remain largely elusive because of the complexity, variety of samples, and assignment limitations. Carbon-13 nuclear magnetic resonance ( 13 C NMR) spectroscopy has contributed extensively to asphaltene characterization. However, proper assignment of 13 C NMR spectra is very challenging because spectra of natural asphaltenes feature a large number of peaks in unusual environments, which may be hard to assign and interpret. We employ the dispersion-corrected ωB97X-D density functional with 6-31G(d,p) basis set to rationalize common trends in the 13 C NMR chemical shifts of asphaltene model compounds. The calculated 13 C NMR chemical shifts for a calibration series of 14 aromatic and heterocyclic reference compounds containing C atoms of types similar to those in the asphaltene model compounds are found to correlate linearly with the respective experimental values. The linear fitting yields a correlation coefficient of R 2 = 0.99 and absolute errors of less than 10 ppm. Moreover, we calculate and calibrate the 13 C chemical shifts of asphaltenes extracted from Brazilian vacuum residues to analyze and correlate the C atom types with those of the reference compounds. It is found that the presence of heteroatoms as well as environments with a high aromatic condensation index can significantly affect the chemical shifts. The effect of heteroatoms on the chemical shift, a situation that has scarcely been addressed in the literature, is evaluated here in detail. The results are intended to help interpret 13 C NMR spectra and allow for a more complete characterization of asphaltene molecules.

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)0.002
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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 designSimulation or modeling
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

Citations6
Published2014
Admission routes2
Has abstractyes

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