SAP fractions from light, medium and heavy oils: Correlation between chemical profile and stationary phases

Ferreira, Polianna da Silva; Madeira, Natã C. L.; Folli, Gabriely S.; Romão, Wanderson; Filgueiras, Paulo R.; Küster, Ricardo Machado

doi:10.1016/j.fuel.2020.117866

Cited by 5 publications

(5 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The FT-ICR MS analyses were performed by a SolariX 9.4T FT-ICR mass spectrometer − (Bruker, Bremen, Germany) equipped with an ICR cell as the infinity cell.…”

Section: Methodsmentioning

confidence: 99%

“…The maximum acceptable accuracy was 3 ppm. The Composer and Compass Data Analysis presents information about the heteroatom classes present in the samples, DBE information, and charts relating carbon number and DBE values. − The DBE is calculated from eq . − where C represents the number of carbons, H the number of hydrogens, N the number of nitrogens in the molecular formula.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Study of Thermal Aging of Model Compounds Present in Asphalt Cement by GC/MS, ESI-MS, NMR, and FTIR

et al. 2021

Self Cite

View full text Add to dashboard Cite

The study of petroleum asphalt cement (AC) aging is essential for the production of good quality pavements with high durability. Because of the complexity of this material, one of the biggest challenges is understanding the chemical variations that occur in the molecules present in the AC during the aging processes. This work proposes to study 15 standards of model compounds present in the AC composition, representing the fractions of saturated compounds (5-α-cholestane and hexatriacontane), aromatics (hexamethylbenzene, coronene, and benzo-[a]anthracene), nitrogenous compounds (acridine, carbazole, indole, and N,N′-Bis(3-pentyl)perylene-3,4,9,10-bis-(dicarboximide)), sulfur compounds (2-naphthalenethiol, 4,6diethyldibenzothiophene, and naphtho[1,2-b:6,5-b′]dithiophene(NDT)), and naphthenic acids (stearic (SA), pentadecanoic (PA), and sinapinic acids (ASN)), which were thermally aged by two methods: (i) they were subjected to a constant temperature of 80 °C, varying the time of analysis over 5, 10, 15, 30, and 60 days; and (ii) temperatures ranging from 80, 100, 120, to 140 °C for 15 days. The analyses of these compounds were performed by GC/MS, 1 H and 13 C NMR, ESI(−)MS (FT-ICR and LTQ), and FTIR. The results obtained showed that at 80 °C, from 15 days, only the indole standard compound showed the presence of thermal products, i.e., compounds detected from thermal aging of the standard model compounds. When the degradation temperature was increased from 100 to 140 °C, we observed the formation of thermal products at 100 °C in 6 out of 15 model compounds. However, at 140 °C, 12 of the 15 model compounds presented some type of degradation. Reactions of oxidation, polymerization, thermal aging, volatilization, and formation of double bonds were observed.

show abstract

“…The FT-ICR MS analyses were performed by a SolariX 9.4T FT-ICR mass spectrometer − (Bruker, Bremen, Germany) equipped with an ICR cell as the infinity cell.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Study of Thermal Aging of Model Compounds Present in Asphalt Cement by GC/MS, ESI-MS, NMR, and FTIR

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…To determine API gravity, the density results were converted to a density equivalent to 20°C and applied in Equation (), where ρ is the density at 60°F 23

API goodbreak= \frac{141,5}{ρ 60^{°} F} goodbreak- 131,5 .

Asphaltenes content was determined according to ASTM D6560 25 and saturates, aromatics, and resins content were analyzed by Supercritical Fluid Chromatography/thin Layer Chromatography–Flame Ionization Detector (SFC/TLC‐FID) 26,27 …”

Section: Methodsmentioning

confidence: 99%

Variable selection by permutation applied in support vector regression models

Cunha

Paulo

Folli

et al. 2022

Journal of Chemometrics

Self Cite

View full text Add to dashboard Cite

Support vector regression (SVR) can be considered as a black box machine‐learning method. Thus, identifying the cause/effect relationship and the synergism between the most important variables is a difficult task. This study demonstrates the potential of two variable selection methods by permutation—subwindow permutation analysis (SPA) and noise incorporated subwindow permutation analysis (NISPA)—to overcome this limitation. The application of these two variable selections in SVR is poorly explored in literature, mainly for regression problems. The algorithms were applied in FTIR (Fourier transform mid infrared spectroscopy) data of crude oil samples to estimate API gravity, kinematic viscosity at 50°C, saturates, aromatics, resins, and asphaltene content. The results were compared to other variable selection methods. SPA and NISPA provided the most accurate models for kinematic viscosity, saturates, and aromatic content. The root‐mean‐squared percentage error of prediction (RMSPEP) of the SPA and NISPA were, respectively, 14.26% and 14.62% for kinematic viscosity, 4.7 wt% and 4.4 wt% for saturates content, and 3.4 wt% and 3.1 wt% for aromatic content. Regarding API prediction, despite obtaining similar accuracy to the other selection methods, SPA produced a more simplified model, using only 3.5% of the 3351 total variables, with RMSEP equal to 1.0 and R2p to 0.981. Therefore, SPA and NISPA, besides obtaining, in general, faster and more accurate and parsimonious models, revealed the most important variables for building the SVR models.

show abstract

“…In this context, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) is widely applied to petroleum study; , however, there are few works on the theme of asphalt aging. Bringing information that can complement the study at the molecular level of asphalt aging can bring more specific information about the chemical composition (C c H h N n O o ) and aromaticity of asphalt and to answer the why or how chemical reactions occur in the aging process.…”

Section: Introductionmentioning

confidence: 99%

“…16−18 Nuclear magnetic resonance (NMR) spectrometry comprises information on the types of hydrogen and carbon, having a wide variety of methods for different applications; though compared to IR, it is still little applied. 19−21 In this context, Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) is widely applied to petroleum study; 22,23 however, there are few works on the theme of asphalt aging. Bringing information that can complement the study at the molecular level of asphalt aging can bring more specific information about the chemical composition (C c H h N n O o ) and aromaticity of asphalt and to answer the why or how chemical reactions occur in the aging process.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Asphalt Aging by Analytical Techniques: A Review on Progress and Perspectives

2022

Self Cite

View full text Add to dashboard Cite

This review describes the chemical composition of asphalt, which is relevant for the development of materials with higher quality and durability. Asphalt aging can occur in the short term (during machining and storage periods) and the long-term (during the time the pavement is exposed to the environment). To understand the effect of aging on the chemical and physical properties of asphalt, we reviewed the short-term (rolling-thin film oven test (RTFOT) and its variations) and long-term (pressure aging vessel (PAV) and its variations) aging methods and the effects of the sun’s ultraviolet radiation (Suntest and its variations). We also explored the main chemical reactions that occur in the aging processes, such as oxidation, polymerization, and aromatization. For a more accurate assessment of the classes of compounds that undergo aging reactions, fractionation techniques have been developed over the years, such as separation of asphalt into saturates, naphthenic-aromatics, resins, asphaltenes, organic sulfides, nitrogenates, and oxygenates, among others. Despite several studies on the theme of asphalt aging, it is still necessary to understand the phenomena that occur in those processes.

show abstract

SAP fractions from light, medium and heavy oils: Correlation between chemical profile and stationary phases

Cited by 5 publications

References 52 publications

Study of Thermal Aging of Model Compounds Present in Asphalt Cement by GC/MS, ESI-MS, NMR, and FTIR

Study of Thermal Aging of Model Compounds Present in Asphalt Cement by GC/MS, ESI-MS, NMR, and FTIR

Variable selection by permutation applied in support vector regression models

Characterization of Asphalt Aging by Analytical Techniques: A Review on Progress and Perspectives

Contact Info

Product

Resources

About