Application of Near‐Infrared Spectroscopy to the Characterization of Petroleum

Pantoja, Patricia Araujo; López‐Gejo, Juan; Nascimento, Cláudio Augusto Oller do; Roux, G.

doi:10.1002/9781119286325.ch8

Cited by 6 publications

(4 citation statements)

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“…Our vapor-phase mid-IR FTIR measurements utilize fuel vapor at 50 or 80 • C (rather than liquid as in [17,18,20,21,22,23,24,25,26]) to characterize the hydrocarbon fuels' spectral features. These spectra are not sensitive to temperature from 50 to 80 • C. This method has several advantages.…”

Section: Advantages Of Using Vapor-phase Mid-ir Spectrummentioning

confidence: 99%

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On estimating physical and chemical properties of hydrocarbon fuels using mid-infrared FTIR spectra and regularized linear models

Wang

Ding

Wei

et al. 2019

Fuel

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The concept of a compact, economical FTIR-based analyzer for estimating the properties of hydrocarbon fuels with small amounts of fuel is proposed. The high correlations between mid-IR FTIR absorption spectra of fuel vapor in the range 3300 to 3550 nm and 15 physical and chemical properties, such as density, initial boiling point, surface tension, kinematic viscosity, number of carbon and hydrogen per average molecule, and derived cetane number, for 64 hydrocarbon fuels are demonstrated. Lasso-regularized linear models based on linear combination of absorption cross sections at selected wavelengths are built for each of these physical and chemical properties, yielding accurate estimations.

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Section: Advantages Of Using Vapor-phase Mid-ir Spectrummentioning

confidence: 99%

“…Da Silva et al used liquid-phase spectra in both near-and mid-IR (833.3 nm to 15.4 µm) and machine learning models to classify if a gasoline contains dispersant and detergent additives [21]. More related work can be found in [22,23,24,25,26].…”

Section: Introductionmentioning

confidence: 99%

On estimating physical and chemical properties of hydrocarbon fuels using mid-infrared FTIR spectra and regularized linear models

Wang

Ding

Wei

et al. 2019

Fuel

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“…PLS was firstly developed over 40 years ago. Nevertheless, it is still the most widely used methodology for multivariate calibration and quantitative analysis . The goal of PLS is to establish a relationship between a matrix X of predictor variables and a vector y of the target property values, previously measured by conventional techniques.…”

Section: Methodsmentioning

confidence: 99%

Estimation of gasoline properties by ¹H NMR spectroscopy with repeated double cross‐validated partial least squares models

Leal

Albuquerque²,

Silva

et al. 2020

Journal of Chemometrics

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Commercial gasoline must satisfy several product specifications before trading.In the present work, repeated double cross validation using partial least squares regression was applied to create reliable prediction models for 13 physicochemical parameters (eg, density, vapour pressure, evaporate at 70 C, evaporate at 100 C, evaporate at 150 C, final boiling point, research octane number, motor octane number, aromatic content, olefinic content, benzene content, oxygen content, and methyl tert-butyl ether content) of gasoline produced in Matosinhos' refinery. The input variables for the regression are the 1 H NMR spectral intensities of a total of 448 samples, which were recorded using a pico-Spin NMR spectrometer operating at 80 MHz. The output variables are the corresponding property values, which were also measured according to ISO standard methods. A spectral feature elimination before multivariate analysis was done to remove noise and speed up the chemometric analysis. The optimum complexity of each model was achieved by repeated double crossvalidation strategy, consisting of 100 repetitions of two nested cross-validation loops. Quantitative partial least squares yielded accurate predictions of 11 of 13 properties within the reproducibility of ISO standards. The methodology presented in this work has been proven effective in property estimation and enables a significant reduction in the total time of gasoline quality control.

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“…O primeiro estudo envolvendo a identificação de substâncias puras e grupos funcionais, fazendo-se uso da radiação infravermelho, foi realizado pelo físico norte-americano William Coblentz, em 1900 (PASQUINI, 2018). Por esse motivo, a espectroscopia no infravermelho oferece oportunidades analíticas quase que ilimitadas para muitas áreas de produção e controle de qualidade, sendo aplicada atualmente em indústrias farmacêuticas, de alimentos, têxteis, além de laboratórios analíticos e indústrias petroquímicas (NAZARENKO; RODIN; SHPIGUN, 2019; PANTOJA et al, 2017;ZAREEF et al, 2020;ZHOU et al, 2015).…”

Section: Espectroscopia No Infravermelhounclassified

Desenvolvimento de classificador de código aberto para identificação de polímeros destinados à manufatura aditiva

Cunha¹

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very specific subset, evidencing the feasibility of applying the classification system in the scope of the project. The main contribution of the work, therefore, was the development of a classification algorithm, as well as a conceptual project, capable of granting initial procedures of a system that provides the increase of accessibility and productivity of the AM in various manufacturing domains.

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Application of Near‐Infrared Spectroscopy to the Characterization of Petroleum

Cited by 6 publications

References 50 publications

On estimating physical and chemical properties of hydrocarbon fuels using mid-infrared FTIR spectra and regularized linear models

On estimating physical and chemical properties of hydrocarbon fuels using mid-infrared FTIR spectra and regularized linear models

Estimation of gasoline properties by ¹H NMR spectroscopy with repeated double cross‐validated partial least squares models

Desenvolvimento de classificador de código aberto para identificação de polímeros destinados à manufatura aditiva

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Application of Near‐Infrared Spectroscopy to the Characterization of Petroleum

Cited by 6 publications

References 50 publications

On estimating physical and chemical properties of hydrocarbon fuels using mid-infrared FTIR spectra and regularized linear models

On estimating physical and chemical properties of hydrocarbon fuels using mid-infrared FTIR spectra and regularized linear models

Estimation of gasoline properties by 1H NMR spectroscopy with repeated double cross‐validated partial least squares models

Desenvolvimento de classificador de código aberto para identificação de polímeros destinados à manufatura aditiva

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Estimation of gasoline properties by ¹H NMR spectroscopy with repeated double cross‐validated partial least squares models