Artículos de revistas
Laser Desorption Ionization Ft-icr Mass Spectrometry And Carspls For Predicting Basic Nitrogen And Aromatics Contents In Crude Oils
Registro en:
Laser Desorption Ionization Ft-icr Mass Spectrometry And Carspls For Predicting Basic Nitrogen And Aromatics Contents In Crude Oils. Elsevier Sci Ltd, v. 160, p. 274-281 Nov-2015.
0016-2361
WOS:000360710600031
10.1016/j.fuel.2015.07.099
Autor
Terra
Luciana A.; Filgueiras
Paulo R.; Tose
Lilian V.; Romao
Wanderson; de Castro
Eustaquio V. R.; de Oliveira
Lize M. S. L.; Dias
Julio C. M.; Vaz
Boniek G.; Poppi
Ronei J.
Institución
Resumen
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) This work describes a methodology for predicting basic nitrogen and aromatics contents in crude oil, using positive ion mode laser desorption ionization coupled to Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and partial least squares (PLS) regression with variable selection based on competitive adaptive reweighted sampling (CARS), in a procedure called CARSPLS regression. The basic nitrogen and aromatics contents were determined using UOP Method 269-10 and ASTM D5443-14, respectively, for 70 samples of Brazilian crude oil. The basic nitrogen values ranged from 0.016% to 0.151% and the aromatics values from 8.4% to 35.1%. The LDI(+)-FT-ICR mass spectra of crude oil samples have profiles that ranged from m/z 200 to 1000, with an average molar mass distribution (M-w) centered between 554 and 636 Da. Most of the identified organic species are analogues of pyridine and polyaromatic hydrocarbon compounds that belong in the N-x, N-x[H], HC, and HC[H] classes. Additionally, the number of detected N-x species increases systematically with increasing basic nitrogen and aromatics content. The CARS method was used to select the most informative variables for the PLS calibration model, thereby reducing the number of variables from 47,873 to 48 and 10 for basic nitrogen and aromatic compounds, respectively. The prediction model based on CARSPLS presented RMSEP of 0.012 and 3.73 wt% for basic nitrogen and aromatics contents, respectively. In addition, it was possible to verify that the accuracy of CARSPLS is ever better than only using PLS regression (with all variables). The application of CARSPLS algorithm is therefore justified by easier interpretation of the FT-ICR MS data after variables reduction. (C) 2015 Elsevier Ltd. All rights reserved. 160
274 281 PETROBRAS/CENPES Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) FAPEG FINEP Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)