Use of 1H NMR and chemometrics to detect additives present in the Brazilian commercial gasoline

被引:24
|
作者
Pinto, Vinicius S. [1 ]
Gambarra-Neto, Francisco F. [1 ]
Flores, Igor S. [2 ]
Monteiro, Marcos R. [3 ]
Liao, Luciano M. [1 ]
机构
[1] Univ Fed Goias, Inst Quim, BR-74690900 Goiania, Go, Brazil
[2] Inst Fed Goias, BR-72811580 Luziania, Go, Brazil
[3] Univ Fed Sao Carlos, Dept Engn Mecan, BR-13560971 Sao Carlos, SP, Brazil
关键词
NMR; PCA; SIMCA; Gasoline additives; Gasoline analysis; MAGNETIC-RESONANCE-SPECTROSCOPY; GEOGRAPHICAL ORIGIN; FUEL ADDITIVES; QUALITY; NMR;
D O I
10.1016/j.fuel.2016.05.072
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In Brazil, gasoline is classified as type C, where the addition of oxygenates occurs as anhydrous ethanol at a concentration determined by law. The gasoline can be marketed as common (CG) or additive gasoline (AG), which differs by the addition of packages of multifunctional additives that confer beneficial properties to the fuel. However, there are no methods for the identification of additives in gasoline. This paper describes the use of Nuclear Magnetic Resonance spectroscopy of hydrogen (H-1 NMR) along with principal component analysis (PCA) and Soft Independent Modelling of Class Analogies (SIMCA) to differentiate between CG and AG. All AG samples were correctly classified, including thirty-three CG samples intentionally additive with 500, 1000 and 2500 ppm of seven different commercial additives. The methodology allows to detect the presence of additives used in commercial gasolines and can be an important tool for quality control of the product. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:27 / 33
页数:7
相关论文
共 50 条
  • [1] Use of 1H nuclear magnetic resonance and chemometrics to detect the percentage of ethanol anhydrous in Brazilian type C premium gasoline
    Pinto, Vinicius S.
    FUEL, 2020, 276
  • [2] Multivariate calibrations on 1H NMR profiles for prediction of physicochemical parameters of Brazilian commercial gasoline
    Flumignan, Danilo Luiz
    Sequinel, Rodrigo
    Hatanaka, Rafael Rodrigues
    Boralle, Nivaldo
    de Oliveira, Jose Eduardo
    FUEL, 2012, 99 : 180 - 187
  • [3] Discrimination of Brazilian lager beer by 1H NMR spectroscopy combined with chemometrics
    da Silva, Luis Augusto
    Flumignan, Danilo Luiz
    Tininis, Aristeu Gomes
    Pezza, Helena Redigolo
    Pezza, Leonardo
    FOOD CHEMISTRY, 2019, 272 : 488 - 493
  • [4] CLASSIFICATION OF TURKISH HONEY BY 1H NMR SPECTROSCOPY AND CHEMOMETRICS
    Ozkok, Asli
    Ozenirler, Cigdem
    Sorkun, Kadriye
    FRESENIUS ENVIRONMENTAL BULLETIN, 2018, 27 (12): : 8328 - 8339
  • [5] 1H NMR Fingerprinting of Brazilian Commercial Gasoline: Pattern-Recognition Analyses for Origin Authentication Purposes
    Maia Rigo, Tainara Rodrigues
    Flumignan, Danilo Luiz
    Boralle, Nivaldo
    de Oliveira, Jose Eduardo
    ENERGY & FUELS, 2009, 23 (08) : 3954 - 3959
  • [6] 1H NMR spectroscopy and chemometrics evaluation of non-thermal processing of orange juice
    Alves Filho, Elenilson G.
    Almeida, Francisca D. L.
    Cavalcante, Rosane S.
    de Brito, Edy S.
    Cullen, Patrick J.
    Frias, Jesus M.
    Bourke, Paula
    Fernandes, Fabiano A. N.
    Rodrigues, Sueli
    FOOD CHEMISTRY, 2016, 204 : 102 - 107
  • [7] Gasoline composition determined by 1H NMR spectroscopy
    Burri, J
    Crockett, R
    Hany, R
    Rentsch, D
    FUEL, 2004, 83 (02) : 187 - 193
  • [8] HR MAS 1H NMR and chemometrics as useful tool to assess the geographical origin of cocoa beans - Comparison with HR 1H NMR
    Marseglia, A.
    Acquotti, D.
    Consonni, R.
    Cagliani, L. R.
    Palla, G.
    Caligiani, A.
    FOOD RESEARCH INTERNATIONAL, 2016, 85 : 273 - 281
  • [9] Alternative approach of applying 1H NMR in conjunction with chemometrics for wine classification
    Magdas, Dana Alina
    Pirnau, Adrian
    Feher, Ioana
    Guyon, Francois
    Cozar, Bogdan Ionut
    LWT-FOOD SCIENCE AND TECHNOLOGY, 2019, 109 : 422 - 428
  • [10] Use of 1H NMR to Detect the Percentage of Pure Fruit Juices in Blends
    Marchetti, Lucia
    Pellati, Federica
    Benvenuti, Stefania
    Bertelli, Davide
    MOLECULES, 2019, 24 (14):