Determinação de propriedade físico-químicas de biodiesel e blendas por RMN de baixo campo e calibração multivariada

• Ano de defesa: 2018
• Autor(a) principal: Constantino, André Fazolo
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Doutorado em Química; Centro de Ciências Exatas; UFES; Programa de Pós-Graduação em Química
• Palavras-chave em Português: Biodiesel; RMN de baixo campo; PLS; Viscosidade cinemática; Ressonância magnética nuclear; Iodo; Química; 54
• Link de acesso: http://repositorio.ufes.br/handle/10/10793

Because the methods specified by regulatory agencies for the determination of the physicochemical properties of biodiesel can be laborious and expensive, the development of alternative methodologies represents a major breakthrough. Thus, low-field nuclear magnetic resonance (NMR) is an advantageous option because it is nondestructive and reduces the cost and time consumption. In this study, the partial least squares (PLS) regression method was used to create models that correlated the decay curves of the Carr–Purcell–Meiboom–Gill (CPMG) signal, Continuous Wave Free Precession (CWFPx-x) orCarr–Purcell Continuous Wave Free Precession (CP-CWFPx-x), obtained fromlow-field NMR equipments(2.2 MHz and 15.0 MHz for 1H), with the kinematic viscosity, specific mass,refractive index and iodine value of biodiesel and their blends. Seventeen oilseeds diversified between edible and non-edible oils were utilized to synthesizethe biodiesel and producebinary blends.Separately, multivariate calibration models were created only with pure biodiesel and blends withcastor bean because these samples showed different tendencies from the others. The best values of root mean square error of prediction (RMSEP) for the kinematic viscosity, specific mass and refractive index were equal to 0.1 mm2/s, 1.9 kg/m3, 0.002 and 15.5 g I2/100 g of sample,respectively, for samples of biodiesel and blends without castor bean and 0.3mm2/s, 1.3kg/m3,0.0003 and 1.9 g I2/100 g of samplefor samples of biodiesel and blends with castor bean. The results reveal that the developed models are very satisfactory to predict the quality parameters of biodiesel and blendswith fairly good efficacy, withthe models created withCPMG andCP-CWFPx-xdata being stood out to those constructedwith CWFPx-xdata. The physicochemical properties were also correlated with the decay curves of seed and oil samples, with the aim of predicting the quality of biodiesel from the analysis of its raw materials. However,the resultswere not very promising, sincethe correlations betweenmeasured physicochemical properties by American Society for Testing and Materials (ASTM) methods and its predicted values from the constructed PLS models resulted in very low coefficients of determination (R2)