This study proposes a screen of variables that have an influence on the modification of the bio-oil chemical composition as a unique critical quality attribute (CQA) throughout the pyrolytic process (zeolite, ZSM-5) by using a 24 full factorial design, followed by optimization through a response surface methodology (RSM) based on central composite design (CCD) involving samples of biomass sorghum BRS716 (Sorghum bicolor L. Moench). The pyrolysis of pure biomasses and the biomass impregnated with the catalyst was carried out in a vertical bench furnace at 500 °C. Screening design involved factor variation in two levels (-1 and +1) of four variables as critical process parameters (CPPs) such as furnace heating rate (°C min-1), nitrogen flow (mL min-1), amount of biomass (g), and catalyst (% m/m), leading to obtaining bio-oil. Thus, it was possible to create a response surface from these two variables (biomass and catalyst), in which a minimum critical point was reached. The production of a bio-oil rich in hydrocarbon compounds is possible, but a large amount of catalyst was required. Two analytical techniques based on gas chromatography coupled to mass spectrometry (GC-MS) and mid-infrared (MIR) spectroscopy, provided additional information to fully characterize bio-oil chemical composition.

Três origens diferentes de biodiesel (algodão, mamona e palma) foram adulteradas com óleo de soja cru, em concentrações variando de 1 a 40% (m/m). Estas amostras foram analisadas por espectrometria de infravermelho médio (MIR) e os seus espectros foram estudados em três diferentes faixas espectrais: espectro inteiro (4000-665 cm-1), e nas faixas de 1800-1700 cm-1 e 1800-1000 cm-1. Para determinar a origem do biodiesel utilizado no sistema adulterado, os dados espectrais foram analisados pela ferramenta análise de componentes principais (PCA) e a melhor segregação das origens foi obtida para o espectro inteiro (4000-665 cm-1). A variância explicada foi de 99%, para os três primeiros componentes. Para quantificar o óleo de soja cru foi aplicada a ferramenta mínimos quadrados parciais (PLS). Os melhores resultados foram obtidos para a região espectral de 1800-1000 cm-1, com valores de RMSEP (erro médio quadrático de previsão) variando de 1,10 a 1,47% (m/m).

Three different biodiesel sources (cotton, castor and palm) were adulterated with raw soybean oil at concentrations ranging from 1-40% (m/m). These samples were analyzed by infrared spectrometry (MIR) and their spectra were studied at three different spectral ranges: full spectrum (4000-665 cm-1), and the spectral ranges of 1800-1700 cm-1 and 1800-1000 cm-1. To determine the source of biodiesel used in the adulterated system, the data were analyzed by PCA (principal components analysis) spectral analysis tool and the best segregation of the sources was obtained at the range of 4000-665 cm-1. The explained variance was of 99% for the first three components. To quantify the raw soybean oil partial least squares (PLS) tool was applied. The best results were obtained for the spectral range of 1800-1000 cm-1, with values of RMSEP (root mean square error of prediction) varying from 1.10 to 1.47% (m/m).

Due to source contamination and wearing of instrument components problems caused by the direct insertion probe technique, a new way of introduction of low volatile compounds into mass spectrometer was tested. This new scheme comprises the introduction of the low volatile compounds solutions via a six port valve connected to a particle beam interface. Solutions of isatin were injected into this system and the best results were obtained with CH2Cl2, CH3OH and CH3CN. The solution inlet system has shown to be advantageous over the conventional way of direct insertion probe introduction.