87 research outputs found
Multivariate quality control of lubricating oils using Fourier transform infrared spectroscopy
Multivariate quality control in conjunction with Fourier transform infrared Spectroscopy (FTIR) were used to qualitatively detect the class and the condition of lubricating oils. The multivariate approach was based on principal component analysis (PCA), first to classify the lubricating oil type (mineral, synthetic and semi-synthetic) and then to develop two control charts: a T² chart using the most significant principal components and a Q chart with the PC not used in the first chart. From these two charts it was possible to identify oil samples, based on a viscosity parameter, which were out of the pattern normally present in utilizable lubricating oils.Controle de qualidade multivariado, em conjunto com espectroscopia no infravermelho por transformada de Fourier (FTIR), foi usado para detectar qualitativamente o tipo e a condição de óleos lubrificantes. O procedimento multivariado baseou-se na análise de componentes principais (PCA), primeiro para classificar o tipo do lubrificante (mineral, sintético e semi-sintético) e depois para desenvolver duas cartas de controle: uma carta T² usando os componentes principais mais significativos e uma carta Q com os componentes principais não utilizados na primeira carta. A partir destas duas cartas, foi possível identificar amostras de óleo, baseado no parâmetro da viscosidade, que se encontravam fora do padrão normalmente presente em lubrificantes em condições de uso.570576Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq
Simultaneous Determination Of Hydrocarbon Renewable Diesel, Biodiesel And Petroleum Diesel Contents In Diesel Fuel Blends Using Near Infrared (nir) Spectroscopy And Chemometrics.
Highly polluting fuels based on non-renewable resources such as fossil fuels need to be replaced with potentially less polluting renewable fuels derived from vegetable or animal biomass, these so-called biofuels, are a reality nowadays and many countries have started the challenge of increasing the use of different types of biofuels, such as ethanol and biodiesel (fatty acid alkyl esters), often mixed with petroleum derivatives, such as gasoline and diesel, respectively. The quantitative determination of these fuel blends using simple, fast and low cost methods based on near infrared (NIR) spectroscopy combined with chemometric methods has been reported. However, advanced biofuels based on a mixture of hydrocarbons or a single hydrocarbon molecule, such as farnesane (2,6,10-trimethyldodecane), a hydrocarbon renewable diesel, can also be used in mixtures with biodiesel and petroleum diesel fuel and the use of NIR spectroscopy for the quantitative determination of a ternary fuel blend of these two hydrocarbon-based fuels and biodiesel can be a useful tool for quality control. This work presents a development of an analytical method for the quantitative determination of hydrocarbon renewable diesel (farnesane), biodiesel and petroleum diesel fuel blends using NIR spectroscopy combined with chemometric methods, such as partial least squares (PLS) and support vector machines (SVM). This development leads to a more accurate, simpler, faster and cheaper method when compared to the standard reference method ASTM D6866 and with the main advantage of providing the individual quantification of two different biofuels in a mixture with petroleum diesel fuel. Using the developed PLS model the three fuel blend components were determined simultaneously with values of root mean square error of prediction (RMSEP) of 0.25%, 0.19% and 0.38% for hydrocarbon renewable diesel, biodiesel and petroleum diesel, respectively, the values obtained were in agreement with those suggested by reference methods for the determination of renewable fuels.1386477-8
Time-based injection approach for monosegmented continuous flow systems and related techniques
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Two-dimensional low resolution raman spectroscopy applied to fast discrimination of clinically relevant microorganisms: a whole-organism fingerprinting approach
The discrimination of the bacteria that cause gastroenteritis through classical microbiological methods is very efficient in the great majority of the cases. However, the high cost of chemicals and the time spent for such identifications, about four days, could generate serious consequences for the patients. Thus, the search for low cost spectroscopic methods which would allow a fast and reagentless discrimination of these microorganisms is extremely relevant. In this work the main microorganisms that cause gastroenteritis: E. coli, S. chroleraesuis, S. flexneri were studied. For each of the microorganisms sixty different dispersions were prepared using physiological solution as solvent and its Raman spectra recorded. The 1D spectra obtained were similar, making it very difficult to differentiate the microorganisms. However, applying the 2D correlation method, it was possible to identify the microorganisms evaluated using the synchronous spectrum as whole-organism fingerprinting in a reduced time interval (~10 h).A diferenciação de bactérias causadoras de gastrenterites através de métodos microbiológicos clássicos é muito eficiente, na maior parte dos casos. Todavia, o elevado custo dos reagentes e o tempo necessário para tais determinações, cerca de 4 dias, podem causar sérias conseqüências, quando os pacientes são crianças, idosos ou adultos com baixa resistência imunológica. Assim, a pesquisa por métodos espectroscópicos de baixo custo, que permitam tais determinações com pouco uso de reagentes e em curtos intervalos de tempo é extremamente relevante. Neste trabalho os principais microrganismos causadores de gastrenterites, E. coli, S. chroleraesuis, S. flexneri foram avaliados. Foram preparadas sessenta dispersões para cada um dos microrganismos, usando solução fisiológica como solvente, e seus espectros adquiridos. Os espectros obtidos foram muito similares, tornando muito difícil a diferenciação dos microrganismos. Entretanto, aplicando a teoria de correlação generalizada em 2D, foi possível diferenciar os microrganismos avaliados usando o espectro síncrono como impressão digital do organismo em um curto intervalo de tempo (~10h).7378Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES
Validação de modelos de calibração multivariada: uma aplicação na determinação de pureza polimórfica de carbamazepina por espectroscopia no infravermelho próximo
Sugar cane (Saccharum officinarum L.) analysis through biospeckle and spectroscopy (NIR)
The objective of this paper was to evaluate the sugar and water content in sugar cane samples by means of two non-destructive techniques in comparison with conventional methods. One non-destructive technique is the Biospeckle, an interaction between the laser and the biological material which provides information about the material. The other technique is the near infrared spectroscopy (NIR). The Biospeckle technique has been constantly used in agricultural engineering. In this paper, the relation between the water and the sugar contents were obtained. The results for the Biospeckle were acquired through the moment of inertia (MI). The data acquired through already consolidated methodologies were used to quantify the samples’ water and sugar contents, correlating to the spectroscopy results and also to the Biospeckle. It was obtained a high determination coefficient (R2 = 0.9287) between the predicted Brix by the model generated by NIR spectroscopy and Brix measured by refractometer. It was also possible to differentiate the water contents of the sugar cane samples both externally lit (husk) and internally lit (cut) by Biospeckle analysis through the calculation of MI. It is possible to evaluate the water content and the sugar content in samples combining Biospeckle and NIR spectroscopy, which are non-invasive and non-destructive methods.7626
Procedimentos analíticos para identificação de antocianinas presentes em extratos naturais
Anthocyanins are among the most important plant pigments. Due to their potential benefits for human health, there is considerable interest in these natural pigments. Nonetheless, there is great difficulty in finding a technique that could provide the identification of structurally similar compounds and estimate the number and concentration of the species present. A lot of techniques have been tried to find the best methodology to extract information from these systems. In this paper, a review of the most important procedures is given, from the extraction to the identification of anthocyanins in natural extracts
Me tomo cinco minutos... me tomo una HSI!
HSI es la sigla inglesa de imagen hiperespectral. En este resumen se presentan los resultados parciales obtenidos como parte del plan de trabajos de una beca externa de Conicet realizada en el Instituto de Química (UNICAMP). El objeto de este trabajo ha sido desarrollar y estudiar los alcances de una metodología alternativa, basada en la espectrometría molecular en la región del infrarrojo cercano (NIR) combinada con métodos quimiométricos, para la clasificación de muestras de té (Camellia sinensis) de acuerdo a su origen geográfico. Para ello, se tomaron imágenes hiperespectrales en la zona del NIR de muestras comerciales de té negro y té verde provenientes de distintos países del Mercosur (Argentina, Paraguay y Brasil). Una HSI es una imagen digital que contiene un espectro molecular por cada pixel, permitiendo revelar y visualizar la distribución espacial de numerosos compuestos químicos. Como consecuencia de esta arquitectura, cada HSI acarrea una gran cantidad de datos dispuestos en forma de tres dimensiones, 2 (dos) referidas a la distribución de pixeles y la tercera con los valores correspondientes a cada espectro, lo que hace necesario emplear técnicas de análisis multivariante de imágenes para obtener información relevante de las mismas. Resultados y ConclusionesEn este trabajo se presentan los resultados obtenidos para 15 muestras de té verde. Las muestras fueron comprimidas a pastillas previo a su análisis. Se tomaron HSI de 3 puntos diferentes en cada muestra utilizando un sistema de obtención de imágenes hiperespectrales (Perkin-Elmer Spotlight 400N) en la región espectral de 4000 a 7800 cm-1 generando una HSI (16×16×254) en cada punto. Una vez importados los archivos, los hipercubos de cada imagen se descompusieron en matrices aumentadas por columna (unfolding) que fueron analizadas mediante el método MCR-ALS (1-2). El método MCR-ALS permite obtener los perfiles de concentración y espectros de los componentes puros presentes en cada muestra. Cinco (5) componentes resultaron óptimos para hacer converger el algoritmo, con una falta de ajuste inferior al 1,0%. Los resultados de los perfiles de abundancia de cada componente se utilizaron luego para la aplicación de diferentes métodos de clasificación multivariante, LDA, PLS-DA y SVM-DA. Los resultados obtenidos demostraron que el método SVM-DA fue el que tuvo mejor desempeño y fue capaz de modelar la matriz de datos con una taza de acierto superior al 90% cuando se utilizó el método de validación cruzada por lotes (10-fold cross validation).Fil: Hidalgo, Melisa Jazmin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Dantas, William. Universidade Estadual Do Campinas. Instituto de Química.; BrasilFil: Pellerano, Roberto Gerardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; ArgentinaFil: Poppi, Ronei Jesus. Universidade Estadual Do Campinas. Instituto de Química.; Brasil9º Congreso Argentino de Química analíticaRío CuartoArgentinaAsociación Argentina de Química Analític
Development of an algorithm for identification and correction of spikes in Raman imaging spectroscopy
Raman imaging spectroscopy is a highly useful analytical tool that provides spatial and spectral information on a sample. However, CCD detectors used in dispersive instruments present the drawback of being sensitive to cosmic rays, giving rise to spikes in Raman spectra. Spikes influence variance structures and must be removed prior to the use of multivariate techniques. A new algorithm for correction of spikes in Raman imaging was developed using an approach based on comparison of nearest neighbor pixels. The algorithm showed characteristics including simplicity, rapidity, selectivity and high quality in spike removal from hyperspectral images.612615Fundação 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
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