Utilización de una Nariz Electrónica elaborada a partir de MOS para la evaluación y diferenciación de la calidad del pisco peruano
Date
2023-08-31
Journal Title
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Publisher
Pontificia Universidad Católica del Perú
Abstract
El objetivo de la presente tesis es realizar la diferenciación de las variedades de Pisco (Italia
y Quebranta) que cumplan con la Denominación de Origen, así como la diferenciación del
Pisco Quebranta con mezclas adulteradas con aguardiente de caña en diferentes
proporciones. Para esta investigación se utilizó una nariz electrónica conformada por un
arreglo de sensores basados en óxidos metálicos (SnO2 y TiO2) y composites a base de
mezcla de óxidos en diferentes proporciones: (SnO2/TiO2) 1:4, (SnO2/TiO2) 1:2 y
(SnO2/TiO2) 4:1. Estos materiales fueron dopados con Pt y/o Pd y adicionalmente fueron
recubiertos con zeolita-Y. Este material funciona como un tamiz molecular que discrimina
moléculas por su tamaño y forma. Para la preparación de los óxidos metálicos se utilizó el
método sol-gel, y para el dopaje se utilizó el método por impregnación húmeda. La
caracterización de los materiales se realizó mediante las siguientes técnicas: DRX, SEMEDS
y FRX, con las que se lograron determinar las estructuras cristalinas y se pudo
confirmar la presencia de los dopantes. Asimismo, por espectroscopía Raman se confirmó
la presencia de vacancia de oxígenos superficiales, lo cual fue asociado con el incremento
en la respuesta del sensor.
La información de las respuestas obtenidas del análisis de sensado fue procesada
utilizando la técnica de Análisis de Componentes Principales (PCA), esta técnica es un
método estadístico multivariado que produce nuevas variables, denominadas componentes
principales, a partir de transformaciones lineales de las variables originales, de modo tal
que estas nuevas variables maximicen la Varianza Total que indica el nivel de confianza de
los resultados. El PCA permite visualizar la diferenciación entre las variedades de pisco, así
como la diferenciación frente a un pisco adulterado.
Los sensores que mostraron una buena diferenciación de las muestras de Pisco según las
variedades Italia y Quebranta son: (SnO2-TiO2)1:4, (SnO2/TiO2)1:2, (SnO2/TiO2) 4:1, 0.05%
Pt (SnO2/TiO2) 4:1, 0.1% Pt (SnO2/TiO2)4:1, 0.05% -0.05% Pt-Pd(SnO2/TiO2) 4:1, 0.05% -
0.1% Pt-Pd(SnO2/TiO2) 4:1, 0.1% Pt/SnO2 y 0.05% -0.1% Pt/SnO2.
El sensor (TiO2/SnO2) 4:1 es el que muestra una mayor sensibilidad y mayor capacidad
para diferenciar las mezclas de Pisco con aguardiente de caña (AC), especialmente en las
mezclas con menor concentración de AC. Asimismo, la capacidad de diferenciación mejora
con el recubrimiento de zeolita-Y en los siguientes sensores: 0.1% Pt/SnO2 y 0.05%-0.1%
Pt-Pd/SnO2.
The aim of this thesis is to differentiate the varieties of Pisco (Italia and Quebranta) that act in accordance with the Denomination of Origin, as well as the differentiation of Pisco Quebranta with mixtures adulterated with cane liquor in different proportions. For this research, an electronic nose was used, constituted by an array of sensors based on metal oxides (SnO2 and TiO2) and composites based on oxides mixtures in different proportions: (SnO2/TiO2) 1:4, (SnO2/TiO2) 1:2 and (SnO2/TiO2) 4:1. These materials were doped with Pt and/or Pd and additionally they were coated with zeolite-Y. This material works as a molecular sieve that discriminates molecules by their size and shape. For the preparation of metal oxides, the sol-gel method was used. And for doping, the wet impregnation method was used. The characterization of the materials was performed using the following techniques: XRD, SEM-ED and XRF, with these techniques was possible the determination of the crystalline structures and the presence of dopants was confirmed. Raman spectroscopy confirmed the presence of surface oxygen vacancies, it was associated with the increase of the sensor response. The information obtained from the sensing analysis was processed using the Principal Component Analysis (PCA) technique. This technique is a multivariate statistical method that produces new variables, called principal components from linear transformations of the original variables, in such a way that these new variables maximize the Total Variance that indicates the confidence level of the results. The PCA allows to visualize the differentiation between the varieties of Pisco, as well as the differentiation against an adulterated Pisco. The sensors that showed a good differentiation of the Pisco samples according to the Italia and Quebranta varieties are: (SnO2/TiO2)1:4, (SnO2/TiO2)1:2, (SnO2/TiO2) 4:1, 0.05% Pt (SnO2/TiO2) 4:1, 0.1% Pt (SnO2/TiO2)4:1, 0.05% -0.05% Pt-Pd(SnO2/TiO2) 4:1, 0.05% -0.1% Pt-Pd(SnO2/TiO2) 4:1, 0.1% Pt/SnO2 and 0.05% -0.1% Pt/SnO2. The (SnO2/TiO2) 4:1 sensor is the one that shows greater sensitivity and greater capacity to differentiate the mixtures of Pisco with cane liquor (CA), especially in the mixtures with lower concentration of CA. Besides, the differentiation capacity improves with the zeolite-Y coating in the following sensors: 0.1% Pt/SnO2 and 0.05%-0.1% Pt-Pd/SnO2.
The aim of this thesis is to differentiate the varieties of Pisco (Italia and Quebranta) that act in accordance with the Denomination of Origin, as well as the differentiation of Pisco Quebranta with mixtures adulterated with cane liquor in different proportions. For this research, an electronic nose was used, constituted by an array of sensors based on metal oxides (SnO2 and TiO2) and composites based on oxides mixtures in different proportions: (SnO2/TiO2) 1:4, (SnO2/TiO2) 1:2 and (SnO2/TiO2) 4:1. These materials were doped with Pt and/or Pd and additionally they were coated with zeolite-Y. This material works as a molecular sieve that discriminates molecules by their size and shape. For the preparation of metal oxides, the sol-gel method was used. And for doping, the wet impregnation method was used. The characterization of the materials was performed using the following techniques: XRD, SEM-ED and XRF, with these techniques was possible the determination of the crystalline structures and the presence of dopants was confirmed. Raman spectroscopy confirmed the presence of surface oxygen vacancies, it was associated with the increase of the sensor response. The information obtained from the sensing analysis was processed using the Principal Component Analysis (PCA) technique. This technique is a multivariate statistical method that produces new variables, called principal components from linear transformations of the original variables, in such a way that these new variables maximize the Total Variance that indicates the confidence level of the results. The PCA allows to visualize the differentiation between the varieties of Pisco, as well as the differentiation against an adulterated Pisco. The sensors that showed a good differentiation of the Pisco samples according to the Italia and Quebranta varieties are: (SnO2/TiO2)1:4, (SnO2/TiO2)1:2, (SnO2/TiO2) 4:1, 0.05% Pt (SnO2/TiO2) 4:1, 0.1% Pt (SnO2/TiO2)4:1, 0.05% -0.05% Pt-Pd(SnO2/TiO2) 4:1, 0.05% -0.1% Pt-Pd(SnO2/TiO2) 4:1, 0.1% Pt/SnO2 and 0.05% -0.1% Pt/SnO2. The (SnO2/TiO2) 4:1 sensor is the one that shows greater sensitivity and greater capacity to differentiate the mixtures of Pisco with cane liquor (CA), especially in the mixtures with lower concentration of CA. Besides, the differentiation capacity improves with the zeolite-Y coating in the following sensors: 0.1% Pt/SnO2 and 0.05%-0.1% Pt-Pd/SnO2.
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Keywords
Pisco--Diferenciación del producto--Automatización, Sensores--Aplicaciones industriales, Semiconductores de óxido metálico--Aplicaciones industriales
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