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Título
Enose lab made with vacuum sampling: Quantitative applications
Autor
Año del Documento
2022
Editorial
MDPI
Descripción
Producción Científica
Documento Fuente
Chemosensors, 2022, Vol. 10, Nº. 7, 261
Resumen
A lab-made electronic nose (Enose) with vacuum sampling and a sensor array, comprising nine metal oxide semiconductor Figaro gas sensors, was tested for the quantitative analysis of vapor–liquid equilibrium, described by Henry’s law, of aqueous solutions of organic compounds: three alcohols (i.e., methanol, ethanol, and propanol) or three chemical compounds with different functional groups (i.e., acetaldehyde, ethanol, and ethyl acetate). These solutions followed a fractional factorial design to guarantee orthogonal concentrations. Acceptable predictive ridge regression models were obtained for training, with RSEs lower than 7.9, R2 values greater than 0.95, slopes varying between 0.84 and 1.00, and intercept values close to the theoretical value of zero. Similar results were obtained for the test data set: RSEs lower than 8.0, R2 values greater than 0.96, slopes varying between 0.72 and 1.10, and some intercepts equal to the theoretical value of zero. In addition, the total mass of the organic compounds of each aqueous solution could be predicted, pointing out that the sensors measured mainly the global contents of the vapor phases. The satisfactory quantitative results allowed to conclude that the Enose could be a useful tool for the analysis of volatiles from aqueous solutions containing organic compounds for which Henry’s law is applicable.
Materias (normalizadas)
Electronics - Dectectors
Electrónica - Sensores
Materias Unesco
2203 Electrónica
3312 Tecnología de Materiales
Palabras Clave
Electronic nose
Nariz electrónica
MOS sensor array
Conjunto de sensores MOS
Quantitative analysis
Análisis cuantitativo
Ridge regression
Regresión de cresta
ISSN
2227-9040
Revisión por pares
SI
Patrocinador
Fundación para la Ciencia y la Tecnología (FCT, Portugal) y Fondo Europeo de Desarrollo Regional (FEDER) under Programme PT2020 - (grants UID/AGR/00690/2019 y LA/P/0007/2020)
Version del Editor
Propietario de los Derechos
© 2022 The Authors
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
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