TY - JOUR
T1 - Implementación y evaluación de una nariz electrónica para la detección de alcoholes lineales
AU - Paredes-Doig, Ana Lucía
AU - Sun Kou, María del Rosario
AU - Picasso-Escobar, Gino
AU - Doig-Camino, Elizabeth
AU - Comina, Germán
N1 - Publisher Copyright:
© 2016, Universidad Nacional de Colombia. All rights reserved.
PY - 2016/5/1
Y1 - 2016/5/1
N2 - An electronic nose for the detection of alcohols, easy to use and inexpensive as compared to traditional electronic noses, was developed. This nose is based on four SnO2 gas sensors (two commercial and two homemade), an irregular pneumatic system, hardware and a software for data acquisition and a software for pattern recognition. The nose behavior and the working conditions with vapor samples of alcohols (methanol, ethanol, n-butanol and 1-octanol) were evaluated. Alcohols could be detected with the array of prepared sensors and could be also differentiated from each other by using principal component analysis (PCA). The detection order for linear alcohols followed the order: methanol > ethanol > n-butanol > 1- octanol. It was also found that by using PCA and performing a standardization of data in software pattern recognition so, the total variance of such information increases from 76% up to 85%. This result confirms that a simple and inexpensive nose can rank well the tested samples.
AB - An electronic nose for the detection of alcohols, easy to use and inexpensive as compared to traditional electronic noses, was developed. This nose is based on four SnO2 gas sensors (two commercial and two homemade), an irregular pneumatic system, hardware and a software for data acquisition and a software for pattern recognition. The nose behavior and the working conditions with vapor samples of alcohols (methanol, ethanol, n-butanol and 1-octanol) were evaluated. Alcohols could be detected with the array of prepared sensors and could be also differentiated from each other by using principal component analysis (PCA). The detection order for linear alcohols followed the order: methanol > ethanol > n-butanol > 1- octanol. It was also found that by using PCA and performing a standardization of data in software pattern recognition so, the total variance of such information increases from 76% up to 85%. This result confirms that a simple and inexpensive nose can rank well the tested samples.
KW - Alcohol classification
KW - Array of sensors
KW - Electronic nose
KW - Gas sensors
KW - PCA
KW - Tin oxide
UR - http://www.scopus.com/inward/record.url?scp=85006054024&partnerID=8YFLogxK
U2 - 10.15446/rev.colomb.quim.v45n2.60393
DO - 10.15446/rev.colomb.quim.v45n2.60393
M3 - Artículo
AN - SCOPUS:85006054024
SN - 0120-2804
VL - 45
SP - 12
EP - 18
JO - Revista Colombiana de Quimica
JF - Revista Colombiana de Quimica
IS - 2
ER -