Odor sensor using quartz crystal microbalance coated with molecular recognition membrane
Abstract
Quartz crystal microbalance (QCM) odor sensor coated with films of with acrylic-acid-film with different functional groups, methcrylic-acid-films with different functional group and styrene-film as the molecular recognition membrane are prepared using plasma chemical vapor deposition (CVD) method. The sensor coated with acrylic acid thin film as the molecular recognition membrane exhibits an excellent selectivity and a high sensitivity for ammonia and amine gases. The effect of the functional groups on the sensor characteristics is also investigated.
In this paper, we demonstrate a novel quartz crystal microbalance (QCM) gas sensor with nanowires of a molecular recognition membrane (MRM), which is fabricated by the nanosize particle-beam irradiation technique. It was found that the QCM sensor with poly-acrylic acid MRM exhibited an excellent selectivity for ammonia gas. It is confirmed that the sensitivity of the QCM sensor with nanowires of poly-acrylic acid MRM is higher than that of the sensor with a common poly-acrylic acid MRM. Furthermore, we investigate the influence of the functional group of MRM on the gas sensing characteristics of the QCM gas sensor.
Quartz resonator gas sensors coated with films of styrene, allylamine, acrylic acid or methacrolein as the molecular recognition membrane are prepared using plasma-polymerized CVD. The sensor coated with acrylic acid film exhibits an excellent selectivity and a high sensitivity for ammonia gas. This sensor is useful in a sensor array in conjunction with pattern recognition analysis for identification of gases and odors.
Transient response curves for exposure to aromas from several kinds of alcohols are observed using a Japanese-lacquer-film-coated quartz resonator gas sensor. The shape of the transient response curves strongly depends on the ethanol concentration of alcohols. The pattern recognition analysis using principal component or neural network analysis is carried out using four parameters which characterize the shape of the transient response curve. The recognition probability using neural network analysis for aromas from alcohols is 100% for 25 trials.
Although the identification of various kinds of odors in our daily life is important, few artificial odor sensing systems have been reported. From the biomimetic point of view, the use of plural sensors to recognize the output pattern of a sensor array for such identification is very promising. An odor sensor using a quartz-resonator array and neural-network pattern recognition has been previously reported. In the present study, optimization of the sensor-array components has been made and the recognition probability has been improved.
Transient response curves for aromas from ethanol solutions or several kinds of alcohols with different ethanol concentrations are observed using CH3Si(OCH3)3 a sol-gel-film-coated quartz crystal resonator gas sensor. The pattern recognition analysis using principal component analysis or neural network analysis is carried out using three parameters which characterize the transient response curves. The recognition probability of neural network for five kinds of alcohols such as Japanese Sake (ethanol concentration 15%), Shoutyuu (25%), cognac (45%), vodka (50%) and vodka (95%) is 100% for 50 trials.
The functional design of the smart electronic nose using polymer-film-coated quartz resonator gas sensors, based on the solubility parameter of sensing membrane and gases, is carried out in order to develop a sensor with excellent selectivity and high sensitivity for harmful gases such as toluene, acetaldehyde and ammonia gases. The polymer films such as propylene-butyl, polycarbonate and acrylic-resin of which the solubility parameter almost coincide with that of toluene, acetaldehyde and ammonia gases, respectively, are chosen as a sensing membrane material coated on the quartz resonator. It is found that propylene-butyl-film-coated quartz resonator gas sensor exhibits a high sensitivity and an excellent selectivity for toluene and p-xylene gas, as expected from a functional design based on solubility parameter. It is also found that polycarbonate-film-coated and acrylic-resin film-coated sensors exhibit high sensitivity and excellent selectivity for acetaldehyde and ammonia, respectively, also as expected. The results strongly suggest that solubility parameter is effective in the functional design of the sensing membrane of quartz resonator gas sensors. The successful identification of a specific gas is possible through the principal component pattern recognition analysis of the transient responses of each sensor for gases.
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