Byeongdeok Yea

The concentration-estimation of inflammable gases with a semiconductor gas sensor utilizing neural networks and fuzzy inference

This paper proposes a method to estimate the concentration of inflammable gases from transient response patterns which a semiconductor gas sensor shows under periodic heating conditions. The procedure and effectiveness of the method were illustrated for five selected gases of butane, hydrogen, LP gas, methane, and town gas. The response patterns obtained were found to be well reproducible and specific to the kinds of gases. Frequency analysis could be applied easily to the response patterns because of their periodic characteristics, allowing one to extract D.C. and A.C. components of them by fast Fourier transform. The A.C. components remained almost unchanged irrespective of the variations of ambient temperature and/or humidity and gas concentration, proving themselves to be adequate for the concentration-independent discrimination of gases. The D.C. components, on the other hand, depended largely on the variations of gas concentration, being useful for the estimation of gas concentration. It was shown that the discrimination of the five gases supported by a three-layered back propagation neural network as well as the estimation of their concentrations assisted by fuzzy inference were successfully performed.

The discrimination of many kinds of odor species using fuzzy reasoning and neural networks

Abstract To discriminate many kinds of odor species, a system composed of multiple gas sensors and neural networks is proposed. Three commercial gas sensors are used for the system, and four kinds of inflammable gases, four kinds of fragrant smells and one kind of offensive odor are introduced as odor species. The discrimination is performed in two steps to increase the efficiency of the system; the first step is classification of the odor group, that is, the groups of inflammable gases, fragrant smells and offensive odor; the second step is the discrimination of individual odor species in the classified group. 100% group classification rate is obtained by the use of simple fuzzy reasoning and the steady-state response patterns of the sensors. The discrimination of individual odor species is performed with a neural network and transient response patterns of the sensors and a high discrimination rate (99.2%) is achieved.

Analysis of the sensing mechanism of tin dioxide thin film gas sensors using the change of work function in flammable gas atmosphere

Abstract To investigate the sensing mechanism of SnO 2 thin films prepared with the targets-facing type sputtering method, the change of work function of the films was measured with the Kelvin method, and was compared with the change of resistance when they were exposed to hydrogen. The change of work function in the same concentration of hydrogen shows different trends according to the variation of the film temperature and this result reveals that there exist three different models of hydrogen interaction with the film surface or with the oxygen adsorbates on the surface, which depend on the film temperature at that time. The change of resistance of the films shows quick saturation, while that of the work function has trends of slow and continuous decreasing; from these results, it is concluded that the adsorption or desorption of the oxidizing or reducing gases on the film surface are contributed mainly to the change of potential barrier of grain boundaries of the films.

Investigation of Substrate-dependent Characteristics of SnO2 Thin Films with Hall Effect, X-Ray Diffraction, X-Ray Photoelectron Spectroscopy and Atomic Force Microscopy Measurements

SnO2 thin films of 100 nm in thickness were prepared on glass and alumina substrates with targets-facing type sputtering apparatus to investigate the substrate-dependent characteristics of the films. The sensitivity of the films is measured in flammable gas atmosphere (hydrogen, butane and methane, 5000 ppm), and it revealed that the SnO2 films on alumina substrates showed better sensitivity for all introduced gases than the films on glass substrates. Hall effect, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM) measurements were performed to clarify the difference of the sensitivity, and it is concluded as follows: 1) The variation of carrier concentration of the films on alumina substrates is larger than those on glass substrates when they are exposed to flammable gases. 2) The structure of the films on alumina substrates is similar to that of SnO2 powder. 3) The film on an alumina substrate contains more oxygen impurities than that on a glass substrate, which can be considered to cause the large variation of carrier concentration. 4) Surface area of the films on alumina substrates is wider than that of the films on glass substrates.

IMPROVEMENT OF CONCENTRATION-ESTIMATION ALGORITHM FOR INFLAMMABLE GASES UTILIZING FUZZY RULE-BASED NEURAL NETWORKS

Abstract We have proposed an algorithm which can discriminate inflammable gases and estimate their concentration with a semiconductor gas sensor under the periodic operation in our previous paper. In this paper, we propose fuzzy rule-based neural networks, which are composed of two back propagation neural networks, to improve the estimation accuracy and to reduce the time and efforts for creation and tuning of the membership functions. The proposed network is examined in estimating the concentrations of three kinds of inflammable gases, that is, butane, hydrogen and methane, and it is proved that the results are more accurate than those obtained with simplified fuzzy inference.

Microscopic Analysis of the Degradation Mechanism of Gallium Arsenide Metal-Semiconductor Field-Effect Transistor

The microscopic degradation mechanism of the recess surface of GaAs metal- semiconductor field-effect transistor (MESFET) after a long duration aging is analyzed using a transmission electron microscope (TEM), Raman scattering and several other analytical methods. Crystallographic arsenic (As) and amorphous gallium (Ga) precipitated after the aging test. Raman scattering during device operation indicates that the temperature of the drain side is higher than that of the source side. Light emission by hot carriers is observed at the drain side of the device during operation. The degradation of the device is accelerated by the hot carriers generated by a thermionic field emission at the high-temperature drain side.

Light Emission and Surface States Annealing on GaAs Metal Semiconductor Field-Effect Transistor

The annealing mechanism of surface states in the gallium arsenide metal semiconductor field-effect transistor (GaAs MESFET) is investigated by measuring the light-emission characteristics and excess gate currents generated by hot-carriers. Nonuniform light emission is observed when the Schottky junction is reverse biased, and the nonuniformity is increased with temperature. On the other hand, uniform and strong emission is observed under RF operation even when the device is biased with a deep pinch-off condition. The reverse and forward Schottky current caused by RF swing may not be a main emission mechanism under RF operation. Light emissions due to impact ionization and thermionic field emission are observed separately. The light intensity of the thermionic field emission has a weak temperature coefficient, while that of the impact ionization has a strong negative temperature coefficient. The decreasing rate of the surface states depends on the intensity and the distribution of the light emission during the operation.

An advanced gas discrimination method utilizing the periodic operation of a semiconductor gas sensor

This paper proposes a concentration-independent inflammable gas discrimination method utilizing transient response patterns of a semiconductor gas sensor. In the proposed method, the heater voltage of the sensor is changed periodically for a certain time interval after a gas sample is introduced to obtain accurate and uniform information from the response patterns regardless of the surrounding temperature variations. To realize concentration-independent gas discrimination, the DC components of the periodic response patterns which depend largely on the variation of ambient temperature and gas concentration are removed by applying a Fourier transform, and only AC components which show little change on their shape in spite of the same variations are used for pattern matching. The method is examined in discriminating five kinds of inflammable gases with a three layered backpropagation neural network, and average 99% discrimination rate is achieved.

Decrease in Surface States on GaAs Metal-Semiconductor Field-Effect Transistor by High Temperature Operation

The decrease mechanism of plasma-induced surface states in a GaAs metal-semiconductor field-effect transistor (MESFET) during high temperature operation has been studied by means of high temperature operational tests, drain current transient analysis and three-terminal gate current measurements. The energy level of trapped electrons in the surface states distributes widely in the band-gap, and its activation energy does not change after decreasing the density of surface states. In order to decrease the surface states effectively, hot-carriers generated by accelerated channel electrons under high temperature operation are required.

Neurofuzzy approach to the concentration-estimation of inflammable gas

Neurofuzzy approach to the estimation of the concentration of inflammable gas is proposed in this paper. The membership functions for the pur pose are made up of Fourier-transformed output signals of a semiconductor gas sensor (TGS 813). The resulting membership functions are used for training a neural nctwork which has the ability of learning fuzzy rules. Once the neural network is trained and verified to be pcrforminc, satisfactorily, it can be used to tune the membership functions automatically with the output signals of the sensor, and more precise estimation of the concentration can be expected, consequently. The proposed method is examined with the concentration-estimation of hydrogen and, as a result, good performance is achieved.