Linear Thermal Expansion Coefficient of Silicon from 293 to 1000 K

As a part of the program to establish a thermal expansion standard, the linear thermal expansion coefficients of single-crystal silicon have been determined in the temperature range 293 to 1000 K using a dilatometer which consists of a heterodyne laser Michelson interferometer and gold versus platinum thermocouple. The relative standard deviation of the measured values from those calculated from the best least-squares fit was 0.21%. The relative expanded uncertainty in the measurement was estimated to be 1.1 to 1.5% in the temperature range, based upon an analysis of thirteen standard uncertainties. The present data are compared with the data previously obtained by similar dilatometers and the standard reference data for the thermal expansion coefficient of silicon, recommended by the Committee on Data for Science and Technology (CODATA). The present data are in good agreement with the most recently reported data but not with the earlier high-temperature data used to evaluate the standard reference data, which suggests a need for the reevaluation of the standard reference data for the thermal expansion coefficient of silicon at temperatures above 600 K.     

Extended SPRT for structural change detection of time series based on a multiple regression model

It is important to detect a structural change in a time series quickly as a trigger to remodeling the forecasting model. The well-known Chow test has been used as the standard method for detecting change, especially in economics. However, we have proposed the application of the sequential probability ratio test (SPRT) for detecting the change in single-regression modeled time-series data. In this article, we show experimental results using SPRT and the Chow test when applied to time-series data that are based on multiple regression models. We also clarify the effectiveness of SPRT compared with the Chow test in its ability to detect change early and correctly, and its computational complexity. Moreover, we extend the definition of the point at which structural change is detected with the SPRT method, and show an improvement in the accuracy of change detection.     

Transverse zero sound in superfluid3He-B

The dispersion of the transverse zero sound in superfluid³He-B in the colisionless limit is studied theoretically. The dispersion is most easily understood as due to strong coupling between two distinct modes; the original zero-sound mode which is present in normal liquid and the collective mode with energy gap _t (T) proportional to (T), the temperature-dependent energy gap.Work supported by the National Science Foundation.     

Handwritten digit recognition: benchmarking of state-of-the-art techniques

This paper presents the results of handwritten digit recognition on well-known image databases using state-of-the-art feature extraction and classification techniques. The tested databases are CENPARMI, CEDAR, and MNIST. On the test data set of each database, 80 recognition accuracies are given by combining eight classifiers with ten feature vectors. The features include chaincode feature, gradient feature, profile structure feature, and peripheral direction contributivity. The gradient feature is extracted from either binary image or gray-scale image. The classifiers include the k-nearest neighbor classifier, three neural classifiers, a learning vector quantization classifier, a discriminative learning quadratic discriminant function (DLQDF) classifier, and two support vector classifiers (SVCs). All the classifiers and feature vectors give high recognition accuracies. Relatively, the chaincode feature and the gradient feature show advantage over other features, and the profile structure feature shows efficiency as a complementary feature. The SVC with RBF kernel (SVC-rbf) gives the highest accuracy in most cases but is extremely expensive in storage and computation. Among the non-SV classifiers, the polynomial classifier and DLQDF give the highest accuracies. The results of non-SV classifiers are competitive to the best ones previously reported on the same databases.     

Handwritten digit recognition: investigation of normalization and feature extraction techniques

The performance evaluation of various techniques is important to select the correct options in developing character recognition systems. In our previous works, we have proposed aspect ratio adaptive normalization (ARAN) and have evaluated the performance of state-of-the-art feature extraction and classification techniques. For this time, we will propose some improved normalization functions and direction feature extraction strategies and will compare their performance with existing techniques. We compare ten normalization functions (seven based on dimensions and three based on moments) and eight feature vectors on three distinct data sources. The normalization functions and feature vectors are combined to produce eighty classification accuracies to each dataset. The comparison of normalization functions shows that moment-based functions outperform the dimension-based ones and the aspect ratio mapping is influential. The comparison of feature vectors shows that the improved feature extraction strategies outperform their baseline counterparts. The gradient feature from gray-scale image mostly yields the best performance and the improved NCFE (normalization-cooperated feature extraction) features also perform well. The combined effects of normalization, feature extraction, and classification have yielded very high accuracies on well-known datasets.     

Plasma behavior in a non‐equilibrium disk MHD generator with a spatially non‐uniform seed fraction

The influence of azimuthal non‐uniformity of the seed fraction on plasma structure and performance in a non‐equilibrium disk MHD generator is investigated with a two dimensional r–θ numerical simulation. It is found that a locally high seed fraction causes mainly non‐uniformity of gas‐dynamical properties, whereas a locally low seed fraction develops a non‐uniform plasma. Both locally high and low seed fractions reduce generator performance considerably. These results suggest a spatially uniform seed fraction should be required for high power generation. ©1999 Scripta Technica, Electr Eng Jpn, 126(4): 48–54, 1999     

Thick-film coating of hexaaluminate catalyst on ceramic substrates for high-temperature combustion

Structural and chemical stabilities of substituted hexaaluminate catalyst films coated on some ceramic substrates were investigated for high-temperature combustion applications. The thermal stability of the hexaaluminate catalyst films on -SiC substrate was greatly enhanced by the insertion of both, a neat hexaaluminate and mullite intermediate layer. Pure alumina substrate was preferable in depositing the substituted hexaaluminate catalyst film to pure mullite, mullite-zirconia composite, or partially stabilized zirconia substrates. The thermal stability of the hexaaluminate catalyst films, coated on these oxide ceramic substrates, greatly depended on the extent of diffusion of components between the film and substrate at high temperatures. The substituted hexaaluminate microparticles in the film rearranged during the sintering process above 1400°C, and their (00l) plane oriented parallel to the surface of the substrate. Manganese introduced in the substituted hexaaluminate films or disks gradually decreased with an increase in the heat-treatment temperature because of its volatilization.     

Design of Ceramic Materials for Chemical Sensors: SmFeO3 Thick Films Sensitive to NO2

Ultrafine SmFeO₃ powders were prepared by the thermal decomposition at 700°C of the corresponding hexacyanocomplex, Sm[Fe(CN)₆]·4H₂O. These powders were used for the preparation of pastes which were deposited as thick films on alumina substrates with comb-type Au electrodes. The films were fired at different temperatures in the 800-1000°C range. The content of α-terpineol, a component of the organic vehicle, was varied in the range 0.0046-4 wt%. The microstructure, the chemical composition at the surface, the electrical conductivity, and the NO₂ sensing properties of the films were investigated. The content of α-terpineol strongly influenced the electrical conductivity and its activation energy. A significant reduction in the NO₂ response was observed for the films containing smaller amounts of α-terpineol, together with an increase in conductivity. On the other hand, the largest NO₂ response was observed for the films fired at 1000°C when 4 wt% of α-terpineol was used. Such increase in conductivity is attributed to a different oxygen surface layer on the SmFeO₃ surface, which is induced by the decomposition reaction of α-terpineol during sintering. The materials processing parameters are thus of primary concern for the NO₂ sensing properties of the SmFeO₃ thick films. The correlations found between activation energy, NO₂ sensitivity, and materials characteristics (influenced by the preparation parameters) are reported. These correlations can be used to design the gas-sensing properties of SmFeO₃ thick films for the optimization of their sensing characteristics.     

Carbon nanotube-dependent synthesis of armchair graphene nanoribbons

Sub-nanometer armchair graphene nanoribbons(GNRs)with moderate band gap have great potential towards novel nanodevices.GNRs can be synthesized in the confined t...