Phase evolution and <110>-orientation mechanism in RTGG-processed BaTiO3 ceramics with electrical properties

The <110>-oriented BaTiO₃ ceramics were fabricated using BaCO₃ matrix and H_1.08Ti_1.73O₄.nH₂O (HTO) template particles, and the mechanism of BaTiO₃ phase formation was investigated. The dielectric, ferroelectric, and piezoelectric properties were also investigated. The transformation of the HTO phase into the TiO₂ bronze or TiO₂ (B) phase was observed at 600°C, where the BaTiO₃ nucleation was accompanied by the formation of a Ba₂TiO₄ phase. The TiO₂ phase reacted with the Ba₂TiO₄ phase at 800°C to give a BaTiO₃ phase, whereas its reaction with the BaTiO₃ resulted in the formation of BaTi₂O₅ phase that got decomposed into BaTiO₃ and Ba₆Ti₁₇O₄₀ phase at sintering temperature ≥1300°C. Sintering with samples’ embedding in BaTiO₃ powders prevented the formation of the Ba₆Ti₁₇O₄₀ secondary phase. The crystallographic orientation along the <110> direction (F₁₁₀) was developed by the epitaxial grain growth mechanism. In addition to the contribution of the grain-size increment for enhancing the F₁₁₀, the preservation of the platelike structure was also found to have a significant impact. The ceramics prepared by the embedded sintering (grain size ≈12.4 µm and F₁₁₀ = 83%) exhibited the room-temperature dielectric constant of 1708 and piezoelectric strain constant of 445 pm/V, which are higher than those of the BaTiO₃ ceramics with randomly oriented grains.     

Differential Sintering by Improper Selection of Sintering Parameters during Pulse Electric Current Sintering

Recently, we reported on the retention of fine-grained micro-structure in Al₂O₃/3 vol% 3Y-ZrO₂ composites using the pulse electric current sintering (PECS) technique. It was demonstrated that a high heating rate is beneficial for the retention of fine grains and homogeneous microstructure. As there are few reports on microstructural inhomogeneity and excessive grain growth in compacts densified by the PECS technique, we carried out a series of experiments on monolithic alumina by varying the sintering parameters and discussed the characteristic results. All specimens that were densified under selective sintering conditions attained high density (∼99% of the theoretical density) at 1250°3C in > 5 min. The average fracture strength of monolithic alumina was observed to be 741 ± 25 MPa and the fracture toughness was 2.2 MPa.m <^1/2, and these were reasoned out to small grains. However, compacts sintered under very low compaction pressure attained ∼92%-93% of the theoretical density, and these specimens had undesirable microstructural inhomogeneity owing to differential sintering. Hence, in the present study, we address the problem of differential sintering.     

Dissolution and Separation of Ruthenium in Borosilicate Glass

The behavior of ruthenium oxide (RuO₂) in aluminoborosilicate glass used for the stabilization of nuclear waste was investigated. It was found that 0.025 mass% RuO₂ dissolved as Ru⁴⁺ in the glass at 1400°C, which caused the glass to turn yellow. When the RuO₂ amount was 0.05 mass%, needle-shaped crystals formed in the glass during slow cooling. If the added amount exceeded 0.1 mass% and the cooling rate was slow, it separated rapidly and the glass became pale after cooling. No dissolution of ruthenium was detectable after melting at 1200°C.     

Three-dimensional medical image recognition of cancer of the liver by a revised radial basis function (RBF) neural network algorithm

In this study, we propose a revised radial basis function (RBF) neural network algorithm and apply this algorithm to computer-aided diagnosis (CAD) of the liver. First, the revised RBF neural network algorithm is applied to recognition of the liver regions, and the recognition results are compared with those obtained using the conventional RBF neural network and the conventional multilayered neural network trained using the back-propagation algorithm. It is shown that the revised RBF neural network is accurate, and is a useful method because the parameters are automatically determined. Then, the revised RBF neural network is applied to CAD of the liver cancer called hepatocellular carcinoma (HCC).     

A Knowledge-Based Software Process Simulation Model

In this paper we propose a new software development process simulation model. The model can predict variations of productivity based on dynamic changes in the developer's knowledge structure. An important concept of the model is that a developer's productivity is influenced by the developer's knowledge. Moreover, a developer can acquire new knowledge by executing activities of a project. In other words, the developer's knowledge structure changes during the project. The knowledge structure is defined using a cognitive map that consists of knowledge elements and prerequisite relationships among the knowledge elements. By adding the specific developer's knowledge and the specific project workload to the knowledge structure, an increment of the developer's knowledge and the project progress are calculated into the model. The simulation results are useful for making project plans including technical reviews, which are an efficient technique for acquiring new knowledge. The simulation model can predict what knowledge should be discussed in the technical review, when the review should be held, and who the members of the review should be. The simulation results help managers make the most appropriate and executable project plan.     

High-Accuracy Analysis of Beams of Bimodulus Materials

Recently, several authors have treated the problems of bending of beams of bimodulus materials. The present paper, applies Levinson beam theory, which includes shear deformation and warping of the cross section, to bending analysis of thick rectangular beams with bimodulus materials. Many numerical results are obtained by use of the transfer matrix approach and compared with the methods of Bernoulli-Euler beam theory, Timoshenko beam theory, and Levinson beam theory with various boundaries. Also, the neutral-surface location and displacements for beams of bimodulus materials are calculated.     

Fabrication of sub-micron structures for MEMS using deep X-ray lithography

Fabrication techniques of microstructures with high resolution and high aspect ratio are necessary for practical microelectromechanical systems (MEMS) that have high performance and integration. In order to fabricate microstructures with sub-micron resolution and high aspect ratio, deep X-ray lithography has been investigated using the compact synchrotron radiation (SR) light source called “AURORA”. An X-ray mask for sub-micron deep X-ray lithography, which is composed of 1 μm thick Au as absorbers, 2 μm thick SiC as a membrane and 625 μm thick Si as a frame, was designed. In preliminary experiments, the following results were achieved: EB resist microstructures with an aspect ratio of 22 corresponding with 0.07 μm width and 1.3 μm height were formed; a 10 μm thick PMMA resist containing no warp was formed by direct polymerization, enabling more precise gap control.     

User Modeling in Spoken Dialogue Systems to Generate Flexible Guidance

We address the issue of appropriate user modeling to generate cooperative responses to users in spoken dialogue systems. Unlike previous studies that have focused on a user’s knowledge, we propose more generalized modeling. We specifically set up three dimensions for user models: the skill level in use of the system, the knowledge level about the target domain, and the degree of urgency. Moreover, the models are automatically derived by decision tree learning using actual dialogue data collected by the system. We obtained reasonable accuracy in classification for all dimensions. Dialogue strategies based on user modeling were implemented on the Kyoto City Bus Information System that was developed at our laboratory. Experimental evaluations revealed that the cooperative responses adapted to each subject type served as good guides for novices without increasing the duration dialogue lasted for skilled users.