A new refining process for iron oxide using iron ore and its application to hard ferrites

Kawasaki Steel Corporation and Kawatetsu Mining Co., Ltd. have developed a new refining process to extract iron oxide from iron ore to meet the increase in demand for iron oxide for high- grade hard ferrites. This article discusses the quality of iron oxides and the characteristics of the hard ferrite magnets produced from them.     

Microstructure development of steel during severe plastic deformation

The microstructure development during plastic deformation was reviewed for iron and steel which were subjected to cold rolling or mechanical milling (MM) treatment, and the change in strengthening mechanism caused by the severe plastic deformation (SPD) was also discussed in terms of ultra grain refinement behavior. The microstructure of cold-rolled iron is characterized by a typical dislocation cell structure, where the strength can be explained by dislocation strengthening. It was confirmed that the increase in dislocation density by cold working is limited at 10¹⁶m⁻², which means the maximum hardness obtained by dislocation strengthening is HV3.7 GPa. However, the iron is abnormally work-hardened over the maximum dislocation strengthening by SPD of MM because of the ultra grain refinement caused by the SPD. In addition, impurity of carbon plays an important role in such grain refinement: the carbon addition leads to the formation of nano-crystallized structure in iron.     

Template‐Free Fabrication of Mesoporous Alumina Nanospheres Using Post‐Synthesis Water‐Ethanol Treatment of Monodispersed Aluminium Glycerate Nanospheres for Molybdenum Adsorption

This work reports the template‐free fabrication of mesoporous Al₂O₃ nanospheres with greatly enhanced textural characteristics through a newly developed post‐synthesis “water‐ethanol” treatment of aluminium glycerate nanospheres followed by high temperature calcination. The proposed “water‐ethanol” treatment is highly advantageous as the resulting mesoporous Al₂O₃ nanospheres exhibit 2–4 times higher surface area (up to 251 m² g^?1), narrower pore size distribution, and significantly lower crystallization temperature than those obtained without any post‐synthesis treatment. To demonstrate the generality of the proposed strategy, a nearly identical post‐synthesis “water treatment” method is successfully used to prepare mesoporous monometallic (e.g., manganese oxide (MnO₂)) and bimetallic oxide (e.g., CuCo₂O₄ and MnCo₂O₄) nanospheres assembled of nanosheets or nanoplates with highly enhanced textural characteristics from the corresponding monometallic and bimetallic glycerate nanospheres, respectively. When evaluated as molybdenum (Mo) adsorbents for potential use in molybdenum‐99/technetium‐99m (⁹⁹Mo/^99mTc) generators, the treated mesoporous Al₂O₃ nanospheres display higher molybdenum adsorption performance than non‐treated Al₂O₃ nanospheres and commercial Al₂O₃, thereby suggesting the effectiveness of the proposed strategy for improving the functional performance of oxide materials. It is expected that the proposed method can be utilized to prepare other mesoporous metal oxides with enhanced textural characteristics and functional performance.     

High-performance cone beam reconstruction using CUDA compatible GPUs

Compute unified device architecture (CUDA) is a software development platform that allows us to run C-like programs on the nVIDIA graphics processing unit (GPU). This paper presents an acceleration method for cone beam reconstruction using CUDA compatible GPUs. The proposed method accelerates the Feldkamp, Davis, and Kress (FDK) algorithm using three techniques: (1) off-chip memory access reduction for saving the memory bandwidth; (2) loop unrolling for hiding the memory latency; and (3) multithreading for exploiting multiple GPUs. We describe how these techniques can be incorporated into the reconstruction code. We also show an analytical model to understand the reconstruction performance on multi-GPU environments. Experimental results show that the proposed method runs at 83% of the theoretical memory bandwidth, achieving a throughput of 64.3 projections per second (pps) for reconstruction of 512³-voxel volume from 360 512²-pixel projections. This performance is 41% higher than the previous CUDA-based method and is 24 times faster than a CPU-based method optimized by vector intrinsics. Some detailed analyses are also presented to understand how effectively the acceleration techniques increase the reconstruction performance of a naive method. We also demonstrate out-of-core reconstruction for large-scale datasets, up to 1024³-voxel volume.     

Visual simulation of mixed-motion avalanches with interactions between snow layers

In the field of computer graphics, simulation of fluids, including avalanches, is an important research topic. In this paper, we propose a method to simulate a kind of avalanche, mixed-motion avalanche, which is usually large and travels down the slope fast, often resulting in impressive visual effects. The mixed-motion avalanche consists of snow smokes and liquefied snow which form an upper suspension layer and a lower dense-flow layer, respectively. The mixed-motion avalanche travels down the surface of the snow-covered mountain, which is called accumulated snow layer. We simulate a mixed-motion avalanche taking into account these three snow layers. We simulate the suspension layer using a grid-based approach, the dense-flow and accumulated snow layer using a particle-based approach. An important contribution of our method is an interaction model between these snow layers that enables us to obtain the characteristic motions of avalanches, such as the generation of the snow smoke from the head of the avalanche.     

An Algorithm for Minimum Cost Arc-Connectivity Orientations

Given a 2k-edge-connected undirected graph, we consider to find a minimum cost orientation that yields a k-arc-connected directed graph. This minimum cost k-arc-connected orientation problem is a special case of the submodular flow problem. Frank (1982) devised a combinatorial algorithm that solves the problem in O(k ² n ³ m) time, where n and m are the numbers of vertices and edges, respectively. Gabow (1995) improved Frank’s algorithm to run in O(kn ² m) time by introducing a new sophisticated data structure. We describe an algorithm that runs in O(k ³ n ³+kn ² m) time without using sophisticated data structures. In addition, we present an application of the algorithm to find a shortest dijoin in O(n ² m) time, which matches the current best bound.     

Discharge properties and chemical stability of SrZrO films

Abstract— MgO thin film is currently used as a surface protective layer for dielectric materials because MgO has a high resistance during ion sputtering and exhibits effective secondary electron emission. The secondary‐electron‐emission coefficient γ of MgO is high for Ne ions; however, it is low for Xe ions. The Xe content of the discharge gas of PDPs needs to be raised in order to increase the luminous efficiency. Thus, the development of high‐γ materials replacing MgO is required. The discharge properties and chemical surface stability of SrO containing Zr (SrZrO) as the candidate high‐γ protective layer for noble PDPs have been characterized. SrZrO films have superior chemical stability, especially the resistance to carbonation because of the existence of a few adsorption sites due to their amorphous structure. The firing voltage is 60 V lower than that of MgO films for a discharge gas of Ne/Xe = 85/15 at 60 kPa.     

Designing high-level decision making systems based on fuzzy if–then rules for a point-to-point car racing game

In this paper, fuzzy rule-based systems are applied to a point-to-point car racing game. In the point-to-point car racing game, two car agents compete with each other for taking waypoints. There are three waypoints in the car racing field, each of which is assigned a number that indicates the order to take. The control process of car agents is modeled as a non-holonomic system where there are two input variables (acceleration and steering) for controlling the position, angle and velocity of the car agents. Fuzzy rule-based systems are used to make a high-level decision where the target waypoint to take is determined. Since a fuzzy rule-based system for the high-level decision making is generated in the manner of supervised learning, a set of training patterns should be given for the construction of the fuzzy rule-based systems. In this paper we examine two methods to obtain such a set of training patterns. We also examine two representations of input vectors for the fuzzy rule-based systems. We discuss the effect of obtained training patterns and the input representation on the performance of the fuzzy rule-based systems. After discussing and analyzing the experimental results, we present an adaptive framework of fuzzy rule-based systems. The performance of adaptive fuzzy rule-based systems is then examined based on the results of their non-adaptive version. A series of computational experiments are performed to show the learning ability of the adaptive fuzzy rule-based systems.     

Deformation characteristics of ultra-thin liquid film considering temperature and film thickness dependence of surface tension

Thermocapillary deformations of an ultra-thin liquid film caused by temperature distribution were three-dimensionally analyzed using the unsteady and linearized long wave equation considering the temperature and film thickness dependence of surface tension. The temperature and film thickness dependence equation for the surface tension of a liquid was firstly established. The temperature dependence of the surface tension was obtained experimentally using a surface tensiometer and the film thickness dependence was obtained theoretically from the corrected van der Waals pressure equation for a symmetric multilayer system. Time evolutions of depression and groove of the ultra-thin liquid film caused by local heating were obtained quantitatively.