Graphene oxide-decorated Fe<Subscript>2</Subscript>(MoO<Subscript>4</Subscript>)<Subscript>3</Subscript> microflowers as a promising anode for lithium and sodium storage

Mixed transition metal oxides (MTMOs) have received intensive attention as promising anode materials for lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs). In this work, we demonstrate a facile one-step water-bath method for the preparation of graphene oxide (GO) decorated Fe₂(MoO₄)₃ (FMO) microflower composite (FMO/GO), in which the FMO is constructed by numerous nanosheets. The resulting FMO/GO exhibits excellent electrochemical performances in both LIBs and SIBs. As the anode material for LIBs, the FMO/GO delivers a high capacity of 1,220 mAh·g^–1 at 200 mA·g^–1 after 50 cycles and a capacity of 685 mAh·g^–1 at a high current density of 10 A·g^–1. As the anode material for SIBs, the FMO/GO shows an initial discharge capacity of 571 mAh·g^–1 at 100 mA·g^–1, maintaining a discharge capacity of 307 mAh·g^–1 after 100 cycles. The promising performance is attributed to the good electrical transport from the intimate contact between FMO and graphene oxide. This work indicates that the FMO/GO composite is a promising anode for high-performance lithium and sodium storage.

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Fabrication of Titanium Aluminides via Powder-Cored Wire Arc Additive Manufacturing: Microstructural and Mechanical Characterization

Herein, an innovative powder-cored wire arc additive manufacturing (PC-WAAM) process is proposed to fabricate γ-TiAl thin-walled intermetallic alloy. The metallography, phase composition, and mechanical properties at different thin-wall locations are characterized. The results show that the alternatively distributed layer-like microstructure composed of α₂ (Ti₃Al) and γ (TiAl) phases is obtained along the building direction. The content of α₂ phase exhibits the tendency of decreasing from the bottom to top region. This unique microstructure characteristic is closely related to the typical thermal cycling history during deposition. Moreover, the tensile strength and microhardness of the top region are lower than the middle and bottom region. In general, the current PC-WAAM technique shows promising capability of fabricating γ-TiAl intermetallic alloy with low cost. This work becomes a valuable reference for understanding the evolution mechanism of microstructure and paves the way for the flexible and customized additive manufacturing of γ-TiAl alloy.     

Computational Parametric Analysis of Cellular Solids with the Miura-Ori Metamaterial Geometry under Quasistatic Compressive Loads

Origami-based metamaterials have widespread application prospects in various industries including aerospace, automotive, flexible electronics, and civil engineering structures. Among the wide range of origami patterns, the fourfold tessellation known as Miura-ori is of particular attraction to engineers and designers. More specifically, researchers have proposed different 3D structures and metamaterials based on the geometric characteristics of this classic origami pattern. Herein, a computational modeling approach for the design and evaluation of 3D cellular solids with the Miura-ori metamaterial geometry which can be of zero or nonzero thicknesses is presented. To this end, first, a range of design alternatives generated based on a numerical parametric model is designed. Next, their mechanical properties and failure behavior under quasistatic axial compressive loads along three perpendicular directions are analyzed. Then, the effects of various geometric parameters on their energy absorption behavior under compression in the most appropriate direction are investigated. The findings of this study provide a basis for future experimental investigations and the potential application of such cellular solids for energy-absorbing purposes.     

Isolation and identification of (3-methoxyphenyl)acetonitrile as a phytotoxin from meadowfoam (Limnanthes alba) seedmeal

Ethyl ether, ethanol, and water extracts of meadowfoam (Limnanthes alba Hartweg ex. Benth.) seedmeal were prepared and bioassayed against velvetleaf (Abutilon theophrasti Medicus) and wheat (Triticum aestivum L. Cardinal). Both the ethyl ether and ethanol fractions, but not the water extract, inhibited velvetleaf and wheat radicle elongation. Fractionation of the extracts indicated that (3-methoxyphenyl)acetonitrile (3-MPAN) was the active compound from both extracts, comprising >97% of the active ethanol fraction. 3-Methoxybenzyl isothiocyanate, which had been previously shown to be the major breakdown product of glucolimnanthin, the majorL. alba glucosinolate, was not detected in either extract. Radicle elongation of velvetleaf and wheat were inhibited by 3-MPAN with I₅₀ (the concentration required to inhibit growth by 50%) values of approximately 4 × 10^–4 M (velvetleaf) and 7×10^–4 M (wheat).Mention of firms or products does not imply endorsement by the U.S. Department of Agriculture over other firms or products not mentioned.     

Experimental study on fitness of one-piece casting osseointegrated implant frameworks with relation to fixture abutment positions

An experiment on fitness of one-piece casting osseointegrated implant frameworks was performed among three fixture abument positions where other conditions were controlled. The result revealed that there was statistically significant differences in dimensional change among the three fixture abument positions. In terms of the relation between abument position and fitness, the more backward the abument position was, the worse the osseointegrated framework fitness was. The frameworks showed deformations in "arch form" and "warp" in three dimensions.     

Theory and techniques of data mining in CGF behavior modeling

For the large quantity of data,rules and models generated in the course of computer generated forces (CGFs) behavior modeling,the common analytical methods are statistical methods based on the tactical rules,tactical doctrine and empirical knowledge.However,from the viewpoint of data mining,we can find many of these analytical methods are also each-and-every different data mining methods.In this paper,we survey the data mining theory and techniques that have appeared in the course of CGF behavior modeling f...     

Direct raycasting of unstructured cell-centered data by discontinuity Roe-average computation

In the field of computational fluid dynamics (CFD), the upwind finite volume method (FVM) is widely applied to solve 3D flows with discontinuity phenomena (e.g., shock waves). It produces unstructured data at the center of each cell (cell-centered data) with the flow discontinuity constraint on the inner-face between face-neighboring cells. For visualization, existing approaches with interpolation usually pre-extrapolate cell-centered data into cell-vertexed data (data values given at cell vertices) and only handle cell-vertexed data during actual rendering, which unconsciously depress the rendering accuracy and violate the discontinuity constraint. In this paper, we propose a novel method to visualize cell-centered data directly avoiding extrapolation and keep the discontinuity in the rendering data on the framework of multi-pass raycasting. During resampling, the field is reconstructed using the original cell-centered data value and the cell-gradient estimated by Green–Gauss theorem. To keep the discontinuity, we reconstruct the field at an inner-face resampled point using both the face-adjacencies and get two discontinuous field values. Then the field is obtained by computing Roe-average of the two. The analysis and experiments demonstrate that our approach gains a high-accuracy reconstruction and leads to a high-quality image.     

基于蚁群算法的网格资源发现模型研究

本文通过对传统的网格资源发现存在的问题进行分析,针对其不足,引入蚁群算法,提出基于蚁群算法的网格资源发现模型（AA_GRRM）,设计并分析AA_GRRM的体系结构,并对其关键模块分析设计,以提高网格资源发现效率。     

Multi-agent and driving behavior based rear-end collision alarm modeling and simulating

Distance-between-vehicle-measurement is the only factor in traditional car rear-end alarm system. To address the above problem, this paper proposes an alarming model based on multi-agent systems (MAS) and driving behavior. It consists of four different types of agents that can either work alone or collaborate through a communications protocol on the basis of the extended KQML. The rear-end alarming algorithm applies the Bayes decision theory to calculate the probability of collision and prevent its occurrence real-time. The learning algorithm of driving behavior based on ensemble artificial neural network (ANN) and the decision procedure based on Bayes’ theory are also described in this paper. Both autonomy and reliability are enhanced in the proposed system. The effectiveness and robustness of the model have been confirmed by the simulated experiments.