Solidification behavior and microstructural evolution of near-eutectic Zn-Al alloys under intensive shear

Copyright @ 2009 ASM International. This paper was published in Metallurgical and Materials Transactions A, 40(1), 185 - 195 and is made available as an electronic reprint with the permission of ASM International. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplications of any material in this paper for a fee or for commercial purposes, or modification of the content of this paper are prohibited.The effect of intensive shear on the solidification behavior and microstructural evolution of binary Zn-Al alloys is presented at hypoeutectic, eutectic, and hypereutectic compositions. It is found that the intensive shear, applied on the eutectic melt prior to solidification at a temperature above but close the eutectic temperature, can significantly reduce the size of eutectic cells, but the solidified microstructure still remains the lamellar morphology. For applying intensive shear on the melt during solidification, the nucleation occurs at temperatures very close to the equilibrium condition and requires very small undercooling for both the primary solidification and the eutectic solidification. The intensive shear can significantly alter the microstructural morphology. In contrast to the dendritic morphology formed in the conventional solidification, the primary Al-rich phase in hypoeutectic Zn-Al alloy and the primary Zn-rich phase in hypereutectic Zn-Al alloy under intensive shear exhibit fine and spherical particles, respectively. The lamellae morphology of Zn-rich phase and Al-rich phase formed in the conventional eutectic solidification exhibit fine and spherical particles. The increase of intensity of shear promotes the independence of solid Zn-rich particles and Al-rich particles during the eutectic solidification, resulting in the uniform and separate distribution of two solid particles in the matrix. It is speculated that the high intensity of shear can result in the independent nucleation of individual eutectic phase throughout the whole melt, and the separate growth of solid phases in the subsequent solidification

A super-ductile alloy for the die-casting of aluminium automotive body structural components

Super-ductile die-cast aluminium alloys are critical to future light-weighting of automotive body structures. This paper introduces a die-cast aluminium alloy that can satisfy the requirements of these applications. After a review of currently available alloys, the requirement of a die-cast aluminium alloy for automotive body structural parts is proposed and an Al-Mg-Si system is suggested. The effect of the alloying elements, in the composition, has been investigated on the microstructure and mechanical properties, in particular the yield strength, the ultimate tensile strength and elongation. © (2014) Trans Tech Publications, Switzerland.The EPSRC and JLR U

Designer Topological Insulators in Superlattices

Gapless Dirac surface states are protected at the interface of topological and normal band insulators. In a binary superlattice bearing such interfaces, we establish that valley-dependent dimerization of symmetry-unrelated Dirac surface states can be exploited to induce topological quantum phase transitions. This mechanism leads to a rich phase diagram that allows us to design strong, weak, and crystalline topological insulators. Our ab initio simulations further demonstrate this mechanism in [111] and [110] superlattices of calcium and tin tellurides.Comment: 5 pages, 4 figure

Microstructural characteristics of diecast AlMgSiMn alloy

Solidification and microstructural characteristics of Al-5wt.%Mg-1.5wt.%Si-0.6wt.%Mn- 0.2wt.%Ti alloy have been investigated in high pressure die casting. The average size of dendrites and fragmented dendrites of the primary α-Al phase formed in the shot sleeve is 43μm, and the globular α-Al grains formed inside the die cavity is 7.5μm. Solidification inside the die cavity also forms the lamellar Al-Mg2Si eutectic phase and the Fe-rich intermetallics. The size of the eutectic cells is about 10μm, in which the lamellar α-Al phase is 0.41μm thick. The Fe-rich intermetallic compound exhibits a compact morphology and is less than 2μm. Calculations using the Mullins and Sekerka stability criterion reveal that the solidification of the primary α-Al phase inside the die cavity has completed before the spherical α-Al globules begin to lose their stability, but the α-Al grains formed in the shot sleeve exceed the limit of spherical growth and therefore exhibit a dendritic morphology

MatchZoo: A Learning, Practicing, and Developing System for Neural Text Matching

Text matching is the core problem in many natural language processing (NLP) tasks, such as information retrieval, question answering, and conversation. Recently, deep leaning technology has been widely adopted for text matching, making neural text matching a new and active research domain. With a large number of neural matching models emerging rapidly, it becomes more and more difficult for researchers, especially those newcomers, to learn and understand these new models. Moreover, it is usually difficult to try these models due to the tedious data pre-processing, complicated parameter configuration, and massive optimization tricks, not to mention the unavailability of public codes sometimes. Finally, for researchers who want to develop new models, it is also not an easy task to implement a neural text matching model from scratch, and to compare with a bunch of existing models. In this paper, therefore, we present a novel system, namely MatchZoo, to facilitate the learning, practicing and designing of neural text matching models. The system consists of a powerful matching library and a user-friendly and interactive studio, which can help researchers: 1) to learn state-of-the-art neural text matching models systematically, 2) to train, test and apply these models with simple configurable steps; and 3) to develop their own models with rich APIs and assistance