Friction Stir Back Extrusion of Aluminium Alloys for Automotive Applications

Since the invention of Friction Stir Welding in 1991 as a solid state joining technique, extensive scientific investigations have been carried out to understand fundamental aspects of material behaviors when processed by this technique, in order to optimize processing conditions as well as mechanical properties of the welds. Based on the basic principles of Friction Stir Welding, several derivatives have also been developed such as Friction Stir Processing, Friction Extrusion and Friction Stir Back Extrusion. Friction Stir Back Extrusion is a novel technique that is proposed recently and designed for fabricating tubes from lightweight alloys. Some preliminary results have been reported regarding microstructure and mechanical properties of Friction Stir Back Extrusion processed AZ31 magnesium alloy, however, systematic study and in-depth investigations are still needed to understand the materials behaviors and underlying mechanisms when subjected to Friction Stir Back Extrusion, especially for age-hardenable Al alloys. In the present study, Friction Stir Back Extrusion processed AA6063-T5 and AA7075-T6 alloys are analyzed with respect to grain structure evolution, micro-texture change, recrystallization mechanisms, precipitation sequence as well as mechanical properties. Optical Microscopy, Electron Backscatter Diffraction, Transmission Electron Microscopy, Vickers Hardness measurements and uniaxial tensile tests are carried out to characterize the microstructural change as well as micro and macro mechanical properties of the processed tubes. Special attention is paid to the micro-texture evolution across the entire tube and dynamic recrystallization mechanisms that are responsible for grain refinement. Significant grain refinement has been observed near the processing zone while the tube wall is characterized by inhomogeneous grain structure across the thickness for both alloys. Dissolution of existing precipitates is noticed under the thermal hysterias imposed by Friction Stir Back Extrusion process, resulting in decreased strength but improved elongation of the processed tubes; a post-process aging step can effectively restore the mechanical properties of the processed tubes by allowing for the reprecipitation of solute elements in the form of fine, dispersed precipitates. Texture analysis performed for AA6063 alloy suggests the dominance of simple shear type textures with clear transition from initial texture to stable B/ ÍžB components via intermediate types that are stable under moderate strain levels. In order to identify the texture components properly, rigid body rotations are applied to the existing coordinate system to align it to local shear reference frame. Surprisingly, for AA7075 tubes, \u3c111\u3e and \u3c100\u3e fibers are observed to be the dominant texture components in the transition region as well as thermomechanically affected zone while the processing zone is characterized by random texture. The underlying mechanisms responsible for the formation of random texture are discussed in Chapter 5 based on Electron Backscatter Diffraction analysis. Comparative discussions are also carried out for the recrystallization mechanisms that are responsible for grain structure evolution of both alloys. Continuous grain subdivision and reorientation is cited as the dominant mechanism for the recrystallization of AA6063 alloys, while dynamic recrystallization occurs mainly in the form of Geometric Dynamic Recrystallization and progressive subgrain rotations near grain boundaries in AA7075 alloys

Effects of Microstructure on the Strain Rate Sensitivity of Advanced Steels

The dependence of the strain rate sensitivity of advanced ~1 GPa tensile strength steels on the phases present in their microstructures was studied by testing different steels at 0.005 and 500 s−1. The high strain rate tests were performed using a Kolsky bar setup, while the quasi-static tests were performed using a universal testing machine. The two main steels of interest were the Ferrite-Martensite DP980 and the Ferrite-Martensite-Austenite QP980; the latter being a transformation induced plasticity (TRIP) assisted steel. For comparison, ferritic CR5 mild steel and austenitic stainless steel 201 were also tested under the same conditions. Though the differences in the steel chemistries were not taken into account, the results obtained here suggest a strong relationship between the phase-content of the steel and its response to the changes in the loading rate. The relationships between the observed mechanical behavior and the phases present in the microstructure are discussed

Controlling mass and energy diffusion with metamaterials

Diffusion driven by temperature or concentration gradients is a fundamental mechanism of energy and mass transport, which inherently differs from wave propagation in both physical foundations and application prospects. Compared with conventional schemes, metamaterials provide an unprecedented potential for governing diffusion processes, based on emerging theories like the transformation and the scattering cancellation theory, which enormously expanded the original concepts and suggest innovative metamaterial-based devices. We hereby use the term ``diffusionics'' to generalize these remarkable achievements in various energy (e.g., heat) and mass (e.g., particles and plasmas) diffusion systems. For clarity, we categorize the numerous studies appeared during the last decade by diffusion field (i.e., heat, particles, and plasmas) and discuss them from three different perspectives: the theoretical perspective, to detail how the transformation principle is applied to each diffusion field; the application perspective, to introduce various intriguing metamaterial-based devices, such as cloaks and radiative coolers; and the physics perspective, to connect with concepts of recent concern, such as non-Hermitian topology, nonreciprocal transport, and spatiotemporal modulation. We also discuss the possibility of controlling diffusion processes beyond metamaterials. Finally, we point out several future directions for diffusion metamaterial research, including the integration with artificial intelligence and topology concepts.Comment: This review article has been accepted for publication in Rev. Mod. Phy

The B7 family member B7-H6 is a tumor cell ligand for the activating natural killer cell receptor NKp30 in humans

Cancer development is often associated with the lack of specific and efficient recognition of tumor cells by the immune system. Natural killer (NK) cells are lymphocytes of the innate immune system that participate in the elimination of tumors. We report the identification of a tumor cell surface molecule that binds NKp30, a human receptor which triggers antitumor NK cell cytotoxicity and cytokine secretion. This previously unannotated gene belongs to the B7 family and, hence, was designated B7-H6. B7-H6 triggers NKp30-mediated activation of human NK cells. B7-H6 was not detected in normal human tissues but was expressed on human tumor cells, emphasizing that the expression of stress-induced self-molecules associated with cell transformation serves as a mode of cell recognition in innate immunity

A synergistic ozone-climate control to address emerging ozone pollution challenges

Tropospheric ozone threatens human health and crop yields, exacerbates global warming, and fundamentally changes atmospheric chemistry. Evidence has pointed toward widespread ozone increases in the troposphere, and particularly surface ozone is chemically complex and difficult to abate. Despite past successes in some regions, a solution to new challenges of ozone pollution in a warming climate remains unexplored. In this perspective, by compiling surface measurements at ∼4,300 sites worldwide between 2014 and 2019, we show the emerging global challenge of ozone pollution, featuring the unintentional rise in ozone due to the uncoordinated emissions reduction and increasing climate penalty. On the basis of shared emission sources, interactive chemical mechanisms, and synergistic health effects between ozone pollution and climate warming, we propose a synergistic ozone-climate control strategy incorporating joint control of ozone and fine particulate matter. This new solution presents an opportunity to alleviate tropospheric ozone pollution in the forthcoming low-carbon transition.This study was supported by the Research Grants Council of Hong Kong Special Administrative Region via General Research Funds (HKBU 15219621 and PolyU 15212421) and a Theme-based Research Scheme (T24-504/17-N). The authors acknowledge the support of the Australia–China Centre on Air Quality Science and Management. R.S. acknowledges support from ANID/FONDAP/1522A0001. D.S. thanks the program of Coordination for the Improvement of Higher Education Personnel (CAPES) (436466/2018-0). X.X. acknowledges funding from the Natural Science Foundation of China (41330422) and the Chinese Academy of Meteorological Sciences (2020KJ003). K.L. is supported by the Natural Science Foundation of China (42205114), Jiangsu Carbon Peak and Neutrality Science and Technology Innovation fund (BK20220031), and the Startup Foundation for Introducing Talent of NUIST. We sincerely appreciate all the organizations and programs introduced in the section “experimental procedures” for freely providing ozone data. We thank Dr. Owen Cooper (University of Colorado, Boulder, and NOAA) for insightful guidance and discussion. No organization or program will be responsible for the results generated from their data.Peer reviewe

Concatenated Network Fusion Algorithm (CNFA) Based on Deep Learning: Improving the Detection Accuracy of Surface Defects for Ceramic Tile

The low accuracy of detection algorithms is one impediment in detecting ceramic tile’s surface defects online utilizing intelligent detection instead of human inspection. The purpose of this paper is to present a CNFA for resolving the obstacle. Firstly, a negative sample set is generated online by non-defective images of ceramic tiles, and a comparator based on a modified VGG16 extracts a reference image from it. Disguised rectangle boxes, including defective and non-defective, are acquired from the image to be inspected by a detector. A reference rectangle box most similar to the disguised rectangle box is extracted from the reference image. A discriminator is constituted with a modified MobileNetV3 network serving as the backbone and a metric learning loss function strengthening feature recognition, distinguishing the true and false of disguised and reference rectangle boxes. Results exhibit that the discriminator appears to have an accuracy of 98.02%, 13% more than other algorithms. Furthermore, the CNFA performs an average accuracy of 98.19%, and the consumption time of a single image extends by only 64.35 ms, which has little influence on production efficiency. It provides a theoretical and practical reference for surface defect detection of products with complex and changeable textures in industrial environments