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Titlebook: Light Metals 2022; Dmitry Eskin Conference proceedings 2022 The Minerals, Metals & Materials Society 2022 Alumina and bauxite.Aluminum all

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樓主: 大腦
51#
發(fā)表于 2025-3-30 12:05:10 | 只看該作者
Influence of Tungsten Nanoparticles on the Structure and Mechanical Behavior of AA5056 Under Quasi-sing electron microscopy, the structure of the AA5056-W composite and the initial alloy is investigated. Introduction of 0.5 wt. % of tungsten nanoparticles does not modify the structure of the aluminum alloy, but due to dispersed hardening, it can increase the hardness and the values of the yield st
52#
發(fā)表于 2025-3-30 13:22:44 | 只看該作者
On the Influence of Alloy Composition and Sn Micro-Alloying on Mechanical Properties and Corrosion Rd mechanical properties and higher resistance against corrosion. Apart from modifying the alloy’s composition within specified limits, micro-alloying is a valuable tool to aim for improved mechanical properties and/or corrosion resistance. This study puts shed light on how this affects mechanical pr
53#
發(fā)表于 2025-3-30 20:13:18 | 只看該作者
Effect of Alloying Elements on Strength Properties and Casting Properties of Corrosion Resistant Quethat can face increased requirements to the material performance especially in an as-casted condition. The Al–Ca alloying system has good perspectives due to the possibility of obtaining dispersed eutectic (Al)?+?Al.Ca in the cast state without modification and heat treatment. The investigation of A
54#
發(fā)表于 2025-3-30 23:30:21 | 只看該作者
55#
發(fā)表于 2025-3-31 03:43:04 | 只看該作者
Effect of TiC Nanoparticles on Solidification Processing and Properties of Al–1.4Mg–0.8Si Alloynd its compounds (e.g., β-Mg.Si) with TiC nanoparticles at high temperatures makes solidification processing challenging for Al–Mg–Si containing TiC nanoparticles. Given the broad applications of Al–Mg–Si alloys, how TiC nanoparticles affect its solidification processing and resultant properties is
56#
發(fā)表于 2025-3-31 05:29:30 | 只看該作者
57#
發(fā)表于 2025-3-31 09:21:28 | 只看該作者
bjektive Erfahrung stützen kann. Die empirische Bilanzforschung erm?glicht indes, z. B. durch Multivariate Diskriminanzanalyse (MDA) oder durch Künstliche Neuronale Netz-Analyse (KNNA) jene Kennzahlenkombination zu ermitteln, die objektiv die Bilanzbonit?t von Unternehmen am zuverl?ssigsten beurteil
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