Effect of Nd on the Microstructure, Mechanical Properties and Corrosion Behavior of Die-Cast Mg–4Al-based Alloy

Jinghuai Zhang,Jun Wang,Xin Qiu,Deping Zhang,Zheng Tian,Xiaodong Niu,Dingxiang Tang,Jian Meng

Journal of Alloys and Compounds（2008）SCI 2区

Chinese Acad Sci

Cited 174|Views0

Abstract

Die-cast Mg–4Al–0.4Mn–xNd (x=0, 1, 2, 4 and 6wt.%) magnesium alloys were prepared successfully and influences of Nd on the microstructure, mechanical properties and corrosion behavior of the Mg–4Al–0.4Mn alloy have been investigated. The results showed that with the addition of Nd binary Al2Nd phase and Al11Nd3 phase, which mainly aggregated along the grain boundaries, were formed, and the relative ratio of above two phases was in correlation with the Nd content in the alloy. Meanwhile, the grain sizes were greatly reduced with the increasing Nd content. It was found that due to the addition of Nd both the tensile properties and corrosion resistance were improved substantially. The alloy E with 5.96wt.% Nd content had the best tensile properties and corrosion resistance behavior in our research. While considering the cost of alloy, that with 1.13wt.% Nd addition has already performed well enough for the improvement of properties. All the analyses demonstrated that the improvement of mechanical properties and corrosion resistance depended on the grain refinement, grain boundary strengthening as well as solid solution strengthening.

Translated text

Key words

Mg-Al-Mn-Nd alloy,microstructure,mechanical properties,corrosion

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Try using models to generate summary,it takes about 60s

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper