Heat treatment for metal additive manufacturing

材料科学 微观结构 残余应力 冶金 高温合金 腐蚀
作者
Majid Laleh,Esmaeil Sadeghimeresht,Reynier I. Revilla,Qi Chao,N. Haghdadi,A.E. Hughés,Wei Xu,Iris De Graeve,Ma Qian,Ian Gibson,Yongjun Tan
出处
期刊:Progress in Materials Science [Elsevier]
卷期号:133: 101051-101051 被引量:170
标识
DOI:10.1016/j.pmatsci.2022.101051
摘要

Metal additive manufacturing (AM) refers to any process of making 3D metal parts layer-upon-layer via the interaction between a heating source and feeding material from a digital design model. The rapid heating and cooling attributes inherent to such an AM process result in heterogeneous microstructures and the accumulation of internal stresses. Post-processing heat treatment is often needed to modify the microstructure and/or alleviate residual stresses to achieve properties comparable or superior to those of the conventionally manufactured (CM) counterparts. However, the optimal heat treatment conditions remain to be defined for the majority of AM alloys and are becoming another topical issue of AM research due to its industrial importance. Existing heat treatment standards for CM metals and alloys are not specifically designed for AM parts and may differ in many cases depending on the initial microstructures and desired properties for specific applications. The purpose of this paper is to critically review current knowledge and discuss the influence of post-AM heat treatment on microstructure, mechanical properties, and corrosion behavior of the major categories of AM metals including steel, Ni-based superalloys, Al alloys, Ti alloys, and high entropy alloys. This review clarifies significant differences between heat treating AM metals and their CM counterparts. The major sources of differences include microstructural heterogeneity, internal defects, and residual stresses. Understanding the influence of such differences will benefit industry by achieving AM metals with consistent and superior balanced performance compared to as-built AM and CM metals.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
QHAW驳回了大个应助
刚刚
英俊短靴完成签到,获得积分10
1秒前
王哈哈发布了新的文献求助10
3秒前
5秒前
anyi完成签到,获得积分10
5秒前
6秒前
英俊的铭应助www采纳,获得10
7秒前
奥特曼完成签到,获得积分10
10秒前
11秒前
11秒前
HANGOVERG发布了新的文献求助10
11秒前
gg发布了新的文献求助10
11秒前
12秒前
Ava应助丸子采纳,获得10
12秒前
zz完成签到,获得积分10
12秒前
奶味蓝发布了新的文献求助10
12秒前
Fx关闭了Fx文献求助
13秒前
14秒前
赢赢发布了新的文献求助30
14秒前
14秒前
淡定舞仙发布了新的文献求助10
15秒前
17秒前
paparazzi221应助交钱上班采纳,获得50
18秒前
脑洞疼应助危机的如波采纳,获得30
18秒前
kyou发布了新的文献求助10
19秒前
小蘑菇应助wangayting采纳,获得10
19秒前
xbb0905完成签到,获得积分10
19秒前
JamesPei应助气泡水采纳,获得10
21秒前
奶味蓝完成签到,获得积分10
21秒前
烟花应助xuhaohao采纳,获得10
21秒前
好运锦鲤完成签到 ,获得积分10
22秒前
22秒前
闲听花落发布了新的文献求助10
22秒前
称心语风完成签到,获得积分20
22秒前
无花果应助byumi采纳,获得10
23秒前
FashionBoy应助我没有名字采纳,获得20
23秒前
维生素完成签到 ,获得积分10
24秒前
24秒前
25秒前
27秒前
高分求助中
Sustainability in Tides Chemistry 2000
Bayesian Models of Cognition:Reverse Engineering the Mind 888
Essentials of thematic analysis 700
A Dissection Guide & Atlas to the Rabbit 600
Very-high-order BVD Schemes Using β-variable THINC Method 568
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger 500
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3125274
求助须知:如何正确求助?哪些是违规求助? 2775580
关于积分的说明 7727081
捐赠科研通 2431059
什么是DOI,文献DOI怎么找? 1291657
科研通“疑难数据库(出版商)”最低求助积分说明 622216
版权声明 600368