Study of laser directed energy deposition of Inconel 625 and austenitic steel

IF 3.1 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Science and Technology of Welding and Joining Pub Date : 2022-12-18 DOI:10.1080/13621718.2022.2156715

Nehem Tudu, M. Baruah, Shashi Bhushan Prasad

引用次数: 2

Abstract

Functionally graded material (FGM) is an advanced material that illustrates the number of properties in a single component. To develop FGM, it is very important to study each component gradient separately to understand the properties and their behaviour. This paper presents the study of the properties of deposited blocks of the different gradients of Inconel 625 (IN625) and stainless steel 304L (SS304L) (25% IN625 + 75% SS304L, 50% IN625 + 50% SS304L, 75% IN625 + 25% SS304L, and 100% IN625) by a laser directed energy deposition technique. Various tests were performed to understand its mechanical, metallurgical, and chemical behaviour. Deposited samples were heat-treated and then optical microscopy and microhardness were measured and compared to untreated ones and results found to be comparatively improved.

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激光定向能沉积Inconel 625和奥氏体钢的研究

功能梯度材料(FGM)是一种先进的材料，说明了在一个单一的组件性能的数量。为了开发FGM，分别研究各组分梯度以了解其性质和行为是非常重要的。采用激光定向能沉积技术研究了不同梯度Inconel 625 (IN625)和不锈钢304L (SS304L) (25% IN625 + 75% SS304L、50% IN625 + 50% SS304L、75% IN625 + 25% SS304L和100% IN625)沉积块体的性能。进行了各种测试以了解其机械、冶金和化学行为。对沉积后的样品进行热处理，测量光学显微镜和显微硬度，并与未处理的样品进行比较，结果发现相对提高。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Science and Technology of Welding and Joining 工程技术-材料科学：综合

CiteScore

6.10

自引率

12.10%

发文量

审稿时长

1.7 months

期刊介绍： Science and Technology of Welding and Joining is an international peer-reviewed journal covering both the basic science and applied technology of welding and joining. Its comprehensive scope encompasses all welding and joining techniques (brazing, soldering, mechanical joining, etc.) and aspects such as characterisation of heat sources, mathematical modelling of transport phenomena, weld pool solidification, phase transformations in weldments, microstructure-property relationships, welding processes, weld sensing, control and automation, neural network applications, and joining of advanced materials, including plastics and composites.