Phase Transformation Dynamics Guided Alloy Development for Additive Manufacturing
Abstract
Fusion-based additive manufacturing technologies enable the fabrication of geometrically and compositionally complex parts unachievable by conventional manufacturing methods. However, the non-uniform and far-from-equilibrium heating/cooling conditions pose a significant challenge to consistently obtaining desirable phases in the as-printed parts. Here we report a martensite stainless steel development guided by phase transformation dynamics revealed by in-situ high-speed, high-energy, high-resolution X-ray diffraction. This developed stainless steel consistently forms desired fully martensitic structure across a wide range of cooling rates (102-107 °C/s), which enables direct printing of parts with fully martensitic structure. The as-printed material exhibits a yield strength of 1157 ± 23 MPa, comparable to its wrought counterpart after precipitation-hardening heat-treatment. The as-printed property is attributed to the fully martensitic structure and the fine precipitates formed during the intrinsic heat treatment in additive manufacturing. The phase transformation dynamics guided alloy development strategy demonstrated here opens the path for developing reliable, high-performance alloys specific for additive manufacturing.
Recommended Citation
Q. Guo and M. Qu and C. A. Chuang and L. Xiong and A. Nabaa and Z. A. Young and Y. Ren and P. Kenesei and F. Zhang and L. Chen, "Phase Transformation Dynamics Guided Alloy Development for Additive Manufacturing," Additive Manufacturing, vol. 59, article no. 103068, Elsevier, Nov 2022.
The definitive version is available at https://doi.org/10.1016/j.addma.2022.103068
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
17-4 PH Stainless Steel; Additive Manufacturing; Laser Processing; Phase Transformation; Synchrotron X-Ray Diffraction
International Standard Serial Number (ISSN)
2214-8604
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2022 Elsevier, All rights reserved.
Publication Date
01 Nov 2022
Comments
This work is funded by the National Science Foundation (CMMI-2011354) and University of Wisconsin-Madison Startup Fund.