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Additive manufacturing of alloys with programmable microstructure and properties

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Peer-reviewed

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Abstract

jats:titleAbstract</jats:title>jats:pIn metallurgy, mechanical deformation is essential to engineer the microstructure of metals and to tailor their mechanical properties. However, this practice is inapplicable to near-net-shape metal parts produced by additive manufacturing (AM), since it would irremediably compromise their carefully designed geometries. In this work, we show how to circumvent this limitation by controlling the dislocation density and thermal stability of a steel alloy produced by laser powder bed fusion (LPBF) technology. We show that by manipulating the alloy’s solidification structure, we can ‘program’ recrystallization upon heat treatment without using mechanical deformation. When employed site-specifically, our strategy enables designing and creating complex microstructure architectures that combine recrystallized and non-recrystallized regions with different microstructural features and properties. We show how this heterogeneity may be conducive to materials with superior performance compared to those with monolithic microstructure. Our work inspires the design of high-performance metal parts with artificially engineered microstructures by AM.</jats:p>

Description

Acknowledgements: The authors from Nanyang Technological University (NTU) and University of Cambridge would like to acknowledge M.J. Demkowicz, Z. Cordero, and M. Duchamp for valuable discussion, C. Todaro for the beamtime of neutron diffraction in ANSTO, Z. Wang and T.P. Le for technical support, and the Facilities for Analysis, Characterization, Testing and Simulations (FACTS) at NTU for access to electron microscopy equipment. This research was funded by the National Research Foundation (NRF) Singapore, under the NRF Fellowship program (NRF-NRFF2018-05). S.V.P. acknowledges support from the Swiss National Science Foundation (SNF Sinergia 193799). H.L.S. acknowledges support from the Science and Engineering Research Council, Agency for Science, Technology and Research (ASTAR), Singapore (142 68 00088). H.G. acknowledges support from Advanced Models for Additive Manufacturing (AM2) program under ASTAR (M22L2b0111) and support as a Distinguished University Professor of NTU and Scientific Director of Institute of High Performance Computing of the A*STAR, Singapore.

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Journal Title

Nature Communications

Conference Name

Journal ISSN

2041-1723

Volume Title

14

Publisher

Springer Science and Business Media LLC
Sponsorship
National Research Foundation Singapore (National Research Foundation-Prime Minister’s office, Republic of Singapore) (NRF-NRFF2018-05)
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) (SNF Sinergia 193799)
Agency for Science, Technology and Research (A*STAR) (142 68 00088, M22L2b0111)