Controlling process instability for defect lean metal additive manufacturing

Minglei Qu, Qilin Guo, Luis I. Escano, Ali Nabaa, S. Mohammad H. Hojjatzadeh, Zachary A. Young and Lianyi Chen ()
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Minglei Qu: University of Wisconsin-Madison
Qilin Guo: University of Wisconsin-Madison
Luis I. Escano: University of Wisconsin-Madison
Ali Nabaa: University of Wisconsin-Madison
S. Mohammad H. Hojjatzadeh: University of Wisconsin-Madison
Zachary A. Young: University of Wisconsin-Madison
Lianyi Chen: University of Wisconsin-Madison

Nature Communications, 2022, vol. 13, issue 1, 1-8

Abstract: Abstract The process instabilities intrinsic to the localized laser-powder bed interaction cause the formation of various defects in laser powder bed fusion (LPBF) additive manufacturing process. Particularly, the stochastic formation of large spatters leads to unpredictable defects in the as-printed parts. Here we report the elimination of large spatters through controlling laser-powder bed interaction instabilities by using nanoparticles. The elimination of large spatters results in 3D printing of defect lean sample with good consistency and enhanced properties. We reveal that two mechanisms work synergistically to eliminate all types of large spatters: (1) nanoparticle-enabled control of molten pool fluctuation eliminates the liquid breakup induced large spatters; (2) nanoparticle-enabled control of the liquid droplet coalescence eliminates liquid droplet colliding induced large spatters. The nanoparticle-enabled simultaneous stabilization of molten pool fluctuation and prevention of liquid droplet coalescence discovered here provide a potential way to achieve defect lean metal additive manufacturing.

Date: 2022
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28649-2

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DOI: 10.1038/s41467-022-28649-2

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