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Pore elimination mechanisms during 3D printing of metals

Author

Listed:
  • S. Mohammad H. Hojjatzadeh

    (Missouri University of Science and Technology
    Missouri University of Science and Technology)

  • Niranjan D. Parab

    (Argonne National Laboratory)

  • Wentao Yan

    (National University of Singapore)

  • Qilin Guo

    (Missouri University of Science and Technology
    Missouri University of Science and Technology)

  • Lianghua Xiong

    (Missouri University of Science and Technology
    Missouri University of Science and Technology)

  • Cang Zhao

    (Argonne National Laboratory)

  • Minglei Qu

    (Missouri University of Science and Technology
    Missouri University of Science and Technology)

  • Luis I. Escano

    (Missouri University of Science and Technology)

  • Xianghui Xiao

    (Argonne National Laboratory)

  • Kamel Fezzaa

    (Argonne National Laboratory)

  • Wes Everhart

    (Department of Energy’s Kansas City National Security Campus Managed by Honeywell FM&T)

  • Tao Sun

    (Argonne National Laboratory)

  • Lianyi Chen

    (Missouri University of Science and Technology
    Missouri University of Science and Technology)

Abstract

Laser powder bed fusion (LPBF) is a 3D printing technology that can print metal parts with complex geometries without the design constraints of traditional manufacturing routes. However, the parts printed by LPBF normally contain many more pores than those made by conventional methods, which severely deteriorates their properties. Here, by combining in-situ high-speed high-resolution synchrotron x-ray imaging experiments and multi-physics modeling, we unveil the dynamics and mechanisms of pore motion and elimination in the LPBF process. We find that the high thermocapillary force, induced by the high temperature gradient in the laser interaction region, can rapidly eliminate pores from the melt pool during the LPBF process. The thermocapillary force driven pore elimination mechanism revealed here may guide the development of 3D printing approaches to achieve pore-free 3D printing of metals.

Suggested Citation

  • S. Mohammad H. Hojjatzadeh & Niranjan D. Parab & Wentao Yan & Qilin Guo & Lianghua Xiong & Cang Zhao & Minglei Qu & Luis I. Escano & Xianghui Xiao & Kamel Fezzaa & Wes Everhart & Tao Sun & Lianyi Chen, 2019. "Pore elimination mechanisms during 3D printing of metals," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10973-9
    DOI: 10.1038/s41467-019-10973-9
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    Cited by:

    1. Jingchang Li & Qi Zhou & Xufeng Huang & Menglei Li & Longchao Cao, 2023. "In situ quality inspection with layer-wise visual images based on deep transfer learning during selective laser melting," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 853-867, February.
    2. Yingjie Zhang & Wentao Yan, 2023. "Applications of machine learning in metal powder-bed fusion in-process monitoring and control: status and challenges," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2557-2580, August.
    3. Lingxiu Dong & Duo Shi & Fuqiang Zhang, 2022. "3D Printing and Product Assortment Strategy," Management Science, INFORMS, vol. 68(8), pages 5724-5744, August.

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