2024
DOI: 10.1088/2631-7990/ad1657
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Alloy design for laser powder bed fusion additive manufacturing: a critical review

Zhuangzhuang Liu,
Qihang Zhou,
Xiaokang Liang
et al.

Abstract: Metal additive manufacturing (AM) has been extensively studied in recent decades. Despite the significant progress achieved in manufacturing complex shapes and structures, challenges such as severe cracking when using existing alloys for laser powder bed fusion (L-PBF) AM persisted. This is due to the fact that commercial alloys are primarily designed for conventional casting or forging processes, without considering the fast cooling rates, steep temperature gradients, and multiple thermal cycles of L-PBF. To … Show more

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Cited by 7 publications
(5 citation statements)
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“…Decreasing the scan speed reduces the keyhole/depression zone opening volume, and hence creates a stronger argon vortex flow under an enhanced Bernoulli Effect. Therefore, we expect a high proportion of entrained solid spatter as the F g increases, according to equation (6). The calculated outward argon flow velocity above the powder bed is up to ∼7 m•s −1 [51] and two orders of magnitude slower than the vapour plume velocity.…”
Section: Solid Spatter/liquid Droplet Velocity Figures 3(c) Andmentioning
confidence: 81%
See 1 more Smart Citation
“…Decreasing the scan speed reduces the keyhole/depression zone opening volume, and hence creates a stronger argon vortex flow under an enhanced Bernoulli Effect. Therefore, we expect a high proportion of entrained solid spatter as the F g increases, according to equation (6). The calculated outward argon flow velocity above the powder bed is up to ∼7 m•s −1 [51] and two orders of magnitude slower than the vapour plume velocity.…”
Section: Solid Spatter/liquid Droplet Velocity Figures 3(c) Andmentioning
confidence: 81%
“…Laser powder bed fusion (LPBF) is a prominent additive manufacturing (AM) technology that manufactures near-net shape metallic components with exceptional design freedom, minimal lead time, and no tooling cost, on a layer-by-layer basis [1][2][3][4]. However, the adoption of LPBF for safety critical applications is hindered by the challenge of achieving defectlean, high-density metallic components that meet critical quality standards [5,6].…”
Section: Introductionmentioning
confidence: 99%
“…While traditional methods have provided valuable insights into the behavior and characteristics of disorder systems like GBs, the complexity and huge volume of data involved in these studies are driving researchers towards data-driven techniques such as ML, which are computationally much more efficient [104]. ML achievements in recent years offer new ways to study amorphous materials or multi-element alloys which contain disorders [105][106][107][108][109][110].…”
Section: Application Of Machine Learning In Metastable Gbsmentioning
confidence: 99%
“…Preparing the feedstock powder is the first stage in powder-based AM production processes. Pre-alloyed powder or an elemental mix of the component particles can be used as the raw material for powder-based AM techniques [27,32]. The powder mixing method for obtaining new alloy compositions for AM works is successful if the chemistry of the product is a close match to the new composition being investigated.…”
Section: An Unprecedented Alloy Design Opportunitymentioning
confidence: 99%