Key Takeaways & Executive Findings
- •• Synchrotron X-ray in situ imaging reveals the dynamic evolution of surface depressions across multiple layers in LPBF, linking them to interlayer defect formation. • Insufficient energy input in the first layer causes balling and fracture of melt tracks, which serve as precursors for subsequent surface depressions. • Increasing energy input in the second layer induces local overheating at gaps between melt tracks, creating surface depressions; reducing energy in later layers hinders melt backflow and enlarges depression regions. • The study provides critical experimental evidence for closed-loop interlayer process control, enabling real-time defect mitigation in laser additive manufacturing.
Abstract
In laser powder bed fusion (LPBF) additive manufacturing, surface depressions caused by melt pool instability can induce defects throughout the layer-by-layer printing process. To address the limited understanding of interlayer defect transmission mechanisms, synchrotron X-ray in situ imaging was used to systematically investigate the dynamic evolution of surface depressions during multi-pass printing by adjusting interlayer process parameters. Experimental results show that insufficient energy input in the first layer leads to balling and fracture of melt tracks. When the energy input in the second layer is increased, local overheating at the gap between melt tracks from the previous layer causes surface depressions. Reducing the energy input in the third layer hinders melt backflow, enlarging the depression region. Further lowering the energy input in the final layer leads to the formation of internal unfused defects. This study reveals the dynamic correlation between surface depressions and interlayer defect evolution, offering critical experimental evidence and theoretical guidance for closed-loop interlayer process control in laser additive manufacturing.
1. Introduction
Laser powder bed fusion (LPBF) additive manufacturing offers significant advantages in achieving integrated material-structure-performance fabrication due to its unique layer-by-layer process. It has been widely applied in high-end sectors such as aerospace and biomedical engineering [1]. However, complex physical phenomena such as melt flow and phase-change heat transfer cause significant fluctuations in melt pool behavior, leading to various porosity defects, including keyholes, gas pores, and lack of fusion [2]. More importantly, the inherent layer-by-layer nature of LPBF allows these defects to propagate vertically, significantly degrading the component’s performance, especially its fatigue life [3]. Therefore, understanding melt flow dynamics and their relationship with defect formation is essential for ensuring component quality [4].
Studies on surface depression defects in melt pools have produced several important findings. Using a three-dimensional transient multiphase model, Pang et al. [5] systematically investigated the effects of environmental pressure and laser power on melt pool morphology. They identified vapor recoil pressure as the main cause of surface depression, with reduced ambient pressure significantly exacerbating the defect. Zheng et al. [6] found that changes in laser scanning speed and powder layer thickness significantly affect melt pool depression characteristics. High scanning speeds tend to cause periodic depressions at the rear of the melt pool. Wang et al. [7] also reported that insufficient laser energy caused multiple beam reflections among powder particles, leading to uneven energy distribution and the formation of unmelted regions and random surface depressions. Collectively, these studies indicate that surface depressions occur fundamentally from external forces that cause surface deformation of the melt pool. Due to rapid solidification, the molten metal lacks sufficient time to reflow to fill these depression defects. Although optimizing parameters such as laser power and scanning speed can help control melt flow and reduce surface depressions, current studies insufficiently address their impact on the formation quality of subsequent layers.
Investigating the layer-by-layer defect formation process requires advanced characterization techniques. Traditional metallography and X-ray computed tomography (X-CT) can detect final defects but fail to capture their dynamic formation [8]. Although infrared thermography and high-speed imaging provide real-time data on melt pool temperature and surface morphology [6, 7], their utility is constrained by limited penetration depth and spatial resolution [9-11]. In contrast, synchrotron X-ray imaging enables the study of transient melt pool phenomena with submicron spatial and temporal resolution [12]. Synchrotron X-ray imaging has been widely used to investigate defect formation mechanisms during single-pass printing. Hojjatzadeh et al. [13] identified six types of pores during single-pass printing and revealed their formation mechanisms. Simonds et al. [14] and Zhao et al. [15] captured abnormal keyhole formation at [continued in next section].
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Jie Li, Jie Wan, Zi-jian Chen, Jin-shan Li, Jun Wang (2026). In situ monitoring of surface depressions in metal laser additive manufacturing and its interlayer transfer mechanism. China Foundry. https://doi.org/10.1007/s41230-026-5163-9
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Frequently Asked Questions
What is the main objective of this study?
The study aims to investigate the dynamic evolution of surface depressions during multi-pass LPBF printing and their role in interlayer defect transmission, using synchrotron X-ray in situ imaging.
How does insufficient energy input in the first layer affect subsequent layers?
Insufficient energy input in the first layer leads to balling and fracture of melt tracks, which create gaps and irregularities that influence melt flow in subsequent layers, potentially causing surface depressions and internal defects.
What is the significance of synchrotron X-ray imaging in this research?
Synchrotron X-ray imaging provides submicron spatial and temporal resolution, allowing real-time observation of transient melt pool phenomena and defect formation across layers, which is not possible with traditional post-mortem techniques.
What are the practical implications of this study for additive manufacturing?
The findings offer critical experimental evidence for closed-loop interlayer process control, enabling real-time adjustment of process parameters to prevent defect propagation and improve component quality in laser additive manufacturing.
How does the study contribute to understanding surface depression mechanisms?
The study reveals that surface depressions are influenced by interlayer energy input variations, which affect melt backflow and local overheating, providing a dynamic correlation between surface depressions and interlayer defect evolution.
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