突破激光熔池4D成像速度瓶颈,实现每秒2.5万帧高精度动态捕捉。
4D reconstruction of alumina laser melt pools at 25 kHz via operando X-ray multi-projection imaging
- 通过多角度投影技术解耦时间分辨率与样品转速限制
- 在25Hz转速下实现每秒2.5万次重构,比现有技术快250倍
- 适用于增材制造等快速材料过程的实时动态观测
提升增材制造(如激光粉末床熔融)需要解析熔池动力学和匙孔演化的4D(3D+时间)过程。原位X射线断层扫描是先进的4D表征方法,但其时间分辨率受样品旋转速度制约,难以捕捉快速现象。本文提出旋转增强型X射线多投影成像(rotation-XMPI),每个时间步捕捉三个角度投影,从而解耦时间分辨率与样品旋转速度。结合自监督深度学习重建框架处理多角度输入,rotation-XMPI实现了前所未有的高速高保真4D成像。我们在MAX IV实验中使用三束激光与25 Hz样品旋转,对氧化铝激光重熔过程进行了原位观测。rotation-XMPI成功解析了熔池形貌与匙孔演化;而传统和有限角度断层扫描仍受限于旋转速度,运动模糊导致无法分辨这些动态。总体而言,rotation-XMPI相较当前最优熔池成像技术提升了250倍,有效实现每秒25,000个重构体。该方法为增材制造及其他材料过程提供了可扩展的超高速4D成像实用路径。
原文摘要 · Abstract (English)
Advancing additive manufacturing, e.g., laser powder-bed fusion (LPBF), requires resolving rapid processes such as melt-pool dynamics and keyhole evolution in 4D (3D + time). Operando X-ray tomography is a state-of-the-art approach for 4D characterization, but its temporal resolution is fundamentally constrained by the sample rotation speed, limiting achievable 4D imaging rates and preventing the resolution of these fast phenomena. Here we present rotation-enabled X-ray Multi-Projection Imaging (rotation-XMPI), which captures three angularly resolved projections per time step and thereby decouples temporal resolution from the sample rotation speed. Combined with a self-supervised deep-learning reconstruction framework for multi-angle inputs, rotation-XMPI enables high-fidelity 4D imaging at unprecedented speed. We demonstrate the approach in an operando alumina laser-remelting experiment at MAX IV using three beamlets combined with 25 Hz sample rotation. Rotation-XMPI resolves melt-pool morphology and keyhole evolution; in contrast, conventional and limited-angle tomography remain rotation-limited, and motion blur prevents resolving these dynamics. Overall, rotation-XMPI delivers a 250-fold increase relative to state-of-the-art melt-pool imaging, effectively achieving 25,000 reconstructed volumes per second. This method establishes a practical route to scalable ultrafast 4D imaging for additive manufacturing and other materials processes.
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