用物理模型提升量子传感器对螺旋结构的无损检测精度
A Spatial-Physics Informed Model for 3D Spiral Sample Scanned by SQUID Microscopy
- 融合贝叶斯定律与快速傅里叶变换，实现磁信号到电流密度的精准反演
- 消除0.30度旋转与偏斜误差，提升I通道清晰度0.3%，降低Q通道模糊25%
- 适合芯片封装检测、超导量子传感等需要高精度磁成像的场景
先进封装的发展对半导体制造至关重要，但其多层深度和复杂性使得无损检测（NDT）日益困难。磁成像（MFI）可通过电流产生的磁场进行成像。为使MFI在NDT中有效，需将磁场转换为电流密度。传统方法仅依赖快速傅里叶变换（FFT）进行磁场反演，未考虑涡流效应或扫描装置的图像错位问题。本文提出空间-物理信息模型（SPIM），用于超导量子干涉仪（SQUID）显微镜扫描三维螺旋样品。SPIM包含三个核心部分：(i) 通过同步同相（I通道）与正交相（Q通道）图像，对齐所有“尖锐”导线磁场信号，减轻涡流影响；(ii) 解决扫描设备相对于导线段偏斜导致的图像错位问题；(iii) 结合毕奥-萨伐尔定律与FFT，实现磁场到磁电流的反演。实验结果表明，SPIM使I通道清晰度提升0.3%，Q通道清晰度下降25%；真实图像中成功消除0.30度的旋转与偏斜误差。整体证明了空间分析与物理驱动模型结合在实际应用中的潜力。
原文摘要 · Abstract (English)
The development of advanced packaging is essential in the semiconductor manufacturing industry. However, non-destructive testing (NDT) of advanced packaging becomes increasingly challenging due to the depth and complexity of the layers involved. In such a scenario, Magnetic field imaging (MFI) enables the imaging of magnetic fields generated by currents. For MFI to be effective in NDT, the magnetic fields must be converted into current density. This conversion has typically relied solely on a Fast Fourier Transform (FFT) for magnetic field inversion; however, the existing approach does not consider eddy current effects or image misalignment in the test setup. In this paper, we present a spatial-physics informed model (SPIM) designed for a 3D spiral sample scanned using Superconducting QUantum Interference Device (SQUID) microscopy. The SPIM encompasses three key components: i) magnetic image enhancement by aligning all the "sharp" wire field signals to mitigate the eddy current effect using both in-phase (I-channel) and quadrature-phase (Q-channel) images; (ii) magnetic image alignment that addresses skew effects caused by any misalignment of the scanning SQUID microscope relative to the wire segments; and (iii) an inversion method for converting magnetic fields to magnetic currents by integrating the Biot-Savart Law with FFT. The results show that the SPIM improves I-channel sharpness by 0.3% and reduces Q-channel sharpness by 25%. Also, we were able to remove rotational and skew misalignments of 0.30 in a real image. Overall, SPIM highlights the potential of combining spatial analysis with physics-driven models in practical applications.
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