A Spatial-Physics Informed Model for 3D Spiral Sample Scanned by SQUID Microscopy

TL;DR

This paper introduces a spatial-physics informed model (SPIM) for 3D spiral samples scanned with SQUID microscopy, enhancing magnetic image quality and alignment for better current density inversion in non-destructive testing.

Contribution

The paper presents a novel SPIM that integrates image enhancement, alignment, and physics-based inversion to improve magnetic field analysis in SQUID microscopy.

Findings

SPIM improves I-channel sharpness by 0.3%.

SPIM reduces Q-channel sharpness by 25%.

Successfully removes 0.30 rotational and skew misalignments.

Abstract

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.