Circuit Subsurface Characterization Based on Magnetic Gradient Tensor Quantum Imaging

With the advancement in electronic device integration, multilayer circuits are now capable of arranging high-capacity wiring within limited spaces, which make them extensively applicable in the electronics industry. It is essential to perform inspections on subsurface circuits to guarantee advancements in manufacturing processes and designs. This article presents a method for magnetic gradient tensor imaging of multilayer circuits under operational conditions, utilizing a quantum wide-field microscope based on nitrogen-vacancy (NV) centers in diamond. Compared to vector magnetic field imaging and scalar magnetic field imaging, the magnetic gradient tensor imaging method exhibits superior boundary recognition capabilities and can effectively mitigate blurring issues arising from magnetic field superposition and divergence, thereby enabling the acquisition of more precise circuit structure details. By packaging the vector magnetic field pixel matrix and performing continuous differential operations on adjacent pixels, the calculation of magnetic gradient tensor imaging was successfully achieved. In this article, a dual-layer circuit with a current of 2 and 0.1 A was tested, with an interlayer spacing of $200~\mu $ m. The highest recognition accuracy for magnetic gradient tensor imaging reached 98.2%. This quantum imaging-based method successfully achieved the noninvasive detection of subsurface defects in multilayer circuits under working conditions, which have great potential in the areas of electromagnetic compatibility testing and electronic device characterization.