Affiliation:
1. Tianjin University
2. Key Laboratory of Optoelectronics Information and Technology (Ministry of Education),
Abstract
Discriminative internal imaging for different chip layers can pinpoint the location of critical defect in the flip chips, yet existing methods face challenges in in-line imaging to identify defects or structures from the sub-surface within the silicon substrate and their underlying coating. To address these challenges, we develop and verify layered elasto-optic models for photoacoustic remote sensing microscopy (PARS) that distinguish structures from multi-layers within a single device for in-line flip-chip wafer inspection. A finite-difference time-domain algorithm based on transparent source (TS-FDTD) accurately predicts different initial slopes of PARS signals within the silicon-metal and the silicon-air models. The initial slopes of PARS signals are experimentally validated and utilized for discriminative non-destructive imaging of the interdigital electrode chips and silicon cracks within the same region of interest. PARS with layered elasto-optic models and non-contact fast scanning has the potential for in-line detection of defects from various layered structures with different refractive indices, offering an approach for discriminative non-destructive testing (NDT) of flip-chip and layered structures.
Funder
National Natural Science Foundation of China
Tianjin Municipal Fund for Distinguished Young Scholars
International Science and Technology Independent cooperation Project of Shenzhen
Natural Science Foundation of Shenzhen Municipality
2022 Shenzhen College and University Stability Support Plan