Dr. Zhidan Lei Profile

Dr. Zhidan Lei

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Proceedings Article | 10 December 2024 Paper

Non-destructive measurement of temperature in the micro-area wafer using Mueller matrix spectroscopic ellipsometry

Qimeng Sun, Xing Jin, Bingxu Ma, Zhidan Lei, Xiaoli Liu, Jun Peng, Lin Yang

Proceedings Volume 13423, 1342310 (2024) https://doi.org/10.1117/12.3052989

KEYWORDS: Temperature metrology, Mueller matrices, Semiconducting wafers, Refractive index, Spectroscopic ellipsometry, Deep learning, Reliability, Nondestructive evaluation

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As the number of 3D stacking layers continues to increase and the thermal design power of logic chips escalates, thermal management is confronted with unprecedented challenges. The temperature of the surface to be treated is also a parameter that is difficult to measure non-invasively. The standard technique is infrared (IR) pyrometry. However, due to the transparency of Si wafers in the IR spectrum, it cannot be used in the low-temperature regime (0°C ~ 400°C). In this study, a new low-temperature thermal measurement method was developed, utilizing Mueller Matrix Spectroscopic Ellipsometry (MMSE) combined with Thermo-Optical Coefficients (TOC). Firstly, the coefficients of the Cauchy dispersion equation for Si-based SiO₂ films were measured at different temperatures. The experimental results indicated that the refractive index of SiO₂ films exhibits high sensitivity to temperature in the ultraviolet to visible spectra. Subsequently, MMSE was combined with deep learning to reverse characterize the temperature in the chip overlay region. The results indicated that effective Mueller matrix elements and multi-channel deep learning could accurately identify the temperature in the overlay region, with an accuracy of 99.81% and a recognition precision of 1K. The proposed method contributes to optimizing automatic process control, alleviating wafer deformation and overlay errors caused by thermal management, thereby enhancing the reliability of high-bandwidth memory.

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