COMBINED MODELING AND MACHINE LEARNING IN OPTICAL METROLOGY

    公开(公告)号:US20240159656A1

    公开(公告)日:2024-05-16

    申请号:US18503783

    申请日:2023-11-07

    IPC分类号: G01N21/21

    CPC分类号: G01N21/211

    摘要: Complex three-dimensional structures in semiconductor devices are measured using Mueller matrix paired off-diagonal elements to generate machine learning predictions of asymmetric parameters of the device and determine dimensional parameters based on one or more Mueller matrix elements and the asymmetric parameters. The measurements of the device may be performed at different azimuth angles selected based on sensitivity to the asymmetric parameters and the dimensional parameters. Additionally, the Mueller matrix elements may be generated based on measurements performed at azimuth angles that are 180° apart to eliminate asymmetric noise from the measurement tool. One or more models of the device may be used with the Mueller matrix elements to generate dimensional parameter information and optionally preliminary asymmetrical parameters. The determined asymmetric parameters may be fed forward to the one or more models for determining the dimensional parameters to suppress a correlation between dimensional parameters and asymmetric parameters of the device.