集成电路制造在线光学测量检测技术：现状、挑战与发展趋势

Xiuguo, 陈修国 Chen; Cai, 王才 Wang; Tianjuan, 杨天娟 Yang; Jiamin, 刘佳敏 Liu; Chengfeng, 罗成峰 Luo; Shiyuan, 刘世元 Liu

doi:10.3788/lop202259.0922025

Cited by 7 publications

(1 citation statement)

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“…Non-imaging measurement technologies, such as laser reflectometers and scatterometers, extract the defect information by measuring the reflectivity and scattering information of the sample at different wavelengths or incident angles. Although the measurement process of non-imaging measurement technology is not as simple and intuitive as imaging measurement technology, and usually involves solving complex inverse problems, its measurement is not limited by the optical diffraction limit and can be used for sub-wavelength and deep sub-wavelength nanostructure measurements [4,5]. KLA-Tencor, an industry-leading semiconductor equipment manufacturer, adapts non-imaging inspection technology in their systems using brightfield illumination, darkfield illumination, or a combination of both [6].…”

Section: Instructionmentioning

confidence: 99%

Spot scanning imaging calibration method based on deviation model for wafer inspection

Qu,

Zhou,

et al. 2024

Phys. Scr.

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The spot scanning defect detection system has good detection performance for wafer defects. However, due to the existence of system assembly errors, the wafer defect inspection system could not scan following the planned trace, which resulted in distortion of the reconstructed image and had a greater impact on defect feature extraction and accurate defect location. The system deviation calibration and adjustment can further facilitate the accuracy of the system position and image reconstruction. To address this issue, the causes and shapes of imaging distortion were analyzed and simulated, and a simple and effective calibration method based on a scanning deviation model for the spot scanning defect detection system was proposed. First, a scanning deviation model was established following the characteristics of the spot scanning system, and different degrees of reconstructed image distortion were simulated and analyzed as the system deviation changes. Then, an 8-inch wafer with a grid was used as the calibrator and scanned using the developed spot scanning system. Serveral grid corners in the reconstructed image are selected and used as the calibration feature points. The constraint function is constructed using the equidistant features between adjacent grid points, and then the quasi-Newton method is used to optimize the parameters of the function to obtain the best deviation estimation of the spot scanning system. To prove the validity of the estimated deviation parameters, another patterned wafer was scanned and the distortion image was used for reconstruction. The experiment demonstrated that an accurate and distortion-free wafer image can be reconstructed using the calibrated deviation parameters, and the root mean square error of the measured distance between two points of interest was only 0.61 pixels, which proved the effectiveness of the proposed calibration method.

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Section: Instructionmentioning

confidence: 99%

Spot scanning imaging calibration method based on deviation model for wafer inspection

Qu,

Zhou,

et al. 2024

Phys. Scr.

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Curvelet coefficient prediction-based image super-resolution method for precision measurement

Wu,

Liang,

Tan

et al. 2023

Measurement

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Full-flow surface defect identification method based on spot scanning scattering for unpatterned wafer

Qu,

Zhou,

et al. 2024

J. Inst.

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As the critical dimensions of semiconductor manufacturing processes gradually decrease, the requirements for production yield management become increasingly stringent. During the manufacturing process, there are many different types of defects, such as micron-sized particles, millimeter-sized scratches, etc. Multiple categories and different scales bring great challenges to the detection and identification of defects. This paper provides a full-flow surface defect identification method based on spot scanning scattering for unpatterned wafers. First, an adaptive threshold method with dynamic kernel windows is used to perform line-by-line scanning inspection of the wafer Mercator image. The 3σ decision strategy is used to avoid the impact of defects on background estimation and to improve detection sensitivity. After morphological processing, connected domain analysis is performed to obtain the defect mask, and feature information such as the shape, size, and distribution of the defect is extracted. Finally, the defect identification is performed by rules based binning, and the identified defects are converted into wafer polar coordinate image for display and analysis. In the experiments, the proposed method is used to identify micron-scale particles as well as large scratches on the millimeter scale for SiC wafers. Relative to the actual production rate requirement of 20 wafers per hour, the analysis time for a 6-inch wafer is 24.4 s, which can meet the requirement. Meanwhile, the test results illustrate the effectiveness of the method. The proposed method is recommended for early-stage defect detection and identification of unpatterned wafers.

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集成电路制造在线光学测量检测技术：现状、挑战与发展趋势

Cited by 7 publications

References 0 publications

Spot scanning imaging calibration method based on deviation model for wafer inspection

Spot scanning imaging calibration method based on deviation model for wafer inspection

Curvelet coefficient prediction-based image super-resolution method for precision measurement

Full-flow surface defect identification method based on spot scanning scattering for unpatterned wafer

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