With the decrease in critical dimension of patterned lithography structures, new challenges have emerged in the metrology domain. Eventually, no step of shrinkage modelling calibration nor AI-driven image post processing are needed which implies a gain on simplicity and avoids modelling errors. The benefits of adopting this approach range from reducing the shrinkage effects to improving SEM image acquisition time. Another way of seeing it is, while keeping the same precision, a model-based contour extraction approach can significantly reduce the requested image frame number. We observe that this model-based approach is more robust to noise than standard algorithms by 21% on synthetic data and by 36% on experimental data. We demonstrate that a model-based contour extraction algorithm is able to precisely characterize SEM-induced 2D resist shrinkage. This approach is applied onto both synthetic and experimental CD-SEM images with various patterns (mostly 2D) and noise levels to assess the influence of image integration (frame number) on the contour detection and CD measurement. In this article, we evaluate the benefits of relying on a model-based contour extraction approach for performing measurements. There is thus a need for an accurate, robust to noise, and purely deterministic edge detection algorithm. In addition, post-treatment of these shrinkage effects requires compensation algorithms such as artificial intelligence (AI)- driven algorithms, that are another contributor to the error budget of metrology systems. ![]() Moreover, diminishing noise in CD-SEM acquisition leads to resist shrinkage due to exposure time increase. One of the issues when dealing with CD-SEM metrology is that the results are noise sensitive. In particular, OPC model’s accuracy can be highly improved using contours metrology. Contour metrology on CD-SEM images has become essential for characterization, modelling, and control of advanced lithography processes. ![]() ![]() Among metrology tools in the semi-conductor manufacturing, critical dimension scanning electron microscopes (CD-SEM) are the most broadly used, especially due to their high resolution, low destructivity, and high throughput.
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