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基于图像的离线的光刻工艺稳定性控制方法
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Abstract:
光刻工艺中，光刻条件的稳定性对于光刻后的晶圆上图像质量的稳定起到关键作用。针对光刻条件稳定性的监控，目前的做法是使用散射仪和专门设计的光栅图样，从散射轮廓曲线来推断光刻实际工艺条件。这种方法需要特殊的散射仪工具，并且对光刻胶下的膜堆叠层变化敏感。为了解决上述难题，本文提出一种基于图像的离线光刻工艺稳定性监测方法。首次提出利用神经网络的办法，提取CDSEM图像不同光刻工艺下的特征信息，并与空间像进行一一对应。该方法取代了利用散射仪观察光刻后图像的办法，并避免了实际的光刻工艺流程，对于产线上光刻机稳定性的检测具有重要意义。
In the lithography process, the stability of lithography conditions plays a crucial role in stabilizing the image quality on the wafer. The current approach for monitoring the stability of lithography conditions is to use a scatterometer and specially designed grating patterns to infer the actual lithography process conditions from the scattering profile curve. This method requires special scatterometer tools and is sensitive to changes in the film stacking layer under the photoresist. To address the aforementioned challenges, this article proposes an image-based offline lithography process stability monitoring method. We propose the use of neural networks to extract feature information from CDSEM images under different lithography processes firstly. And match the CDSEM image with the spatial image. This method replaces the method of observing lithography images using a scatterometer and avoids the actual lithography process, which is of great significance for detecting the stability of lithography machines on the production line.
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