Ansuinelli Paolo, Coene Wim M J, Urbach H Paul
Appl Opt. 2020 Jul 10;59(20):5937-5947. doi: 10.1364/AO.395446.
The development of actinic mask metrology tools represents one of the major challenges to be addressed on the roadmap of extreme ultraviolet (EUV) lithography. Technological advancements in EUV lithography result in the possibility to print increasingly fine and highly resolved structures on a silicon wafer; however, the presence of fine-scale defects, interspersed in the printable mask layout, may lead to defective wafer prints. Hence, the development of actinic methods for review of potential defect sites becomes paramount. Here, we report on a ptychographic algorithm that makes use of prior information about the object to be retrieved, generated by means of rigorous computations, to improve the detectability of defects whose dimensions are of the order of the wavelength. The comprehensive study demonstrates that the inclusion of prior information as a regularizer in the ptychographic optimization problem results in a higher reconstruction quality and an improved robustness to noise with respect to the standard ptychographic iterative engine (PIE). We show that the proposed method decreases the number of scan positions necessary to retrieve a high-quality image and relaxes requirements in terms of signal-to-noise ratio (SNR). The results are further compared with state-of-the-art total variation-based ptychographic imaging.
光化掩膜计量工具的发展是极紫外(EUV)光刻路线图中需要应对的主要挑战之一。EUV光刻技术的进步使得在硅晶圆上印刷越来越精细且分辨率高的结构成为可能;然而,在可印刷掩膜版图中散布的微小缺陷可能会导致晶圆印刷出现缺陷。因此,开发用于检查潜在缺陷位置的光化方法变得至关重要。在此,我们报告一种叠层成像算法,该算法利用通过严格计算生成的关于待检索对象的先验信息,以提高尺寸在波长量级的缺陷的可检测性。全面研究表明,在叠层成像优化问题中纳入先验信息作为正则化项,相对于标准叠层成像迭代引擎(PIE),可提高重建质量并增强对噪声的鲁棒性。我们表明,所提出的方法减少了获取高质量图像所需的扫描位置数量,并放宽了对信噪比(SNR)的要求。结果还与基于全变差的最新叠层成像进行了比较。