Shao Yifeng, Weerdenburg Sven, Seifert Jacob, Urbach H Paul, Mosk Allard P, Coene Wim
Imaging Physics Department, Applied Science Faculty, Delft University of Technology, Lorentzweg 1, Delft, 2628 CJ, The Netherlands.
Nanophotonics, Debye Institute for Nanomaterials Science and Center for Extreme Matter and Emergent Phenomena, Utrecht University, P.O. Box 80000, Utrecht, 3508 TA, The Netherlands.
Light Sci Appl. 2024 Aug 19;13(1):196. doi: 10.1038/s41377-024-01558-3.
Ptychographic extreme ultraviolet (EUV) diffractive imaging has emerged as a promising candidate for the next generationmetrology solutions in the semiconductor industry, as it can image wafer samples in reflection geometry at the nanoscale. This technique has surged attention recently, owing to the significant progress in high-harmonic generation (HHG) EUV sources and advancements in both hardware and software for computation. In this study, a novel algorithm is introduced and tested, which enables wavelength-multiplexed reconstruction that enhances the measurement throughput and introduces data diversity, allowing the accurate characterisation of sample structures. To tackle the inherent instabilities of the HHG source, a modal approach was adopted, which represents the cross-density function of the illumination by a series of mutually incoherent and independent spatial modes. The proposed algorithm was implemented on a mainstream machine learning platform, which leverages automatic differentiation to manage the drastic growth in model complexity and expedites the computation using GPU acceleration. By optimising over 200 million parameters, we demonstrate the algorithm's capacity to accommodate experimental uncertainties and achieve a resolution approaching the diffraction limit in reflection geometry. The reconstruction of wafer samples with 20-nm high patterned gold structures on a silicon substrate highlights our ability to handle complex physical interrelations involving a multitude of parameters. These results establish ptychography as an efficient and accurate metrology tool.
叠层成像极端紫外（EUV）衍射成像已成为半导体行业下一代计量解决方案的一个有前途的候选技术，因为它可以在反射几何结构中对纳米级的晶圆样品进行成像。由于高谐波产生（HHG）EUV光源的重大进展以及计算硬件和软件的进步，该技术最近引起了广泛关注。在本研究中，引入并测试了一种新颖的算法，该算法能够进行波长复用重建，提高测量通量并引入数据多样性，从而实现对样品结构的准确表征。为了解决HHG光源固有的不稳定性，采用了一种模态方法，该方法通过一系列相互非相干且独立的空间模式来表示照明的交叉密度函数。所提出的算法在主流机器学习平台上实现，该平台利用自动微分来管理模型复杂度的急剧增长，并通过GPU加速加快计算速度。通过优化超过2亿个参数，我们展示了该算法适应实验不确定性的能力，并在反射几何结构中实现了接近衍射极限的分辨率。在硅衬底上对具有20纳米高图案化金结构的晶圆样品进行重建，突出了我们处理涉及众多参数的复杂物理相互关系的能力。这些结果确立了叠层成像作为一种高效且准确的计量工具。
