Jiang Zijie, Gan Zhuofei, Liang Chuwei, Li Wen-Di
Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, China.
Nanophotonics. 2024 Jan 16;13(7):1181-1189. doi: 10.1515/nanoph-2023-0798. eCollection 2024 Mar.
As a non-destructive and rapid technique, optical scatterometry has gained widespread use in the measurement of film thickness and optical constants. The recent advances in deep learning have presented new and powerful approaches to the resolution of inverse scattering problems. However, the application of deep-neural-network-assisted optical scatterometry for nanostructures still faces significant challenges, including poor stability, limited functionalities, and high equipment requirements. In this paper, a novel characterization method is proposed, which employs deep-neural-network-assisted ellipsometry to address these challenges. The method processes ellipsometric angles, which are measured by basic ellipsometers, as functional signals. A comprehensive model is developed to profile nano-gratings fabricated by diverse techniques, by incorporating rounded corners, residual layers, and optical constants into an existing model. The stability of the model is enhanced by implementing several measures, including multiple sets of initial values and azimuth-resolved measurements. A simple compensation algorithm is also introduced to improve accuracy without compromising efficiency. Experimental results demonstrate that the proposed method can rapidly and accurately characterize nano-gratings fabricated by various methods, with relative errors of both geometric and optical parameters well controlled under 5 %. Thus, the method holds great promise to serve as an alternative to conventional characterization techniques for measurement.
作为一种无损且快速的技术，光学散射测量法在薄膜厚度和光学常数测量中得到了广泛应用。深度学习的最新进展为解决逆散射问题提供了新的强大方法。然而，深度神经网络辅助的光学散射测量法在纳米结构中的应用仍面临重大挑战，包括稳定性差、功能有限以及设备要求高。本文提出了一种新颖的表征方法，该方法采用深度神经网络辅助椭圆偏振测量法来应对这些挑战。该方法将由基本椭圆偏振仪测量的椭圆偏振角作为功能信号进行处理。通过将圆角、残余层和光学常数纳入现有模型，开发了一个综合模型来剖析通过各种技术制造的纳米光栅。通过实施包括多组初始值和方位角分辨测量在内的多种措施，提高了模型的稳定性。还引入了一种简单的补偿算法，在不影响效率的情况下提高准确性。实验结果表明，所提出的方法能够快速、准确地表征通过各种方法制造的纳米光栅，几何参数和光学参数的相对误差均能很好地控制在5%以内。因此，该方法有望成为传统表征技术用于测量的替代方法。
