Yu Jae-Seon, Jung Serang, Cho Jin-Woo, Park Geon-Tae, Kats Mikhail, Kim Sun-Kyung, Lee Eungkyu
Department of Applied Physics, Kyung Hee University, Yongin-Si, Gyonggi-Do, 17104, Republic of Korea.
Department of Electronic Engineering, Kyung Hee University, Yongin-Si, Gyonggi-Do, 17104, Republic of Korea.
Nanophotonics. 2024 Aug 27;13(21):4067-4078. doi: 10.1515/nanoph-2024-0360. eCollection 2024 Sep.
Achieving long-wavelength infrared (LWIR) cameras with high sensitivity and shorter exposure times faces challenges due to series reflections from high-refractive index lenses within compact optical systems. However, designing effective antireflective coatings to maximize light throughput in these systems is complicated by the limited range of transparent materials available for the LWIR. This scarcity narrows the degrees of freedom in design, complicating the optimization process for a system that aims to minimize the number of physical layers and address the inherent large refractive mismatch from high-index lenses. In this study, we use discrete-to-continuous optimization to design a subwavelength-thick antireflective multilayer coating on high-refractive index Si substrate for LWIR cameras, where the coating consists of few (e.g., five) alternating stacks of high- and low-refractive-index thin films (e.g., Ge-YF, Ge-ZnS, or ZnS-YF). Discrete optimization efficiently reveals the configuration of physical layers through binary optimization supported by a machine learning model. Continuous optimization identifies the optimal thickness of each coating layer using the conventional gradient method. As a result, considering the responsivity of a LWIR camera, the discrete-to-continuous strategy finds the optimal design of a 2.3-μm-thick antireflective coating on Si substrate consisting of five physical layers based on the Ge-YF high-low index pair, showing an average reflectance of 0.54 % within the wavelength range of 8-13 μm. Moreover, conventional thin-film deposition (e.g., electron-beam evaporator) techniques successfully realize the designed structure, and Fourier-transform infrared spectroscopy (FTIR) and thermography confirm the high performance of the antireflective function.
由于紧凑型光学系统中高折射率透镜产生的系列反射,实现具有高灵敏度和更短曝光时间的长波红外(LWIR)相机面临挑战。然而,为这些系统设计有效的抗反射涂层以最大化光通量却因LWIR可用的透明材料范围有限而变得复杂。这种稀缺性缩小了设计的自由度,使旨在最小化物理层数并解决高折射率透镜固有的大折射率失配问题的系统的优化过程变得复杂。在本研究中,我们使用离散到连续的优化方法,为LWIR相机在高折射率硅衬底上设计了一种亚波长厚度的抗反射多层涂层,该涂层由少数(例如五层)高折射率和低折射率薄膜(例如锗 - 钇氟化物、锗 - 硫化锌或硫化锌 - 钇氟化物)交替堆叠组成。离散优化通过机器学习模型支持的二元优化有效地揭示了物理层的配置。连续优化使用传统的梯度方法确定每个涂层的最佳厚度。结果,考虑到LWIR相机的响应度,离散到连续的策略找到了基于锗 - 钇氟化物高低折射率对的由五个物理层组成的硅衬底上2.3μm厚抗反射涂层的最佳设计,在8 - 13μm波长范围内显示出0.54%的平均反射率。此外,传统的薄膜沉积(例如电子束蒸发器)技术成功实现了设计结构,傅里叶变换红外光谱(FTIR)和热成像证实了抗反射功能的高性能。