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[Editor's Pick] Current Optics and Photonics Vol. 8 no. 6 (2024 December)_2nd

사무국 hit 240 date 2024-12-26

Binary-optimization-based Multilayers and Their Practical Applications

Geon-Tae Park, Rira Kang, Byunghong Lee, and Sun-Kyung Kim*

 

Current Optics and Photonics  Vol. 8 No. 6 (2024 December), pp. 545-561
DOI: https://doi.org/10.3807/COPP.2024.8.6.545 

Fig. 1  Workflow of binary-optimization-based multilayer design and its applications. (a) Schematic of the iterative optimization cycle, composed of four primary steps [53]. (b) (i) Schematic of antireflective coatings (ARC) applied to a lens, designed to minimize reflectance at the target wavelength λ0 over a wide range of incident angles θ. (ii) Illustration of transparent radiative coolers (TRCs) for energy-saving windows, engineered to reflect ultraviolet and near-infrared light while transmitting visible light, and maintaining high emissivity within the atmospheric window. The red line represents the target transmittance spectrum, and the blue line represents the target emissivity spectrum for an ideal transparent radiative cooler. (iii) Schematic of bandpass filters for thermophotovoltaics (TPVs), designed to enhance the efficiency of the photovoltaic (PV) cell by selective emission. The red dashed line represents the spectral irradiance of a blackbody IBB, and the blue solid line represents the external quantum efficiency (EQE) multiplied by the intensity of blackbody radiation (IBB). The green solid line shows the target spectrum of a selective emitter with unit emissivity.

 

Keywords: Binary optimization, Machine learning, Multilayer, Optical coating, Optical design
OCIS codes: (200.0200) Optics in computing; (220.0220) Optical design and fabrication; (310.0310) Thin films; (310.1210) Antireflection coatings; (310.6845) Thin film devices and applications


Abstract
Multilayers composed of two or more materials enable the regulation of transmission, reflection, and absorption spectra across one or multiple bands. While analytic formulas based on well-established interference conditions, such as those employed in single-, double-, and triple-layer antireflective coatings and distributed Bragg reflectors, have provided suitable solutions for traditional optical coatings, they are limited in achieving the intricate spectral characteristics required by multifunctional optical coatings. To overcome this limitation, a variety of machine learning-based design algorithms have been rigorously studied. Among these, binary optimization has proven particularly effective for designing multilayer optical coatings. This approach transforms a given multilayer into a binary vector with multiple bits, where each bit represents one of the constituent materials, and quickly identifies an optimal figureof-merit by analyzing the interactions among the elements of the binary vector. In this review article, we elucidate the principles of binary optimization and explore its applications in the design of multilayers for antireflective coatings for high-numerical-aperture lenses, transparent radiative coolers for energysaving windows, and bandpass filters for thermophotovoltaics. Furthermore, we address the limitations, challenges, and perspectives of machine learning-based optical design to guide directions for future research in this field.

 

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