This paper presents the optimization design of a miniaturized five-element wide-angle fisheye lens using a deep learning algorithm. Zemax optical design software was used to simulate and optimize the wide-angle fisheye lens. A deep learning algorithm helped to find the best combination of different lens materials. We first used six lens elements as an initial configuration to design miniaturized wide-angle fisheye lenses using the optimization process. The optical system components were gradually decreased to five lens elements. Both OKP4HT and polymethyl methacrylate (PMMA) plastic aspheric lenses were selected to replace the second spherical glass lens in the original design. We propose two types of wide-angle fisheye lens designs with four spherical lenses and one aspheric lens. The results for these designs indicated a viewing angle of 174°, a total length of less than 15 mm, a spot size of less than 6 μm, lateral color within ±1 μm, field curvature within ±0.02 mm, and F-θ distortion of ±3.5%. In addition, the MTF value was larger than 0.4 at the spatial frequency of 100 cycles/mm.

This study presents a multilayer design and fabrication of an optical notch filter for enhancing visual quality. A cost-effective multilayer design of notch filter with low surface roughness and low residual stress is proposed. A 9-layer notch filter composed of SiO2 and Nb2O5 with a central wavelength of 480 nm is prepared by electron beam evaporation combined with ion-assisted deposition. The optical transmittance, residual stress, and surface morphology are measured by a UV/VIS/NIR spectrophotometer, Twyman-Green interferometer and field emission scanning electron microscopy (FE-SEM). The transmittance of the notch filter at the central wavelength is above 15%, and the average transmittance of the transmission band is about 80%. The residual stress of the notch filter is −0.235 GPa, and the root mean square surface roughness is 1.85 nm. For improving the visual quality, a good image contrast can be obtained by observing the microscopic image using the proposed notch filter.

This study presents the optimal process parameters of zirconium nitride (ZrN) thin films prepared by ion-assisted deposition (IAD) technology combined with electron-beam evaporation based on plasma surface treatment and the Taguchi method. We use Minitab statistical software (Version 20.2.0) and L9 orthogonal array parameter design combined with the response surface method (RSM). The quadratic polynomial regression equation was optimized by the RSM. Based on the control factor screening test of the Taguchi method, we determined the most critical factor combination for the process and derived the optimized process parameters of the ZrN thin films. In the coating experiments, we successfully achieved the optimal combination of good refractive index, adequate residual stress, and lower surface roughness on B270 glass substrates. These results indicate that the optimized preparation process can simultaneously achieve several desirable properties, improving the performance and application of ZrN thin films. Furthermore, our research method not only reduces the number of experiments and costs but also improves the efficiency of research and development. By screening key factors and optimizing process parameters, we can find the best process parameter more rapidly, reduce the demand for expenses given materials and equipment costs, and contribute to improving the electron-beam evaporation process. According to the experimental results, it can be observed that under certain conditions, the properties of ZrN thin films reached optimal values. These results are highly useful for optimizing the process parameters of ZrN thin films and provide a basis for further improvement of the thin film properties.

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