Planar cameras with high performance and wide field of view (FOV) are critical in various fields, requiring highly compact and integrated technology. Existing wide FOV metalenses show great potential for ultrathin optical components, but there is a set of tricky challenges, such as chromatic aberrations correction, central bright speckle removal, and image quality improvement of wide FOV. We design a neural meta-camera by introducing a knowledge-fused data-driven paradigm equipped with transformer-based network. Such a paradigm enables the network to sequentially assimilate the physical prior and experimental data of the metalens, and thus can effectively mitigate the aforementioned challenges. An ultra-wide FOV meta-camera, integrating an off-axis monochromatic aberration-corrected metalens with a neural CMOS image sensor without any relay lenses, is employed to demonstrate the availability. High-quality reconstructed results of color images and real scene images at different distances validate that the proposed meta-camera can achieve an ultra-wide FOV (>100 deg) and full-color images with the correction of chromatic aberration, distortion, and central bright speckle, and the contrast increase up to 13.5 times. Notably, coupled with its compact size (< 0.13 cm3), portability, and full-color imaging capacity, the neural meta-camera emerges as a compelling alternative for applications, such as micro-navigation, micro-endoscopes, and various on-chip devices.
In order to fabricate the optimized LED plant lamp we demonstrated an optical spectral exploration. According to the mechanism of higher plant photosynthesis process and the spectral analysis we demonstrate an optical design of the LED plant lamp. Furthermore we built two kins of prototypes of the LED plant lamps which are suitable for the photosynthesis of higher green vegetables. Based on the simulation of the lamp box of the different alignment of the plants we carried out the growing experiment of green vegetable and obtain the optimized light illumination as well as the spectral profile. The results show that only blue and red light are efficient for the green leave vegetables. Our work is undoubtedly helpful for the LED plant lamping design and manufacture.
The model of the wall washer lamp and the practical illumination application have been established with a new design of the lens to meet the uniform illumination demand for wall washer lamp based on the Lambertian light sources. Our secondary optical design of freeform surface lens to LED wall washer lamp based on the conservation law of energy and Snell’s law can improve the lighting effects as a uniform illumination. With the relationship between the surface of the lens and the surface of the target, a great number of discrete points of the freeform profile curve were obtained through the iterative method. After importing the data into our modeling program, the optical entity was obtained. Finally, to verify the feasibility of the algorithm, the model was simulated by specialized software, with both the LED Lambertian point source and LED panel source model.
The third-order nonlinear optical properties of graphene oxide (GO) dispersion in distilled water were investigated in femtosecond regime, using a single beam z-scan technique. Induced by a focused Gaussian beam (λ~800 nm) with 150 fs pulse duration, the graphene oxide shows strong nonlinear absorption, which was dominated by reverse saturable absorption (RSA), originates from two-photon absorption (TPA) in GO. In addition, the optical limiting performance of GO was experimentally derived, indicating that the occurrence of RSA make GO a candidate for optical limiting. In addition, the further increasing of input intensity would enhance the nonlinear scattering effects in the sample so that the optical limiting threshold was reached.
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