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Long wave infrared (LWIR) cameras play a pivotal role across diverse applications due to their distinctive features. The growing demand for high-performance thermal imaging optics, characterized by a broad working bandwidth, large field of view (FOV), aberration-free design, lightweight construction, compactness, and cost-effectiveness, poses significant challenges for LWIR lens design. Here, we propose an inverse design method for LWIR hybrid metalenses, specifically aiming to achieve aberration-corrected thermal imaging with both a large FOV and a broad working bandwidth. Our approach involves optimizing phase profiles of metalens' unit cells guided by a loss function that compares the hybrid lens design to diffraction-limited results for various incident angles and wavelengths. As a result, we demonstrate an aberration-corrected thermal camera with a 30° FOV and an achromatic working bandwidth spanning the entire LWIR atmospheric window (8 to 14 μm). Significantly, the total optical path length, the entrance pupil to the sensor plane of the charge-coupled device (CCD), is a mere 13.6 mm. Our work merits advantages in the FOV, working bandwidth, and compactness, which surpass state-of-the-art LWIR hybrid metalens designs and find numerous imaging and sensing applications.
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http://dx.doi.org/10.1021/acsnano.4c12546 | DOI Listing |
RSC Adv
August 2025
College of Materials Science and Engineering, Jilin University of Chemical Technology Jilin 132022 PR China
To contribute to the circular and sustainable economy framework, waste tire rubber reclamation by extracting carbon black through pyrolysis and heat treatment and then ingeniously designing it as an electromagnetic wave absorbing (EWA) material is proposed herein. The results showed that the pyrolysis-recycled carbon black (RCB) was heterogeneous with multiple interfaces, making it suitable for EWA application. The RCB was processed at 500 °C-1000 °C to study the changes in the composite and microstructure as well as the EWA properties.
View Article and Find Full Text PDFMicrosyst Nanoeng
September 2025
School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, China.
Piezoelectric MEMS loudspeakers based on cantilever diaphragms have demonstrated promising electroacoustic efficiency and low-frequency sound pressure level (SPL). However, their total harmonic distortion (THD) significantly increases near the first resonant frequency, and high-frequency SPL (above 10 kHz) rapidly decreases due to the resonance frequency and bandwidth limitations, severely affecting sound quality. This work presents a piezoelectric MEMS loudspeaker featuring a 2.
View Article and Find Full Text PDFJ Vis
September 2025
Institute de Neurosciences de la Timone, Aix-Marseille Univ, CNRS, Marseille, France.
The visual systems of animals work in diverse and constantly changing environments where organism survival requires effective senses. To study the hierarchical brain networks that perform visual information processing, vision scientists require suitable tools, and Motion Clouds (MCs)-a dense mixture of drifting Gabor textons-serve as a versatile solution. Here, we present an open toolbox intended for the bespoke use of MC functions and objects within modeling or experimental psychophysics contexts, including easy integration within Psychtoolbox or PsychoPy environments.
View Article and Find Full Text PDFModern wireless systems require compact, low-profile, and multiband antennas. The designs offer high performance without structural complications. The classic, traditional single-band antenna mostly does not fit the bandwidth of applications.
View Article and Find Full Text PDFNanophotonics
August 2025
School of Science, Minzu University of China, Beijing 100081, China.
Optical neural networks (ONNs) have demonstrated unique advantages in overcoming the limitations of traditional electronic computing through their inherent physical properties, including high parallelism, ultra-wide bandwidth, and low power consumption. As a crucial implementation of ONNs, on-chip diffractive optical neural network (DONN) offers an effective solution for achieving highly integrated and energy-efficient machine learning tasks. Notably, wavelength, as a fundamental degree of freedom in optical field manipulation, exhibits multidimensional multiplexing capabilities that can significantly enhance computational parallelism.
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