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Abstract Metalenses, with their ultrathin thicknesses and their ease for achieving ultra small diameters, offer a promising alternative to refractive lenses in miniaturized imaging systems, such as endoscopes, potentially enabling applications in tightly confined spaces. However, traditional metalenses suffer from strong chromatic aberrations, limiting their utility in multi-color imaging. To address this limitation, here we present an inverse-designed polychromatic metalens with a diameter of 680 μm, focal length of 400 μm, and low dispersion across 3 distinct wavelengths at 643 nm, 532 nm, and 444 nm. The metalens collimates and steers light emitted from a scanning fiber tip, generating scanning beams across a 70° field-of-view to provide illumination for a scan-based imaging. The metalens provides a close-to-diffraction-limited 0.5° angular resolution, only restricted by the effective aperture of the system. The average relative efficiency among three design wavelengths is around 32% for on-axis angle and 13% averaged across the entire field-of-view. This work holds promise for the application of metalenses in endoscopes and other miniaturized imaging systems. 

Abstract Subwavelength diffractive optics known as meta-optics have demonstrated the potential to significantly miniaturize imaging systems. However, despite impressive demonstrations, most meta-optical imaging systems suffer from strong chromatic aberrations, limiting their utilities. Here, we employ inverse-design to create broadband meta-optics operating in the long-wave infrared (LWIR) regime (8-12μm). Via a deep-learning assisted multi-scale differentiable framework that links meta-atoms to the phase, we maximize the wavelength-averaged volume under the modulation transfer function (MTF) surface of the meta-optics. Our design framework merges local phase-engineering via meta-atoms and global engineering of the scatterer within a single pipeline. We corroborate our design by fabricating and experimentally characterizing all-silicon LWIR meta-optics. Our engineered meta-optic is complemented by a simple computational backend that dramatically improves the quality of the captured image. We experimentally demonstrate a six-fold improvement of the wavelength-averaged Strehl ratio over the traditional hyperboloid metalens for broadband imaging. 

Abstract Buckling is a structural phenomenon that can induce significant motion with minimal input variation. Electrothermal bimorphs, with their simple input and compact design, can leverage out-of-plane buckling motion for a broad range of applications. This paper presents the development of analytical electrothermal and structural models for such bimorphs. The electrothermal model calculates the temperature distribution within the bimorph caused by electrothermal heating, providing a 2D explicit analytical expression for estimating temperature along the bimorph’s length and cross-section. Nonhomogeneous heating leads to varying strains, which induce axial forces and moments along the bimorph’s neutral plane, varying with thermal expansion. The structural model derives the governing equation of deformation for the bimorph by analyzing internal strains and stresses resulting from deformation, electrothermal heating, and residual stresses. An analytical solution for deflection is obtained, incorporating infinite sums of heating and buckling modes, with closed-form equivalent expressions when possible. The bimorph’s behavior under different scenarios of residual stresses and electrothermal heating is elucidated based on the analytical model. Comparisons with finite element simulations demonstrated excellent agreement, highlighting the high accuracy of the proposed models. 

Abstract Light’s ability to perform massive linear operations in parallel has recently inspired numerous demonstrations of optics-assisted artificial neural networks (ANN). However, a clear system-level advantage of optics over purely digital ANN has not yet been established. While linear operations can indeed be optically performed very efficiently, the lack of nonlinearity and signal regeneration require high-power, low-latency signal transduction between optics and electronics. Additionally, a large power is needed for lasers and photodetectors, which are often neglected in the calculation of the total energy consumption. Here, instead of mapping traditional digital operations to optics, we co-designed a hybrid optical-digital ANN, that operates on incoherent light, and is thus amenable to operations under ambient light. Keeping the latency and power constant between a purely digital ANN and a hybrid optical-digital ANN, we identified a low-power/latency regime, where an optical encoder provides higher classification accuracy than a purely digital ANN. We estimate our optical encoder enables ∼10 kHz rate operation of a hybrid ANN with a power of only 23 mW. However, in that regime, the overall classification accuracy is lower than what is achievable with higher power and latency. Our results indicate that optics can be advantageous over digital ANN in applications, where the overall performance of the ANN can be relaxed to prioritize lower power and latency. 

Abstract Endoscopes are an important component for the development of minimally invasive surgeries. Their size is one of the most critical aspects, because smaller and less rigid endoscopes enable higher agility, facilitate larger accessibility, and induce less stress on the surrounding tissue. In all existing endoscopes, the size of the optics poses a major limitation in miniaturization of the imaging system. Not only is making small optics difficult, but their performance also degrades with downscaling. Meta-optics have recently emerged as a promising candidate to drastically miniaturize optics while achieving similar functionalities with significantly reduced size. Herein, we report an inverse-designed meta-optic, which combined with a coherent fiber bundle enables a 33% reduction in the rigid tip length over traditional gradient-index (GRIN) lenses. We use the meta-optic fiber endoscope (MOFIE) to demonstrate real-time video capture in full visible color, the spatial resolution of which is primarily limited by the fiber itself. Our work shows the potential of meta-optics for integration and miniaturization of biomedical devices towards minimally invasive surgery. 

Abstract Image sensors with internal computing capability enable in-sensor computing that can significantly reduce the communication latency and power consumption for machine vision in distributed systems and robotics. Two-dimensional semiconductors have many advantages in realizing such intelligent vision sensors because of their tunable electrical and optical properties and amenability for heterogeneous integration. Here, we report a multifunctional infrared image sensor based on an array of black phosphorous programmable phototransistors (bP-PPT). By controlling the stored charges in the gate dielectric layers electrically and optically, the bP-PPT’s electrical conductance and photoresponsivity can be locally or remotely programmed with 5-bit precision to implement an in-sensor convolutional neural network (CNN). The sensor array can receive optical images transmitted over a broad spectral range in the infrared and perform inference computation to process and recognize the images with 92% accuracy. The demonstrated bP image sensor array can be scaled up to build a more complex vision-sensory neural network, which will find many promising applications for distributed and remote multispectral sensing. 

Abstract Meta‐optics have rapidly become a major research field within the optics and photonics community, strongly driven by the seemingly limitless opportunities made possible by controlling optical wavefronts through interaction with arrays of sub‐wavelength scatterers. As more and more modalities are explored, the design strategies to achieve desired functionalities become increasingly demanding, necessitating more advanced design techniques. Herein, the inverse design approach is utilized to create a set of single‐layer meta‐optics that simultaneously focus light and shape the spectra of focused light without using any filters. Thus, both spatial and spectral properties of the meta‐optics are optimized, resulting in spectra that mimic the color matching functions of the CIE 1931 XYZ color space, which links the spectral distribution of a light source to the color perception of a human eye. Experimental demonstrations of these meta‐optics show qualitative agreement with the theoretical predictions and help elucidate the focusing mechanism of these devices. 

Abstract Miniature lenses with a tunable focus are essential components for many modern applications involving compact optical systems. While several tunable lenses have been reported with various tuning mechanisms, they often face challenges with respect to power consumption, tuning speed, fabrication cost, or production scalability. In this work, we have adapted the mechanism of an Alvarez lens – a varifocal composite lens in which lateral shifts of two optical elements with cubic phase surfaces give rise to a change in the optical power – to construct a miniature, microelectromechanical system (MEMS)-actuated metasurface Alvarez lens. Implementation based on an electrostatic MEMS generates fast and controllable actuation with low power consumption. The utilization of metasurfaces – ultrathin and subwavelength-patterned diffractive optics – as optical elements greatly reduces the device volume compared to systems using conventional freeform lenses. The entire MEMS Alvarez metalens is fully compatible with modern semiconductor fabrication technologies, granting it the potential to be mass-produced at a low unit cost. In the reported prototype operating at 1550 nm wavelength, a total uniaxial displacement of 6.3 µm was achieved in the Alvarez metalens with a direct-current (DC) voltage application up to 20 V, which modulated the focal position within a total tuning range of 68 µm, producing more than an order of magnitude change in the focal length and a 1460-diopter change in the optical power. The MEMS Alvarez metalens has a robust design that can potentially generate a much larger tuning range without substantially increasing the device volume or energy consumption, making it desirable for a wide range of imaging and display applications. 

Abstract The purpose of this work is to develop an active self-cleaning system that removes contaminants from a solar module surface by means of an automatic, water-saving, and labor-free process. The output efficiency of a solar module can be degraded over time by dust accumulation on top of the cover glass, which is often referred to as “soiling”. This paper focuses on creating an active self-cleaning surface system using a combination of microsized features and mechanical vibration. The features, which are termed anisotropic ratchet conveyors (ARCs), consist of hydrophilic curved rungs on a hydrophobic background. Two different ARC systems have been designed and fabricated with self-assembled monolayer (SAM) silane and fluoropolymer thin film (Cytop). Fabrication processes were established to fabricate these two systems, including patterning Cytop without degrading the original Cytop hydrophobicity. Water droplet transport characteristics, including anisotropic driving force, droplet resonance mode, cleaning mechanisms, and system power consumption, were studied with the help of a high-speed camera and custom-made test benches. The droplet can be transported on the ARC surface at a speed of 27 mm/s and can clean a variety of dust particles, either water-soluble or insoluble. Optical transmission was measured to show that Cytop can improve transmittance by 2.5~3.5% across the entire visible wavelength range. Real-time demonstrations of droplet transport and surface cleaning were performed, in which the solar modules achieved a 23 percentage-point gain after cleaning.