After half a billion years of evolution, arthropods have developed sophisticated compound eyes with extraordinary visual capabilities that have inspired the development of artificial compound eyes. However, the limited 2D nature of most traditional fabrication techniques makes it challenging to directly replicate these natural systems. Here, we present a biomimetic apposition compound eye fabricated using a microfluidic-assisted 3D-printing technique. Each microlens is connected to the bottom planar surface of the eye via intracorporal, zero-crosstalk refractive-index-matched waveguides to mimic the rhabdoms of a natural eye. Full-colour wide-angle panoramic views and position tracking of a point source are realized by placing the fabricated eye directly on top of a commercial imaging sensor. As a biomimetic analogue to naturally occurring compound eyes, the eye’s full-colour 3D to 2D mapping capability has the potential to enable a wide variety of applications from improving endoscopic imaging to enhancing machine vision for facilitating human–robot interactions.

Microfluidics drives technological advancement in point-of-care (POC) bioanalytical diagnostics towards portability, fast response and low cost. In most microfluidic bioanalytical applications, flowing antigen/antibody reacts with immobilized antibody/antigen at a constant flux; it is difficult to reach a compromise to simultaneously realize sufficient time for the antigen–antibody interaction and short time for the entire assay. Here, we present a pump-free microfluidic chip, in which flow is self-initialized by capillary pumping and continued by imbibition of a filter paper. Microfluidic units in teardrop shape ensure that flow passes through the reaction areas at a reduced flux to facilitate the association between antigen and antibody and speeds up after the reaction areas. By spotting different antibodies into the reaction area, four types of biomarkers can be measured simultaneously in one microfluidic chip. Moreover, a small-sized instrument was developed for chemiluminescence detection and signal analysis. The system was validated by testing four biomarkers of colorectal cancer using plasma samples from patients. The assay took about 20 minutes. The limit of detection is 0.89 ng mL⁻¹, 1.72 ng mL⁻¹, 3.62 U mL⁻¹ and 1.05 U mL⁻¹ for the assays of carcinoembryonic antigen, alpha-fetoprotein, carbohydrate antigen 125 and carbohydrate antigen 19-9, respectively. This flux-adaptable and self-contained microfluidic platform is expected to be useful in various POC disease-monitoring applications.

In this Letter, we demonstrate a deep-learning-based method capable of synthesizing a photorealistic 3D hologram in real-time directly from the input of a single 2D image. We design a fully automatic pipeline to create large-scale datasets by converting any collection of real-life images into pairs of 2D images and corresponding 3D holograms and train our convolutional neural network (CNN) end-to-end in a supervised way. Our method is extremely computation-efficient and memory-efficient for 3D hologram generation merely from the knowledge of on-hand 2D image content. We experimentally demonstrate speckle-free and photorealistic holographic 3D displays from a variety of scene images, opening up a way of creating real-time 3D holography from everyday pictures. © 2023 Optical Society of America