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In this study, the circular Gaussian spot emitted by a laser light source is shaped into a rectangular flat-top beam to improve the scanning efficiency of a selective laser sintering scanning system. A CO2 laser with a power of 200 W, wavelength of 10.6 μm, and spot diameter of 9 mm is shaped into a flat-top spot with a length and width of 0.5 × 0.1 mm, and the mapping function and flat-top Lorentzian function are calculated. We utilize ZEMAX to optimize the aspherical cylindrical lens of the shaping system and the cylindrical lens of the focusing system. We then calculate the energy uniformity of the flat-top line-shaped beam at distances from 500 to 535 mm and study the zoom displacement of the focusing lens system. The results indicated that the energy uniformity of the flat-top beam was greater than 80% at the distances considered, and the focusing system must precisely control the displacement of the cylindrical lens in the Y-direction to achieve precise zooming.

While metal is the most common conducting constituent element in the fabrication of metamaterials, graphene provides another useful building block, that is, a truly two-dimensional conducting sheet whose conductivity can be controlled by doping. Here we report the experimental realization of a multilayer structure of alternating graphene and Al 2 O 3 layers, a structure similar to the metal-dielectric multilayers commonly used in creating visible wavelength hyperbolic metamaterials. Chemical vapour deposited graphene rather than exfoliated or epitaxial graphene is used, because layer transfer methods are easily applied in fabrication. We employ a method of doping to increase the layer conductivity, and our analysis shows that the doped chemical vapour deposited graphene has good optical properties in the mid-infrared range. We therefore design the metamaterial for mid-infrared operation; our characterization with an infrared ellipsometer demonstrates that the metamaterial experiences an optical topological transition from elliptic to hyperbolic dispersion at a wavelength of 4.5 μm. The use of graphene can provide another useful building block for metamaterials. Here, Chang et al . have explored the experimental realization of a mid-infrared hyperbolic metamaterial, in which the role of the metal in providing a conducting layer is taken over by graphene.

Species that propagate by sexual reproduction actively guard against the fertilization of an egg by multiple sperm (polyspermy). Flowering plants rely on pollen tubes to transport their immotile sperm to fertilize the female gametophytes inside ovules. In Arabidopsis , pollen tubes are guided by cysteine-rich chemoattractants to target the female gametophyte 1 , 2 . The FERONIA receptor kinase has a dual role in ensuring sperm delivery and blocking polyspermy 3 . It has previously been reported that FERONIA generates a female gametophyte environment that is required for sperm release 4 . Here we show that FERONIA controls several functionally linked conditions to prevent the penetration of female gametophytes by multiple pollen tubes in Arabidopsis . We demonstrate that FERONIA is crucial for maintaining de-esterified pectin at the filiform apparatus, a region of the cell wall at the entrance to the female gametophyte. Pollen tube arrival at the ovule triggers the accumulation of nitric oxide at the filiform apparatus in a process that is dependent on FERONIA and mediated by de-esterified pectin. Nitric oxide nitrosates both precursor and mature forms of the chemoattractant LURE1 1 , respectively blocking its secretion and interaction with its receptor, to suppress pollen tube attraction. Our results elucidate a mechanism controlled by FERONIA in which the arrival of the first pollen tube alters ovular conditions to disengage pollen tube attraction and prevent the approach and penetration of the female gametophyte by late-arriving pollen tubes, thus averting polyspermy. FERONIA prevents polyspermy in Arabidopsis by enabling pectin-stimulated nitric oxide accumulation at the filiform apparatus after the first pollen tube arrives, which disengages LURE1 chemoattraction to prevent late-arriving pollen tubes from entering the ovule.

The core of any optical imaging system is a photodetector. Whether it is film or a semiconductor chip in a camera, or indeed the retina in an eye, conventional photodetectors are designed to absorb most of the incident light and record a projected two-dimensional (2D) distribution of light from a scene. The intensity distribution of light from 3D objects, however, can be described by a 4D light field, so optical imaging systems that can acquire higher dimensions of optical information are highly desirable1–3. Here, we report a proof-of-concept light field imaging scheme using transparent graphene photodetector stacks. On a transparent substrate we fabricate a photodetector using graphene as the light-sensing layer, the conducting channel layer, the gate layer and interconnects, enabling sensitive light detection and high transparency at the same time. This technology opens up the possibility of developing sensor arrays that can be stacked along the light path, enabling entirely new configurations of optical imaging devices. We experimentally demonstrate depth ranging using a double stack of transparent detectors and develop a method for computational reconstruction of a 4D light field from a single exposure that can be applied following the successful fabrication of dense 2D transparent sensor arrays.A highly transparent photodetector using graphene as the light-sensing layer, conducting channel layer, gate layer and interconnects enables new approaches for light field photodetection and imaging involving simultaneous detection across multiple focal planes.

Controlling electromagnetic waves and information simultaneously by information metasurfaces is of central importance in modern society. Intelligent metasurfaces are smart platforms to manipulate the wave–information–matter interactions without manual intervention by synergizing engineered ultrathin structures with active devices and algorithms, which evolve from the passive composite materials for tailoring wave–matter interactions that cannot be achieved in nature. Here, we review the recent progress of intelligent metasurfaces in wave–information–matter controls by providing the historical background and underlying physical mechanisms. Then we explore the application of intelligent metasurfaces in developing novel wireless communication architectures, with particular emphasis on metasurface-modulated backscatter wireless communications. We also explore the wave-based computing by using the intelligent metasurfaces, focusing on the emerging research direction in intelligent sensing. Finally, we comment on the challenges and highlight the potential routes for the further developments of the intelligent metasurfaces for controls, communications and computing.

Conventional microwave imagers usually require either time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing, making them largely ineffective for complex in-situ sensing and monitoring. Here, we experimentally report a real-time digital-metasurface imager that can be trained in-situ to generate the radiation patterns required by machine-learning optimized measurement modes. This imager is electronically reprogrammed in real time to access the optimized solution for an entire data set, realizing storage and transfer of full-resolution raw data in dynamically varying scenes. High-accuracy image coding and recognition are demonstrated in situ for various image sets, including hand-written digits and through-wall body gestures, using a single physical hardware imager, reprogrammed in real time. Our electronically controlled metasurface imager opens new venues for intelligent surveillance, fast data acquisition and processing, imaging at various frequencies, and beyond. Conventional imagers require time-consuming data acquisition, or complicated reconstruction algorithms for data post-processing. Here, the authors demonstrate a real-time digital-metasurface imager that can be trained in-situ to show high accuracy image coding and recognition for various image sets.

In flowering plants, fertilization requires complex cell-to-cell communication events between the pollen tube and the female reproductive tissues, which are controlled by extracellular signaling molecules interacting with receptors at the pollen tube surface. We found that two such receptors in Arabidopsis, BUPS1 and BUPS2, and their peptide ligands, RALF4 and RALF19, are pollen tube–expressed and are required to maintain pollen tube integrity. BUPS1 and BUPS2 interact with receptors ANXUR1 and ANXUR2 via their ectodomains, and both sets of receptors bind RALF4 and RALF19. These receptor-ligand interactions are in competition with the female-derived ligand RALF34, which induces pollen tube bursting at nanomolar concentrations. We propose that RALF34 replaces RALF4 and RALF19 at the interface of pollen tube–female gametophyte contact, thereby deregulating BUPS-ANXUR signaling and in turn leading to pollen tube rupture and sperm release.

The fifth-generation (5G) wireless communication has an urgent need for target tracking. Digital programmable metasurface (DPM) may offer an intelligent and efficient solution owing to its powerful and flexible controls of electromagnetic waves and advantages of lower cost, less complexity and smaller size than the traditional antenna array. Here, we report an intelligent metasurface system to perform target tracking and wireless communications, in which computer vision integrated with a convolutional neural network (CNN) is used to automatically detect the locations of moving targets, and the dual-polarized DPM integrated with a pre-trained artificial neural network (ANN) serves to realize the smart beam tracking and wireless communications. Three groups of experiments are conducted for demonstrating the intelligent system: detection and identification of moving targets, detection of radio-frequency signals, and real-time wireless communications. The proposed method sets the stage for an integrated implementation of target identification, radio environment tracking, and wireless communications. This strategy opens up an avenue for intelligent wireless networks and self-adaptive systems. The authors present an intelligent metasurface system that uses a target detection algorithm combined with a depth camera, to automatically detect the position of moving targets and achieve real-time wireless communications. The system can operate for multiple targets in limited ambient light, outdoor and other realistic environments.

The Arabidopsis receptor kinase FERONIA (FER) is a multifunctional regulator for plant growth and reproduction. Here we report that the female gametophyte-expressed glycosylphosphatidylinositol-anchored protein (GPI-AP) LORELEI and the seedling-expressed LRE-like GPI-AP1 (LLG1) bind to the extracellular juxtamembrane region of FER and show that this interaction is pivotal for FER function. LLG1 interacts with FER in the endoplasmic reticulum and on the cell surface, and loss of LLG1 function induces cytoplasmic retention of FER, consistent with transport of FER from the endoplasmic reticulum to the plasma membrane in a complex with LLG1. We further demonstrate that LLG1 is a component of the FER-regulated RHO GTPase signaling complex and that fer and llg1 mutants display indistinguishable growth, developmental and signaling phenotypes, analogous to how lre and fer share similar reproductive defects. Together our results support LLG1/LRE acting as a chaperone and co-receptor for FER and elucidate a mechanism by which GPI-APs enable the signaling capacity of a cell surface receptor. Plants respond to changes in their environment by altering how they grow and when they reproduce. A protein called FERONIA is found in most types of cells and regulates many of the processes that drive these responses, such as cell growth and communication between male and female cells. FERONIA sits in the membrane that surrounds the cell, where it can detect molecules in the cell wall and from outside the cell, and send signals to locations within the cell. However, it is not clear how FERONIA is able to specifically regulate different processes to produce the right response in a particular cell at a particular time. A family of proteins called glycosylphosphatidylinositol-anchored proteins (GPI-APs for short) play important roles in plants, animals, and other eukaryotic organisms. Li et al. studied FERONIA and two closely related GPI-APs called LLG1—which is produced in seedlings, and LORELEI, which is only found in female sex cells. The experiments show that plants missing either LLG1 or FERONIA had similar defects in growth and in how they respond to plant hormones. Plants missing LORELEI had similar defects in their ability to reproduce as the plants missing FERONIA. This suggests that FERONIA works with either LLG1 or LORELEI to regulate similar processes in different situations. Li et al. found that FERONIA binds to LLG1 in a compartment within the cell called the endoplasmic reticulum—where proteins are assembled—before both proteins are moved together to the cell membrane. In the absence of LLG1, FERONIA fails to reach the cell membrane, and a large amount of FERONIA remains trapped in the endoplasmic reticulum. Therefore, LLG1 acts as a ‘chaperone’ that delivers FERONIA to the membrane where it is required to regulate plant growth. Li et al. found that LORELEI also interacts with FERONIA. Both LLG1 and LORELEI bind to the same region of FERONIA, which is on the outer surface of the cell membrane. These findings show that FERONIA is able to perform different roles in cells by teaming up with different members of the GPI-AP family of proteins. The next challenges will be to find out if, and how, LLG1 and LORELEI affect the ability of FERONIA to respond to signals from the cell wall and outside the cell.

Recent years have seen the rapid growth of new approaches to optical imaging, with an emphasis on extracting three-dimensional (3D) information from what is normally a two-dimensional (2D) image capture. Perhaps most importantly, the rise of computational imaging enables both new physical layouts of optical components and new algorithms to be implemented. This paper concerns the convergence of two advances: the development of a transparent focal stack imaging system using graphene photodetector arrays, and the rapid expansion of the capabilities of machine learning including the development of powerful neural networks. This paper demonstrates 3D tracking of point-like objects with multilayer feedforward neural networks and the extension to tracking positions of multi-point objects. Computer simulations further demonstrate how this optical system can track extended objects in 3D, highlighting the promise of combining nanophotonic devices, new optical system designs, and machine learning for new frontiers in 3D imaging. Transparent photodetectors based on graphene stacked vertically along the optical axis have shown promising potential for light field reconstruction. Here, the authors develop transparent photodetector arrays and implement a neural network for real-time 3D optical imaging and object tracking.