RESUMO
The bioinspired camera, comprising a single lens and a curved image sensor-a photodiode array on a curved surface-, was born of flexible electronics. Its economical build lends itself well to space-constrained machine vision applications. The curved sensor, much akin to the retina, helps image focusing, but the curvature also creates a problem of image distortion, which can undermine machine vision tasks such as object recognition. Here we report an anti-distortion single-lens camera, where 4096 silicon photodiodes arrayed on a curved surface in a nonuniform pattern assimilated to the distorting optics are the key to anti-distortion engineering. That is, the photo-pixel distribution pattern itself is warped in the same manner as images are warped, which correctively reverses distortion. Acquired images feature no appreciable distortion across a 120° horizontal view, as confirmed by their neural-network recognition accuracies. This distortion correction via photo-pixel array reconfiguration is a form of in-sensor computing.
RESUMO
Mechanically deformable photodetectors (PDs) are key device components for wearable health monitoring systems based on photoplethysmography (PPG). Achieving high detectivity, fast response time, and an ultrathin form factor in the PD is highly needed for next-generation wearable PPG systems. Self-powered operation without a bulky power-supply unit is also beneficial for point-of-care application. Here, we propose ultrathin self-powered PDs using heavy-metal-free Cu-In-Se quantum dots (QDs), which enable high-performance wearable PPG systems. Although the light-absorbing QD layer is extremely thin (â¼40 nm), the developed PD exhibits excellent performance (specific detectivity: 2.10 × 1012 Jones, linear dynamic range: 102 dB, and spectral range: 250-1050 nm at zero bias), which is comparable to that of conventional rigid QD-PDs employing thick Pb-chalcogenide QD layers. This is attributed to material and device strategiesâmaterials that include Cu-In-Se QDs, a MoS2-nanosheet-blended poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) hole transport layer, a ZnO nanoparticle electron transport layer, Ag and ITO electrodes, and an ultrathin form factor (â¼120 nm except the electrodes) that enable excellent mechanical deformability. These allow the successful application of QD-PDs to a wearable system for real-time PPG monitoring, expanding their potential in the field of mobile bioelectronics.
Assuntos
Metais Pesados , Nanopartículas , Pontos Quânticos , Dispositivos Eletrônicos Vestíveis , Fontes de Energia Elétrica , EletrodosRESUMO
With the advance in information technologies involving machine vision applications, the demand for energy- and time-efficient acquisition, transfer, and processing of a large amount of image data has rapidly increased. However, current architectures of the machine vision system have inherent limitations in terms of power consumption and data latency owing to the physical isolation of image sensors and processors. Meanwhile, synaptic optoelectronic devices that exhibit photoresponse similar to the behaviors of the human synapse enable in-sensor preprocessing, which makes the front-end part of the image recognition process more efficient. Herein, we review recent progress in the development of synaptic optoelectronic devices using functional nanomaterials and their unique interfacial characteristics. First, we provide an overview of representative functional nanomaterials and device configurations for the synaptic optoelectronic devices. Then, we discuss the underlying physics of each nanomaterial in the synaptic optoelectronic device and explain related device characteristics that allow for the in-sensor preprocessing. We also discuss advantages achieved by the application of the synaptic optoelectronic devices to image preprocessing, such as contrast enhancement and image filtering. Finally, we conclude this review and present a short prospect.
RESUMO
Synaptic photodetectors exhibit photon-triggered synaptic plasticity, which thus can improve the image recognition rate by enhancing the image contrast. However, still, the visualization and recognition of invisible ultraviolet (UV) patterns are challenging, owing to intense background noise. Here, inspired by all-or-none potentiation of synapse, we develop an integrated device of synaptic phototransistors (SPTrs) and quantum dot light-emitting diodes (QLEDs), facilitating noise reduction and visualization of UV patterns through on-device preprocessing. The SPTrs convert noisy UV inputs into a weighted photocurrent, which is applied to the QLEDs as a voltage input through an external current-voltage-converting circuit. The threshold switching characteristics of the QLEDs result in amplified current and visible illumination by the suprathreshold input voltage or nearly zero current and no visible illumination by the input voltage below the threshold. The preprocessing of image data with the SPTr-QLED can amplify the image contrast, which is helpful for high-accuracy image recognition.
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Visible-light-driven organic transformations are of great interest in synthesizing valuable fine chemicals under mild conditions. The merger of heterogeneous photocatalysts and transition metal catalysts has recently drawn much attention due to its versatility for organic transformations. However, these semi-heterogenous systems suffered several drawbacks, such as transition metal agglomeration on the heterogeneous surface, hindering further applications. Here, we introduce heterogeneous single Ni atoms supported on carbon nitride (NiSAC/CN) for visible-light-driven C-N functionalization with a broad substrate scope. Compared to a semi-heterogeneous system, high activity and stability were observed due to metal-support interactions. Furthermore, through systematic experimental mechanistic studies, we demonstrate that the stabilized single Ni atoms on CN effectively change their redox states, leading to a complete photoredox cycle for C-N coupling.
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Two-dimensional (2D) transition metal dichalcogenide (TMD) layers are unit-cell thick materials with tunable physical properties according to their size, morphology, and chemical composition. Their transition of lab-scale research to industrial-scale applications requires process development for the wafer-scale growth and scalable device fabrication. Herein, we report on a new type of atmospheric pressure chemical vapor deposition (APCVD) process that utilizes colloidal nanoparticles as process-scalable precursors for the wafer-scale production of TMD monolayers. Facile uniform distribution of nanoparticle precursors on the entire substrate leads to the wafer-scale uniform synthesis of TMD monolayers with the controlled size and morphology. Composition-controlled TMD alloy monolayers with tunable bandgaps can be produced by simply mixing dual nanoparticle precursor solutions in the desired ratio. We also demonstrate the fabrication of ultrathin field-effect transistors and flexible electronics with uniformly controlled performance by using TMD monolayers.
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Conventional imaging and recognition systems require an extensive amount of data storage, pre-processing, and chip-to-chip communications as well as aberration-proof light focusing with multiple lenses for recognizing an object from massive optical inputs. This is because separate chips (i.e., flat image sensor array, memory device, and CPU) in conjunction with complicated optics should capture, store, and process massive image information independently. In contrast, human vision employs a highly efficient imaging and recognition process. Here, inspired by the human visual recognition system, we present a novel imaging device for efficient image acquisition and data pre-processing by conferring the neuromorphic data processing function on a curved image sensor array. The curved neuromorphic image sensor array is based on a heterostructure of MoS2 and poly(1,3,5-trimethyl-1,3,5-trivinyl cyclotrisiloxane). The curved neuromorphic image sensor array features photon-triggered synaptic plasticity owing to its quasi-linear time-dependent photocurrent generation and prolonged photocurrent decay, originated from charge trapping in the MoS2-organic vertical stack. The curved neuromorphic image sensor array integrated with a plano-convex lens derives a pre-processed image from a set of noisy optical inputs without redundant data storage, processing, and communications as well as without complex optics. The proposed imaging device can substantially improve efficiency of the image acquisition and recognition process, a step forward to the next generation machine vision.
RESUMO
Displaying information on transparent screens offers new opportunities in next-generation electronics, such as augmented reality devices, smart surgical glasses, and smart windows. Outstanding luminance and transparency are essential for such "see-through" displays to show vivid images over clear background view. Here transparent quantum dot light-emitting diodes (Tr-QLEDs) are reported with high brightness (bottom: ≈43 000 cd m-2 , top: ≈30 000 cd m-2 , total: ≈73 000 cd m-2 at 9 V), excellent transmittance (90% at 550 nm, 84% over visible range), and an ultrathin form factor (≈2.7 µm thickness). These superb characteristics are accomplished by novel electron transport layers (ETLs) and engineered quantum dots (QDs). The ETLs, ZnO nanoparticle assemblies with ultrathin alumina overlayers, dramatically enhance durability of active layers, and balance electron/hole injection into QDs, which prevents nonradiative recombination processes. In addition, the QD structure is further optimized to fully exploit the device architecture. The ultrathin nature of Tr-QLEDs allows their conformal integration on various shaped objects. Finally, the high resolution patterning of red, green, and blue Tr-QLEDs (513 pixels in.-1 ) shows the potential of the full-color transparent display.