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.

Transparent displays lie at the heart of next generation optoelectronics [1,2] in the era of augmented reality (AR), wearable electronics, and internet of things (IoTs). [3][4][5][6][7] Being transparent for light-emitting diodes (LEDs) significantly expands their applications by displaying visual information on objects without affecting their original appearance and functionality. However, there has been a large gap in the electroluminescence (EL) performance between transparent displays and nontransparent counterparts, [8] due in large part to imbalanced injection of charge carriers into the emitter, unoptimized energy band alignment of the top electrode, and vulnerability of organic and/or polymeric light emitting materials during the deposition of transparent conducting oxide electrodes. [9][10][11][12] The previous progresses and unmet requirements for transparent displays are described in Section S2.1, Figure S1, and Table S1 of the Supporting Information. In addition, there has been much need to develop novel device architectures [13][14][15][16] that consider the carrier dynamics for high-performance transparent quantum dot light-emitting diodes (Tr-QLEDs).For high-quality transparent displays, first of all, high transparency is an absolute requirement. [17] The effect of transparency on visibility of background is examined on the university logo and a leaf (Figure 1a). For transparency below 70% (semitransparency), the color and contrast of objects behind the display are significantly deteriorated. In contrast, Tr-QLEDs of 84% transparency present clear background view in both cases. Secondly, high brightness and color purity are particularly important for vividness of "see-through" displays. The maximum brightness of conventional displays (e.g., smart phones and monitors) is around 600 cd m −2 . For see-through displays, however, the displayed information becomes blurred at this brightness (i.e., 600 cd m −2 ) because of photointerference with ambient light (Figure 1b; Figure S2a, Supporting Information). Therefore, significantly higher brightness is required to ensure clear and vivid displays (Figure 1b). In addition, chromatic aberrations can be minimized by employing engineered quantum dots (QD) emitters [18,19] that exhibit better color purity than organic and/or polymer emitters ( Figure S2b, Supporting Information). Lastly, integration of highly deformable 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 accomplishe...

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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.