Nowadays the development of machine vision is oriented toward real-time applications such as autonomous driving. This demands a hardware solution with low latency, high energy efficiency, and good reliability. Here, we demonstrate a robust and self-powered in-sensor computing paradigm with a ferroelectric photosensor network (FE-PS-NET). The FE-PS-NET, constituted by ferroelectric photosensors (FE-PSs) with tunable photoresponsivities, is capable of simultaneously capturing and processing images. In each FE-PS, self-powered photovoltaic responses, modulated by remanent polarization of an epitaxial ferroelectric Pb(Zr0.2Ti0.8)O3 layer, show not only multiple nonvolatile levels but also sign reversibility, enabling the representation of a signed weight in a single device and hence reducing the hardware overhead for network construction. With multiple FE-PSs wired together, the FE-PS-NET acts on its own as an artificial neural network. In situ multiply-accumulate operation between an input image and a stored photoresponsivity matrix is demonstrated in the FE-PS-NET. Moreover, the FE-PS-NET is faultlessly competent for real-time image processing functionalities, including binary classification between ‘X’ and ‘T’ patterns with 100% accuracy and edge detection for an arrow sign with an F-Measure of 1 (under 365 nm ultraviolet light). This study highlights the great potential of ferroelectric photovoltaics as the hardware basis of real-time machine vision.

Ferroelectric synapses using polarization switching (a purely electronic switching process) to induce analog conductance change have attracted considerable interest. Here, we propose ferroelectric photovoltaic (FePV) synapses that use polarization-controlled photocurrent as the readout and thus have no limitations on the forms and thicknesses of the constituent ferroelectric and electrode materials. This not only makes FePV synapses easy to fabricate but also reduces the depolarization effect and hence enhances the polarization controllability. As a proof-of-concept implementation, a Pt/Pb(Zr 0.2 Ti 0.8 )O 3 /LaNiO 3 FePV synapse is facilely grown on a silicon substrate, which demonstrates continuous photovoltaic response modulation with good controllability (small nonlinearity and write noise) enabled by gradual polarization switching. Using photovoltaic response as synaptic weight, this device exhibits versatile synaptic functions including long-term potentiation/depression and spike-timing-dependent plasticity. A simulated FePV synapse-based neural network achieves high accuracies (>93%) for image recognition. This study paves a new way toward highly controllable and silicon-compatible synapses for neuromorphic computing.

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In this report, back-channel-etched (BCE) thin-film transistors (TFTs) were achieved by using Si-incorporated SnO2 (silicon tin oxide (STO)) film as active layer. It was found that the STO film was acid-resistant and in amorphous state. The BCE-TFT with STO active layer exhibited a mobility of 5.91 cm2/V s, a threshold voltage of 0.4 V, an on/off ratio of 107, and a steep subthreshold swing of 0.68 V/decade. Moreover, the device had a good stability under the positive/negative gate-bias stress.

A viable solution toward "green" optoelectronics is rooted in our ability to fabricate optoelectronics on transparent nanofibrillated cellulose (NFC) film substrates. However, the flammability of transparent NFC film poses a severe fire hazard in optoelectronic devices. Despite many efforts toward enhancing the fire-retardant features of transparent NFC film, making NFC film fire-retardant while maintaining its high transparency (≥90%) remains an ambitious objective. Herein, we combine NFC with NFC-dispersed monolayer clay nanoplatelets as a fire retardant to prepare highly transparent NFC-monolayer clay nanoplatelet hybrid films with a superb self-extinguishing behavior. Homogeneous and stable monolayer clay nanoplatelet dispersion was initially obtained by using NFC as a green dispersing agent with the assistance of ultrasonication and then used to blend with NFC to prepare highly transparent and self-extinguishing hybrid films by a water evaporation-induced self-assembly process. As the content of monolayer clay nanoplatelets increased from 5 wt % to 50 wt %, the obtained hybrid films presented enhanced self-extinguishing behavior (limiting oxygen index sharply increased from 21% to 96.5%) while retaining a ∼90% transparency at 600 nm. More significantly, the underlying mechanisms for the high transparency and excellent self-extinguishing behavior of these hybrid films with a clay nanoplatelet content of over 30 wt % were unveiled by a series of characterizations such as SEM, XRD, TGA, and limiting oxygen index tester. This work offers an alternative environmentally friendly, self-extinguishing, and highly transparent substrate to next-generation optoelectronics, and is aimed at providing a viable solution to environmental concerns that are caused by ever-increasing electronic waste.