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.

Achieving high power conversion efficiencies (PCEs) in ferroelectric photovoltaics (PVs) is a longstanding challenge. Although recently ferroelectric thick films, composite films, and bulk crystals have all been demonstrated to exhibit PCEs >1%, these systems still suffer from severe recombination because of the fundamentally low conductivities of ferroelectrics. Further improvement of PCEs may therefore rely on thickness reduction if the reduced recombination could overcompensate for the loss in light absorption. Here, a PCE of up to 2.49% (under 365-nm ultraviolet illumination) was demonstrated in a 12-nm Pb(Zr 0.2 Ti 0.8)O 3 (PZT) ultrathin film. The strategy to realize such a high PCE consists of reducing the film thickness to be comparable with the depletion width, which can simultaneously suppress recombination and lower the series resistance. The basis of our strategy lies in the fact that the PV effect originates from the interfacial Schottky barriers, which is revealed by measuring and modeling the thickness-dependent PV characteristics. In addition, the Schottky barrier parameters (particularly the depletion width) are evaluated by investigating the thickness-dependent ferroelectric, dielectric and conduction properties. Our study therefore provides an effective strategy to obtain high-efficiency ferroelectric PVs and demonstrates the great potential of ferroelectrics for use in ultrathin-film PV devices.

Oxygen stoichiometry plays a crucial role in determining the crystalline structure and physical properties of transition metal oxides (TMOs). Tuning the oxygen content via an electrochemical redox reaction can effectively manipulate the functionalities of TMOs, which is harnessed in many cutting-edge energy and information technologies such as fuel cells, [1] rechargeable batteries, [2] supercapacitors, [3] and memory devices. [4] The redox reaction in certain TMOs can be enabled by a so-called topotactic phase transformation, manifesting itself as the insertion/release of a large amount of oxygen ions without breaking the lattice framework. For example, for an ABO 3 perovskite (PV) phase, upon forming ordered oxygen vacancy channels in its lattice, it transforms into an ABO 2.5 brownmillerite (BM) phase. Along with the structural change, many intriguing physical phenomena emerge owing to the couplings between lattice, charge, and Resistive switching (RS) memory has stayed at the forefront of next-generation nonvolatile memory technologies. Recently, a novel class of transition metal oxides (TMOs), which exhibit reversible topotactic phase transformation between insulating brownmillerite (BM) phase and conducting perovskite (PV) phase, has emerged as promising candidate materials for RS memories. Nevertheless, the microscopic mechanism of RS in these TMOs is still unclear. Furthermore, RS devices with simultaneously high density and superior memory performance are yet to be reported. Here, using SrFeO x as a model system, it is directly observed that PV SrFeO 3 nanofilaments are formed and extend almost through the BM SrFeO 2.5 matrix in the ON state and are ruptured in the OFF state, unambiguously revealing a filamentary RS mechanism. The nanofilaments are ≈10 nm in diameter, enabling to downscale Au/ SrFeO x /SrRuO 3 RS devices to the 100 nm range for the first time. These nanodevices exhibit good performance including ON/OFF ratio as high as ≈10 4 , retention time over 10 5 s, and endurance up to 10 7 cycles. This study significantly advances the understanding of the RS mechanism in TMOs exhibiting topotactic phase transformation, and it also demonstrates the potential of these materials for use in high-density RS memories.

No abstract

Voltage control of magnetism via electric-field-driven ion migration (magneto-ionics) has generated intense interest due to its potential to greatly reduce heat dissipation in a wide range of information technology devices,...