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(Zr_0.2Ti_0.8)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.

Reservoir computing (RC) offers efficient temporal information processing with low training cost. All-ferroelectric implementation of RC is appealing because it can fully exploit the merits of ferroelectric memristors (e.g., good controllability); however, this has been undemonstrated due to the challenge of developing ferroelectric memristors with distinctly different switching characteristics specific to the reservoir and readout network. Here, we experimentally demonstrate an all-ferroelectric RC system whose reservoir and readout network are implemented with volatile and nonvolatile ferroelectric diodes (FDs), respectively. The volatile and nonvolatile FDs are derived from the same Pt/BiFeO₃/SrRuO₃ structure via the manipulation of an imprint field (E_imp). It is shown that the volatile FD with E_imp exhibits short-term memory and nonlinearity while the nonvolatile FD with negligible E_imp displays long-term potentiation/depression, fulfilling the functional requirements of the reservoir and readout network, respectively. Hence, the all-ferroelectric RC system is competent for handling various temporal tasks. In particular, it achieves an ultralow normalized root mean square error of 0.017 in the Hénon map time-series prediction. Besides, both the volatile and nonvolatile FDs demonstrate long-term stability in ambient air, high endurance, and low power consumption, promising the all-ferroelectric RC system as a reliable and low-power neuromorphic hardware for temporal information processing.

In this work, planar inorganic perovskite solar cells (PSCs) with the simple structure of glass/ITO/SnO₂/CsPbI₂Br/C have been fabricated.

Poly (3-hexylthiophene) (P3HT) is one of the most attractive hole transport materials (HTMs) for the pursuit of stable, low-cost, and high-efficiency perovskite solar cells (PSCs). However, the poor contact and the severe recombination at P3HT/perovskite interface lead to a low power conversion efficiency (PCE). Thus, we construct a molecular bridge, 2-((7-(4-(bis(4-methoxyphenyl)amino)phenyl)−10-(2-(2-ethoxyethoxy)ethyl)−10H-phenoxazin-3-yl)methylene)malononitrile (MDN), whose malononitrile group can anchor the perovskite surface while the triphenylamine group can form π−π stacking with P3HT, to form a charge transport channel. In addition, MDN is also found effectively passivate the defects and reduce the recombination to a large extent. Finally, a PCE of 22.87% has been achieved with MDN-doped P3HT (M-P3HT) as HTM, much higher than the efficiency of PSCs with pristine P3HT. Furthermore, MDN gives the un-encapsulated device enhanced long-term stability that 92% of its initial efficiency maintain even after two months of aging at 75% relative humidity (RH) follow by one month of aging at 85% RH in the atmosphere, and the PCE does not change after operating at the maximum power point (MPP) under 1 sun illumination (~45^oC in N₂) over 500 hours.

The ferroelectricity of Hf0.5Zr0.5O2 (HZO) thin films has been usually reported to be induced by metallic capping layer. In this work, we successfully obtained ferroelectricity of HZO thin films induced by ultrathin insulating Al2O3 capping layers. The ferroelectric properties of HZO thin films induced by Al2O3 capping layers with different thickness have been investigated. It was found that the Al2O3 (2 nm)/HZO (20 nm) stack shows excel-lent ferroelectric properties. The Au/Al2O3 (2 nm)/HZO (20 nm)/TiN capacitor exhibits a very low leakage current of ~4.2×10.9 A at 4 V and a maximum 2Pr≈l32.3 µC/cm2 at sweeping voltages between ±8 V. In addition, the capacitor also shows ex-cellent endurance properties up to 108 cycles. Our work demon-strated that dielectric films like Al2O3 can be adopted to be used as capping layer to generate excellent ferroelectric properties of HfO2-based thin films, which will contribute to their future ap-plications in ferroelectric memory and negative capacitance tran-sistors.