Halide perovskite memristors for optoelectronic memory and computing applications

Developing an artificial visual sensory system requires optoelectronic materials and devices that can mimic the behavior of biological synapses. Organic/polymeric semiconductors have emerged as promising candidates for optoelectronic synapses due to their tunable optoelectronic properties, mechanic flexibility, and biological compatibility. In this review, we discuss the recent progress in organic optoelectronic synaptic materials and devices, including their design principles, working mechanisms, and applications. We also highlight the challenges and opportunities in this field and provide insights into potential applications of these materials and devices in next‐generation artificial visual systems. By leveraging the advances in organic optoelectronic materials and devices, we can envision its future development in artificial intelligence.

Halide Perovskites – Optoelectronic and Structural Characterization Methods

This paper presents a methodology we have developed and used to implement an artificial binocular vision system capable of emulating the vergence of eye movements. This methodology involves using weightless neural networks (WNNs) as building blocks of artificial vision systems. Using the proposed methodology, we have designed several architectures of WNN-based artificial vision systems, in which images captured by virtual cameras are used for controlling the position of the ‘foveae’ of these cameras (high-resolution region of the images captured). Our best architecture is able to control the foveae vergence movements with average error of only 3.58 image pixels, which is equivalent to an angular error of approximately 0.629°.

Artificial vision systems (AVS) have potential applications in visual prosthetics and artificially intelligent robotics, and they require a preprocessor and a processor to mimic human vision. Halide perovskite (HP) is a promising preprocessor and processor due to its excellent photoresponse, ubiquitous charge migration pathways, and innate hysteresis. However, the material instability associated with HP thin films hinders their utilization in physical AVSs. Herein, we have developed ultrahigh-density arrays of robust HP nanowires (NWs) rooted in a porous alumina membrane (PAM) as the active layer for an AVS. The NW devices exhibit gradual photocurrent change, responding to changes in light pulse duration, intensity, and number, and allow contrast enhancement of visual inputs with a device lifetime of over 5 months. The NW-based processor possesses temporally stable conductance states with retention >105 s and jitter <10%. The physical AVS demonstrated 100% accuracy in recognizing different shapes, establishing HP as a reliable material for neuromorphic vision systems.

In-sensor computing, which is capable of combining sensing, processing, and memory in a single unit, has been proposed to implement a brain-inspired artificial visual system. Among the proposed candidates, two-terminal optoelectronic memristors with optical and electrical hybrid stimuli have been considered to be one suitable hardware for in-sensor computing due to their low power consumption, fast operating speed, and high scalability. Up to now, various optoelectronic memristive devices have been developed to overcome the drawbacks of conventional artificial visual systems with partition of sensory, memory and processing units. In this chapter, the recent progress in two-terminal optoelectronic memristors for in-sensor computing is focused. We introduced the physical mechanism of optoelectronic memristors in detail, including photon–electron and photon–ion coupling processes. The main operation behaviors can be classified into light–electric hybrid-controlled and fully-light controlled types. Moreover, optoelectronic applications, such as optoelectronic logic, image detection and memorizing, and low/high-level sensory processing functions, were also presented. Finally, a brief discussion of the perspectives and challenges for further development of in-sensor computing based on optoelectronic memristors is presented.

Near-infrared (NIR) synaptic devices integrate NIR optical sensitivity and synaptic plasticity, emulating the basic biomimetic function of the human visual system and showing great potential in NIR artificial vision systems. However, the lack of semiconductor materials with appropriate band gaps for NIR photodetection and effective strategies for fabricating devices with synaptic behaviors limit the further development of NIR synaptic devices. Here, a two-terminal NIR synaptic device consisting of the In2Se3/MoS2 heterojunction has been constructed, and it exhibits fundamental synaptic functions. The reduced band gap and potential barrier of In2Se3/MoS2 heterojunctions are essential for NIR synaptic plasticity. In addition, the NIR synaptic properties of In2Se3/MoS2 heterojunctions under strain have been studied systematically. The ΔEPSC of the In2Se3/MoS2 synaptic device can be improved from 38.4% under no strain to 49.0% under a 0.54% strain with a 1060 nm illumination for 1 s at 100 mV. Furthermore, the artificial NIR vision system consisting of a 10 × 10 In2Se3/MoS2 device array has been fabricated, exhibiting image sensing, learning, and storage functions under NIR illumination. This research provides new ideas for the design of flexible NIR synaptic devices based on 2D materials and presents many opportunities in artificial intelligence and NIR vision systems.

Brain‐inspired neuromorphic computing is recognized as a promising technology for implementing human intelligence in hardware. Neuromorphic devices, including artificial synapses and neurons, are regarded as essential components for the construction of neuromorphic hardware systems. Recently, optoelectronic neuromorphic devices are increasingly highlighted due to their potential applications in next‐generation artificial visual systems, attributed to their integrated sensing, computing, and memory capabilities. In this review, recent advancements in optoelectronic synapses and neurons are examined, with an emphasis on their structural characteristics, operational principles, and the replication of neuromorphic functions. For optoelectronic synaptic devices, such as memristor‐ and transistor‐based ones, attention is given to the two primary weight update modes: the light‐electricity synergistic mode and the all‐optical mode. Optoelectronic neurons are discussed in terms of different device types, including threshold switch neurons and semiconductor laser neurons. Last, the challenges that impede the progress of optoelectronic neuromorphic devices are identified, and potential future directions are suggested.

Comparing biological and artificial vision systems: Network measures of functional connectivity

Recently, nanoscience and technology are based on multidisciplinary fields where electronic and optoelectronic devices have drawn huge attention to overcome the latest development issues. Despite coming from traditional materials, the evolution of low dimensional material, especially two-dimensional semiconductors, became a vibrant candidate for dynamic applications. Monolayer graphene and 2D materials gained a plethora of attention because of their immense electronic and optoelectronic properties, like tunable photon absorption and ultrafast charge transport. These materials, having unique and outstanding properties, bloomed as fascinating contenders with huge potential to explore photonic and optoelectronic applications. The progression of 2D materials toward the comprehension of devices has been one of the auspicious inspirations for the emerging progress of new technology. The main advantage of 2D materials is the modulation of their energy bandgap, which can be implemented in light-related applications. This chapter will focus on the 2D materials and their role in the manufacturing of photonic and optoelectronic devices, such as broadband photodetectors, photovoltaic devices, optoelectronic memory, bio-photonic, light-emitting diode (LED), and MXenes-based photodetectors. Also, a great podium will be provided here to investigate the TMDCs and MXenes for their advantages, challenges, and capabilities to play an important role in future technology.

An oxide-based heterojunction optoelectronic synaptic device with wideband and rapid response performance

Background: The development of organic/inorganic metal halide perovskites has seen unprecedent growth since their first recognition for applications in optoelectronic devices. However, their thermodynamic stability and toxicity remains a challenge considering wide-scale deployment in the future. This spurred an interest in search of perovskite-inspired materials which are expected to retain the advantageous material characteristics of halide perovskites, but with high thermodynamic stability and composed of earth-abundant and low toxicity elements. ABX3 chalcogenides (A, B=metals, X=Se, S) have been identified as potential class of materials meeting the aforementioned criteria. Methods: In this work, we focus on studying tin zirconium selenide (SnZrSe3) relevant physical properties with an aim to evaluate its prospects for application in optoelectronics. SnZrSe3 powder and monocrystals were synthesized via solid state reaction in 600 – 750 °C temperature range. Crystalline structure was determined using single crystal and powder X-ray diffraction methods. The bandgap was estimated from diffused reflectance measurements on powder samples and electrical properties of crystals were analysed from temperature dependent I-V measurements. Results: We found that SnZrSe3 crystals have a needle-like structure (space group – Pnma) with following unit cell parameters: a=9.5862(4) Å, b=3.84427(10) Å, c=14.3959(5) Å. The origin of the low symmetry crystalline structure was associated with stereochemical active electron lone pair of Sn cation. Estimated bandgap was around 1.15 eV which was higher than measured previously and predicted theoretically. Additionally, it was found that resistivity and conductivity type depended on the compound chemical composition. Conclusions: Absorption edge in the infrared region and bipolar dopability makes SnZrSe3 an interesting material candidate for application in earth-abundant and non-toxic single/multi-junction solar cells or other infrared based optoelectronic devices.

All‐inorganic lead‐free halide perovskites have been at the forefront of state‐of‐the‐art optoelectronic materials due to their impressive optoelectronic properties and straightforward solution processability. The exceptional optical properties of halide perovskites are intrinsically linked to their structural characteristics, making the investigation of structure–property relationships critical for advancing functional material design and optimizing performance in optoelectronic applications. Among various tuning methods, pressure engineering is a highly powerful in situ technique, which can efficiently modulate the structural and optical properties. The pressure‐induced structural transitions of all‐inorganic lead‐free halide perovskite lead to significant bandgap engineering, piezochromic behaviors, and emission enhancements. However, systematic and comprehensive reviews in this field remain scarce. In this review, recent progress on studies on pressure effect on all‐inorganic lead‐free halide perovskite materials is summarized. The underlying mechanisms of pressure effects on these materials are discussed comprehensively. Finally, the current review challenges and offers insights into the future prospects for leveraging pressure effects to further develop perovskite structures and properties.

Graphdiyne (GDY) is emerging as a promising material for various applications owing to its unique structure and fascinating properties. However, the application of GDY in electronics and optoelectronics are still in its infancy, primarily owing to the huge challenge in the synthesis of large-area and uniform GDY film for scalable applications. Here a modified van der Waals epitaxy strategy is proposed to synthesize wafer-scale GDY film with high uniformity and controllable thickness directly on graphene (Gr) surface, providing an ideal platform to construct large-scale GDY/Gr-based optoelectronic synapse array. Essential synaptic behaviors have been realized, and the linear and symmetric conductance-update characteristics facilitate the implementation of neuromorphic computing for image recognition with high accuracy and strong fault tolerance. Logic functions including “NAND” and “NOR” are integrated into the synapse which can be executed in an optical pathway. Moreover, a visible information sensing-memory-processing system is constructed to execute real-time image acquisition, in situ image memorization and distinction tasks, avoiding the time latency and energy consumption caused by data conversion and transmission in conventional visual systems. These results highlight the potential of GDY in applications of neuromorphic computing and artificial visual systems.

The study of transport and diffusion dynamics of quasi-particles such as excitons, trions, and biexcitons in two-dimensional (2D) semiconductors has opened avenues for their application in high-speed excitonic and optoelectronic devices. However, long-range transport and fast diffusion of these quasi-particles have not been reported for 2D systems such as transition metal dichalcogenides (TMDCs). The reported diffusion coefficients from TMDCs are low, limiting their use in high-speed excitonic devices and other optoelectronic applications. Here, we report the highest exciton diffusion coefficient value in monolayer WS2 achieved via engineering the radiative lifetime and diffusion lengths using static back-gate voltage and substrate engineering. Electrostatic doping is observed to modulate the radiative lifetime and in turn the diffusion coefficient of excitons by ∼three times at room temperature. By combining electrostatic doping and substrate engineering, we push the diffusion coefficient to an extremely high value of 86.5 cm2/s, which has not been reported before in TMDCs and is even higher than the values in some 1D systems. At low temperatures, we further report the control of dynamic and spatial diffusion of excitons, trions, and biexcitons from WS2. The electrostatic control of dynamics and transport of these quasi-particles in monolayers establishes monolayer TMDCs as ideal candidates for high-speed excitonic circuits, optoelectronic, and photonic device applications.

The ultimate goal of Computer Vision has been, for more than half of century, to create an artificial vision system that could imitate the human vision. The artificial vision system should have all the capabilities of the human vision system but must not carry the same flaws. Robotics and Automation are just two examples of research areas that use artificial vision systems as the main sensorial element. In these areas, the use of color-coded objects is very common since it relieves the burden of information processing while being an unobtrusive restraint of the environment. We present a novel computer vision library called UAVision that provides support for different video sensors technologies and all the necessary software for implementing an artificial vision system for the detection of color-coded objects. The experimental results that we present, both for the scenario of robotic soccer games and for traffic sign detection, show that our library can work at more than 50fps with images of 1 megapixel.