Photoinduced Multi-Bit Nonvolatile Memory Based on a van der Waals Heterostructure with a 2D-Perovskite Floating Gate

In-sensor compressing via programmable optoelectronic sensors based on van der Waals heterostructures for intelligent machine vision

Efficiently capturing multidimensional signals containing spectral and temporal information is crucial for intelligent machine vision. Although in-sensor computing shows promise for efficient visual processing by reducing data transfer, its capability to compress temporal/spectral data is rarely reported. Here we demonstrate a programmable two-dimensional (2D) heterostructure-based optoelectronic sensor integrating sensing, memory, and computation for in-sensor data compression. Our 2D sensor captured and memorized/encoded optical signals, leading to in-device snapshot compression of dynamic videos and three-dimensional spectral data with a compression ratio of 8:1. The reconstruction quality, indicated by a peak signal-to-noise ratio value of 15.81 dB, is comparable to the 16.21 dB achieved through software. Meanwhile, the compressed action videos (in the form of 2D images) preserve all semantic information and can be accurately classified using in-sensor convolution without decompression, achieving accuracy on par with uncompressed videos (93.18% vs 83.43%). Our 2D optoelectronic sensors promote the development of efficient intelligent vision systems at the edge.

Next-Generation Image Sensors Based on Low-Dimensional Semiconductor Materials

With the rapid advancement of technology of big data and artificial intelligence (AI), the exponential increase in visual information leads to heightened demands for the quality and analysis of imaging results, rendering traditional silicon-based image sensors inadequate. This review serves as a comprehensive overview of next-generation image sensors based on low-dimensional semiconductor materials encompassing 0D, 1D, 2D materials, and their hybrids. It offers an in-depth introduction to the distinctive properties exhibited by these materials and delves into the device structures tailored specifically for image sensor applications. The classification of novel image sensors based on low-dimensional materials, in particular for transition metal dichalcogenides (TMDs), covering the preparation methods and corresponding imaging characteristics, is explored. Furthermore, this review highlights the diverse applications of low-dimensional materials in next-generation image sensors, encompassing advanced imaging sensors, biomimetic vision sensors, and non-von Neumann imaging systems. Lastly, the challenges and opportunities encountered in the development of next-generation image sensors utilizing low-dimensional semiconductor materials, paving the way for further advancements in this rapidly evolving field, are proposed.

Solution-processable and photo-programmable logic gate realized by organic non-volatile floating-gate photomemory

Programmable inverters using non-volatile floating-gate photomemories as basic building blocks instead of field-effect transistors enable the manipulation of threshold voltage by photons, providing an additional degree of freedom for applications in integrated circuits. However, the development of organic photo-controllable inverters is challenging due to issues such as solubility constraints for film stacking and the immaturity of photo-recordable devices. Notably, the development of organic non-volatile floating-gate photomemories (ONVFGPs) with n-type charge-transporting layers still lags behind that of the p-type layers due to the limited availability of suitable solution-processable charge-trapping materials and charge-transporting material pairs. Herein, photo-crosslinkable polystyrene-b-poly(methacrylic acid) (PS-b-PMAA)/5,10,15,20-tetraphenyl-21H,23H-porphine zinc (ZnTPP), which follows anti-Kasha's rule, is adopted as the charge-trapping layer for ONVFGPs. Both the second and first excited states of ZnTPP participate in photo-induced charge transfer, achieving the state-of-the-art photo-programming time of 0.1 second for ONVFGPs. The transfer curve of the derived photo-programmable inverter can be fine-tuned across a broad spectrum spanning from 405 nm to 830 nm, leading to at least six output states for the same input signal. This research confirms the possibility of integrated organic optoelectronics, opening avenues for solution-processable system-on-chip, neuromorphic computing and organic photonic integrated circuits.

2D (NH4)BiI3 enables non-volatile optoelectronic memories for machine learning

Machine learning is the core of artificial intelligence. Using optical signals for training and converting them into electrical signals for inference, combines the strengths of both, and thus can greatly improve machine learning efficiency. Optoelectronic memories are the hardware foundation for this strategy. However, the existing optoelectronic memories cannot modulate a large number of non-volatile resistive states using ultra-short and ultra-dim light pulses, leading to low training accuracy, slow computing speed and high energy consumption. Here, we synthesized a van der Waals layered photoconductive material, (NH4)BiI3, with excellent photoconductivity and strong dielectric screening effect. We further employed it as the photosensitive control gate in a floating-gate transistor, replacing the commonly used metal control gate, to construct an optical floating gate transistor which achieves adjustable synaptic weights under ultra-dim light without gate voltage assistance. Moreover, it shows ultra-low training energy consumption to generate a non-volatile state and the largest resistive state numbers among the known non-volatile optoelectronic memories. These exceptional performances enable the construction of one-transistor-one-memory device arrays to achieve ~99% accuracy in Artificial Neural Networks. Moreover, the device arrays can match the performance of GPU in YOLOv8 while greatly reducing energy consumption.

Two-Dimensional Materials for Brain-Inspired Computing Hardware

Recent breakthroughs in brain-inspired computing promise to address a wide range of problems from security to healthcare. However, the current strategy of implementing artificial intelligence algorithms using conventional silicon hardware is leading to unsustainable energy consumption. Neuromorphic hardware based on electronic devices mimicking biological systems is emerging as a low-energy alternative, although further progress requires materials that can mimic biological function while maintaining scalability and speed. As a result of their diverse unique properties, atomically thin two-dimensional (2D) materials are promising building blocks for next-generation electronics including nonvolatile memory, in-memory and neuromorphic computing, and flexible edge-computing systems. Furthermore, 2D materials achieve biorealistic synaptic and neuronal responses that extend beyond conventional logic and memory systems. Here, we provide a comprehensive review of the growth, fabrication, and integration of 2D materials and van der Waals heterojunctions for neuromorphic electronic and optoelectronic devices, circuits, and systems. For each case, the relationship between physical properties and device responses is emphasized followed by a critical comparison of technologies for different applications. We conclude with a forward-looking perspective on the key remaining challenges and opportunities for neuromorphic applications that leverage the fundamental properties of 2D materials and heterojunctions.

Ferroelectric Perovskite/MoS2 Channel Heterojunctions for Wide-Window Nonvolatile Memory and Neuromorphic Computing

Ferroelectric materials commonly serve as gate insulators in typical field-effect transistors, where their polarization reversal enables effective modulation of the conductivity state of the channel material, thereby realizing non-volatile memory. Currently, novel 2D ferroelectrics unlock new prospects in next-generation electronics and neuromorphic computation. However, the advancement of these materials is impeded by limited selectivity and narrow memory windows. Here, new concepts of 2D ferroelectric perovskite/MoS2 channel heterostructures field-effect transistors are presented, in which 2D ferroelectric perovskite features customizable band structure, few-layered ferroelectricity, and submillimeter-size monolayer wafers. Further studies reveal that these devices exhibit unique charge polarity modulation (from n- to p-type channel) and remarkable nonvolatile memory behavior, especially record-wide hysteresis windows up to 177 V, which enables efficient imitation of biological synapses and achieves high recognition accuracy for electrocardiogram patterns. This result provides a device paradigm for future nonvolatile memory and artificial synaptic applications.

Charge-Selective 2D Heterointerface-Driven Multifunctional Floating Gate Memory for In Situ Sensing-Memory-Computing

Flash memory, dominating data storage due to its substantial storage density and cost efficiency, faces limitations such as slow response, high operating voltages, absence of optoelectronic response, etc., hindering the development of sensing-memory-computing capability. Here, we present an ultrathin platinum disulfide (PtS2)/hexagonal boron nitride (hBN)/multilayer graphene (MLG) van der Waals heterojunction with atomically sharp interfaces, achieving selective charge tunneling behavior and demonstrating ultrafast operations, a high on/off ratio (108), extremely low operating voltage, robust endurance (105 cycles), and retention exceeding 10 years. Additionally, we achieve highly linear synaptic potentiation and depression, and observe the reversibly gate-tunable transitions between positive and negative photoconductivity. Furthermore, we employed the VGG11 neural network for in situ trained in-sensor-memory-computing to classify the CIFAR-10 data set, pushing accuracy levels comparable to pure digital systems. This work could pave the way for seamlessly integrated sensing, memory, and computing capabilities for diverse edge computing.

Recent advances in artificial neuromorphic applications based on perovskite composites

High-performance perovskite materials with excellent physical, electronic, and optical properties play a significant role in artificial neuromorphic devices. However, the development of perovskites in microelectronics is inevitably hindered by their intrinsic non-ideal properties, such as high defect density, environmental sensitivity, and toxicity. By leveraging materials engineering, integrating various materials with perovskites to leverage their mutual strengths presents great potential to enhance ion migration, energy level alignment, photoresponsivity, and surface passivation, thereby advancing optoelectronic and neuromorphic device development. This review initially provides an overview of perovskite materials across different dimensions, highlighting their physical properties and detailing their applications and metrics in two- and three-terminal devices. Subsequently, we comprehensively summarize the application of perovskites in combination with other materials, including organics, nanomaterials, oxides, ferroelectrics, and crystalline porous materials (CPMs), to develop advanced devices such as memristors, transistors, photodetectors, sensors, light-emitting diodes (LEDs), and artificial neuromorphic systems. Lastly, we outline the challenges and future research directions in synthesizing perovskite composites for neuromorphic devices. Through the review and analysis, we aim to broaden the utilization of perovskites and their composites in neuromorphic research, offering new insights and approaches for grasping the intricate physical working mechanisms and functionalities of perovskites.

Negative Photoconductivity Transistors for Visuomorphic Computing

Visuomorphic computing aims to simulate and potentially surpass the human retina by mimicking biological visual perception with an artificial retina. Despite significant progress, challenges persist in perceiving complex interactive environments. Negative photoconductivity transistors (NPTs) mimic synaptic behavior by achieving adjustable positive photoconductivity (PPC) and negative photoconductivity (NPC), simulating "excitation" and "inhibition" akin to sensory cell signals. In complex interactive environments, NPTs are desired for visuomorphic computing that can achieve a better sense of information, lower power consumption, and reduce hardware complexity. In this review, it is started by introducing the development process of NPTs, while placing a strong emphasis on the device structures, working mechanisms, and key performance parameters. The common material systems employed in NPTs based on their functions are then summarized. Moreover, it is proceeded to summarize the noteworthy applications of NPTs in optoelectronic devices, including advanced multibit nonvolatile memory, optoelectronic logic gates, optical encryption, and visual perception. Finally, the challenges and prospects that lie ahead in the ongoing development of NPTs are addressed, offering valuable insights into their applications in optoelectronics and a comprehensive understanding of their significance.

Dual-Adaptive Heterojunction Synaptic Transistors for Efficient Machine Vision in Harsh Lighting Conditions

Photoadaptive synaptic devices enable in-sensor processing of complex illumination scenes, while second-order adaptive synaptic plasticity improves learning efficiency by modifying the learning rate in a given environment. The integration of above adaptations in one phototransistor device will provide opportunities for developing high-efficient machine vision system. Here, a dually adaptable organic heterojunction transistor as a working unit in the system, which facilitates precise contrast enhancement and improves convergence rate under harsh lighting conditions, is reported. The photoadaptive threshold sliding originates from the bidirectional photoconductivity caused by the light intensity-dependent photogating effect. Metaplasticity is successfully implemented owing to the combination of ambipolar behavior and charge trapping effect. By utilizing the transistor array in a machine vision system, the details and edges can be highlighted in the 0.4% low-contrast images, and a high recognition accuracy of 93.8% with a significantly promoted convergence rate by about 5 times are also achieved. These results open a strategy to fully implement metaplasticity in optoelectronic devices and suggest their vision processing applications in complex lighting scenes.

The Nonvolatile Memory and Neuromorphic Simulation of ReS2/h-BN/Graphene Floating Gate Devices Under Photoelectrical Hybrid Modulations

The floating gate devices, as a kind of nonvolatile memory, obtain great application potential in logic-in-memory chips. The 2D materials have been greatly studied due to atomically flat surfaces, higher carrier mobility, and excellent photoelectrical response. The 2D ReS2 flake is an excellent candidate for channel materials due to thickness-independent direct bandgap and outstanding optoelectronic response. In this paper, the floating gate devices are prepared with the ReS2/h-BN/Gr heterojunction. It obtains superior nonvolatile electrical memory characteristics, including a higher memory window ratio (81.82%), tiny writing/erasing voltage (±8 V/2 ms), long retention (>1000 s), and stable endurance (>1000 times) as well as multiple memory states. Meanwhile, electrical writing and optical erasing are achieved by applying electrical and optical pulses, and multilevel storage can easily be achieved by regulating light pulse parameters. Finally, due to the ideal long-time potentiation/depression synaptic weights regulated by light pulses and electrical pulses, the convolutional neural network (CNN) constructed by ReS2/h-BN/Gr floating gate devices can achieve image recognition with an accuracy of up to 98.15% for MNIST dataset and 91.24% for Fashion-MNIST dataset. The research work adds a powerful option for 2D materials floating gate devices to apply to logic-in-memory chips and neuromorphic computing.

Ultrafast Non-Volatile Floating-Gate Memory Based on All-2D Materials

The explosive growth of massive-data storage and the demand for ultrafast data processing require innovative memory devices with exceptional performance. 2D materials and their van der Waal heterostructures with atomically sharp interfaces hold great promise for innovations in memory devices. Here, this work presents non-volatile, floating-gate memory devices with all functional layers made of 2D materials, achieving ultrafast programming/erasing speeds (20 ns), high extinction ratios (up to 108), and multi-bit storage capability. These devices also exhibit long-term data retention exceeding 10 years, facilitated by a high gate-coupling ratio (GCR) and atomically sharp interfaces between functional layers. Additionally, this work demonstrates the realization of an "OR" logic gate on a single-device unit by synergistic electrical and optical operations. The present results provide a solid foundation for next-generation ultrahigh-speed, ultralong lifespan, non-volatile memory devices, with a potential for scale-up manufacturing and flexible electronics applications.

Gap State-Modulated Van Der Waals Short-Term Memory with Broad Band Negative Photoconductance

Floating gate memory (FGM), composed of van der Waals (vdW) junctions with an atomically thin floating layer for charge storage, is widely employed to develop logic-in memories and in-sensor computing devices. Most research efforts of FGM are spent on achieving long-term charge storage and fast reading/writing for flash and random-access memory. However, dynamic modulation of memory time via a tunneling barrier and vdW interfaces, which is critical for synaptic computing and machine vision, is still lacking. Here, a van der Waals short-term memory with tunable memory windows and retention times from milliseconds to thousands of seconds is reported, which is approximately exponentially proportional to the thickness h-BN (hexagonal boron nitride) barrier. The specific h-BN barrier with fruitful gap states provides charge release channels for trapped charges, making the vdW device switchable between positive photoconductance and negative photoconductance with a broadband light from IR to UV range. The dynamic short-term memory with tunable photo response highlights the design strategy of novel vdW memory vis interface engineering for further intelligent information storage and optoelectronic detection.

Non-volatile rippled-assisted optoelectronic array for all-day motion detection and recognition

In-sensor processing has the potential to reduce the energy consumption and hardware complexity of motion detection and recognition. However, the state-of-the-art all-in-one array integration technologies with simultaneous broadband spectrum image capture (sensory), image memory (storage) and image processing (computation) functions are still insufficient. Here, macroscale (2 × 2 mm2) integration of a rippled-assisted optoelectronic array (18 × 18 pixels) for all-day motion detection and recognition. The rippled-assisted optoelectronic array exhibits remarkable uniformity in the memory window, optically stimulated non-volatile positive and negative photoconductance. Importantly, the array achieves an extensive optical storage dynamic range exceeding 106, and exceptionally high room-temperature mobility up to 406.7 cm2 V-1 s-1, four times higher than the International Roadmap for Device and Systems 2028 target. Additionally, the spectral range of each rippled-assisted optoelectronic processor covers visible to near-infrared (405 nm-940 nm), achieving function of motion detection and recognition.

Optical readout of charge carriers stored in a 2D memory cell of monolayer WSe2

Owing to their superior charge retaining and transport characteristics, 2D transition metal dichalcogenides are investigated for practical applications in various memory-cell structures. Herein, we fabricated a quasi-one-terminal 2D memory cell by partially depositing a WSe2 monolayer on an Au electrode, which can be manipulated to achieve efficient charge injection upon the application or removal of external bias. Furthermore, the amount of charge carriers stored in the memory cell could be optically probed because of its close correlation with the fluorescence efficiency of WSe2, allowing us to achieve an electron retention time of ∼300 s at the cryogenic temperature of 4 K. Accordingly, the simplified device structure and the non-contact optical readout of the stored charge carriers present new research opportunities for 2D memory cells in terms of both fundamental mechanism studies and practical development for integrated nanophotonic devices.

A 2D Heterostructure-Based Multifunctional Floating Gate Memory Device for Multimodal Reservoir Computing

The demand for economical and efficient data processing has led to a surge of interest in neuromorphic computing based on emerging two-dimensional (2D) materials in recent years. As a rising van der Waals (vdW) p-type Weyl semiconductor with many intriguing properties, tellurium (Te) has been widely used in advanced electronics/optoelectronics. However, its application in floating gate (FG) memory devices for information processing has never been explored. Herein, an electronic/optoelectronic FG memory device enabled by Te-based 2D vdW heterostructure for multimodal reservoir computing (RC) is reported. When subjected to intense electrical/optical stimuli, the device exhibits impressive nonvolatile electronic memory behaviors including ≈108 extinction ratio, ≈100 ns switching speed, >4000 cycles, >4000-s retention stability, and nonvolatile multibit optoelectronic programmable characteristics. When the input stimuli weaken, the nonvolatile memory degrades into volatile memory. Leveraging these rich nonlinear dynamics, a multimodal RC system with high recognition accuracy of 90.77% for event-type multimodal handwritten digit-recognition is demonstrated.

Photoinduced Nonvolatile Memory Transistor Based on Lead-Free Perovskite Incorporating Fused π-Conjugated Organic Ligands

Perovskites field-effect transistors (PeFETs) have been intensively investigated for their application in detector and synapse. However, synapse based on PeFETs is still very difficult to integrate excellent charge carrier transporting ability, photosensitivity, and nonvolatile memory effects into one device, which is very important for developing bionic electronic devices and edge computing. Here, two-dimensional (2D) perovskites are synthesized by incorporating fused π-conjugated pyrene-O-ethyl-ammonium (POE) ligands and a systematic study is conducted to obtain enhanced performance and reliable PeFETs. The optimized (POE)2 SnI4 transistors display the hole mobility over 0.3 cm2  V-1  s-1 , high repeatability, and operational stability. Meanwhile, the derived photo memory devices show remarkable photoresponse, with a switching ratio higher than 105 , high visible light responsivity (>4 × 104  A W-1 ), and stable storage-erase cycles, as well as competitive retention performance (104  s). The photoinduced memory behavior can be benefiting from the insulating nature of quantum-well in 2D perovskite under dark and its excellent light sensitivity. The excellent photo memory behaviors have been maintained after 40 days in a N2 atmosphere. Finally, a 2D perovskite-only transistors with a multi-level memory behavior (16 distinct states) is described by controlling incident light pulse. This work provides broader attention toward 2D perovskite and optoelectronic application.

Harnessing 2D Ruddlesden-Popper Perovskite with Polar Organic Cation for Ultrasensitive Multibit Nonvolatile Transistor-Type Photomemristors

Photomemristors have been regarded as one of the most promising candidates for next-generation hardware-based neuromorphic computing due to their potentials of fast data transmission and low power consumption. However, intriguingly, so far, photomemristors seldom display truly nonvolatile memory characteristics with high light sensitivity. Herein, we demonstrate ultrasensitive photomemristors utilizing two-dimensional (2D) Ruddlesden-Popper (RP) perovskites with a highly polar donor-acceptor-type push-pull organic cation, 4-(5-(2-aminoethyl)thiophen-2-yl)benzonitrile+ (EATPCN+), as charge-trapping layers. High linearity and almost zero-decay retention are observed in (EATPCN)2PbI4 devices, which are very distinct from that of the traditional 2D RP perovskite devices consisting of nonpolar organic cations, such as phenethylamine+ (PEA+) and octylamine+ (OA+), and traditional 3D perovskite devices consisting of methylamine+ (MA+). The 2-fold advantages, including desirable spatial crystal arrangement and engineered energetic band alignment, clarify the mechanism of superior performance in (EATPCN)2PbI4 devices. The optimized (EATPCN)2PbI4 photomemristor also shows a memory window of 87.9 V and an on/off ratio of 106 with a retention time of at least 2.4 × 105 s and remains unchanged after >105 writing-reading-erasing-reading endurance cycles. Very low energy consumptions of 1.12 and 6 fJ for both light stimulation and the reading process of each status update are also demonstrated. The extremely low power consumption and high photoresponsivity were simultaneously achieved. The high photosensitivity surpasses that of a state-of-the-art commercial pulse energy meter by several orders of magnitude. With their outstanding linearity and retention, rabbit images have been rebuilt by (EATPCN)2PbI4 photomemristors, which truthfully render the image without fading over time. Finally, by utilizing the powerful ∼8 bits of nonvolatile potentiation and depression levels of (EATPCN)2PbI4 photomemristors, the accuracies of the recognition tasks of CIFAR-10 image classification and MNIST handwritten digit classification have reached 89% and 94.8%, respectively. This study represents the first report of utilizing a functional donor-acceptor type of organic cation in 2D RP perovskites for high-performance photomemristors with characteristics that are not found in current halide perovskites.

Carrier transfer in quasi-2D perovskite/MoS2 monolayer heterostructure

Two-dimensional layered semiconductors have attracted intense interest in recent years. The van der Waals coupling between the layers tolerates stacking various materials and establishing heterostructures with new characteristics for a wide range of optoelectronic applications. The interlayer exciton dynamics at the interface within the heterostructure are vitally important for the performance of the photodetector and photovoltaic device. Here, a heterostructure comprising two-dimensional organic-inorganic Ruddlesden-Popper perovskites and transition metal dichalcogenide monolayer was fabricated and its ultrafast charge separation processes were systematically studied by using femtosecond time-resolved transient absorption spectroscopy. Significant hole and electron transfer processes in the ps and fs magnitude at the interface of the heterostructure were observed by tuning pump wavelengths of the pump-probe geometries. The results emphasize the realization of the exciton devices based on semiconductor heterostructures of two-dimensional perovskite and transition metal dichalcogenide.

A review on advanced band-structure engineering with dynamic control for nonvolatile memory based 2D transistors

With advancements in information technology, an enormous amount of data is being generated that must be quickly accessible. However, conventional Si memory cells are approaching their physical limits and will be unable to meet the requirements of intense applications in the future. Notably, 2D atomically thin materials have demonstrated multiple novel physical and chemical properties that can be used to investigate next-generation electronic devices and breakthrough physical limits to continue Moore's law. Band structure is an important semiconductor parameter that determines their electrical and optical properties. In particular, 2D materials have highly tunable bandgaps and Fermi levels that can be achieved through band structure engineering methods such as heterostructure, substrate engineering, chemical doping, intercalation, and electrostatic doping. In particular, dynamic control of band structure engineering can be used in recent advancements in 2D devices to realize nonvolatile storage performance. This study examines recent advancements in 2D memory devices that utilize band structure engineering. The operational mechanisms and memory characteristics are described for each band structure engineering method. Band structure engineering provides a platform for developing new structures and realizing superior performance with respect to nonvolatile memory.

Tuning and exploiting interlayer coupling in two-dimensional van der Waals heterostructures

Two-dimensional (2D) layered materials can stack into new material systems, with van der Waals (vdW) interaction between the adjacent constituent layers. This stacking process of 2D atomic layers creates a new degree of freedom-interlayer interface between two adjacent layers-that can be independently studied and tuned from the intralayer degree of freedom. In such heterostructures (HSs), the physical properties are largely determined by the vdW interaction between the individual layers,i.e.interlayer coupling, which can be effectively tuned by a number of means. In this review, we summarize and discuss a number of such approaches, including stacking order, electric field, intercalation, and pressure, with both their experimental demonstrations and theoretical predictions. A comprehensive overview of the modulation on structural, optical, electrical, and magnetic properties by these four approaches are also presented. We conclude this review by discussing several prospective research directions in 2D HSs field, including fundamental physics study, property tuning techniques, and future applications.

Integration of image preprocessing and recognition functions in an optoelectronic coupling organic ferroelectric retinomorphic neuristor

The human visual system (HVS) has the advantages of a low power consumption and high efficiency because of the synchronous perception and early preprocessing of external image information in the retina, as well as parallel in-memory computing within the visual cortex. Realizing the biofunction simulation of the retina and visual cortex in a single device structure provides opportunities for performance improvements and machine vision system (MVS) integration. Here, we fabricate organic ferroelectric retinomorphic neuristors that integrate the retina-like preprocessing function and recognition of the visual cortex in a single device architecture. Benefiting from the electrical/optical coupling modulation of ferroelectric polarization, our devices show a bidirectional photoresponse that acts as the basis for mimicking retinal preconditioning and multi-level memory capabilities for recognition. The MVS based on the proposed retinomorphic neuristors achieves a high recognition accuracy of ∼90%, which is 20% higher than that of the incomplete system without the preprocessing function. In addition, we successfully demonstrate image encryption and optical programming logic gate functions. Our work suggests that the proposed retinomorphic neuristors offer great potential for MVS monolithic integration and functional expansion.

Uncovering the Role of Crystal Phase in Determining Nonvolatile Flash Memory Device Performance Fabricated from MoTe2-Based 2D van der Waals Heterostructures

Although the crystal phase of two-dimensional (2D) transition metal dichalcogenides (TMDs) has been proven to play an essential role in fabricating high-performance electronic devices in the past decade, its effect on the performance of 2D material-based flash memory devices still remains unclear. Here, we report the exploration of the effect of MoTe₂ in different phases as the charge-trapping layer on the performance of 2D van der Waals (vdW) heterostructure-based flash memory devices, where a metallic 1T'-MoTe₂ or semiconducting 2H-MoTe₂ nanoflake is used as the floating gate. By conducting comprehensive measurements on the two kinds of vdW heterostructure-based devices, the memory device based on MoS₂/h-BN/1T'-MoTe₂ presents much better performance, including a larger memory window, faster switching speed (100 ns), and higher extinction ratio (10⁷), than that of the device based on the MoS₂/h-BN/2H-MoTe₂ heterostructure. Moreover, the device based on the MoS₂/h-BN/1T'-MoTe₂ heterostructure also shows a long cycle (>1200 cycles) and retention (>3000 s) stability. Our study clearly demonstrates that the crystal phase of 2D TMDs has a significant impact on the performance of nonvolatile flash memory devices based on 2D vdW heterostructures, which paves the way for the fabrication of future high-performance memory devices based on 2D materials.

Strong interlayer coupling in p-Te/n-CdSe van der Waals heterojunction for self-powered photodetectors with fast speed and high responsivity

Self-driven photodetectors, which can detect optical signals without external voltage bias, are highly attractive in the field of low-power wearable electronics and internet of things. However, currently reported self-driven photodetectors based on van der Waals heterojunctions (vdWHs) are generally limited by low responsivity due to poor light absorption and insufficient photogain. Here, we report p-Te/n-CdSe vdWHs utilizing non-layered CdSe nanobelts as efficient light absorption layer and high mobility Te as ultrafast hole transporting layer. Benefiting from strong interlayer coupling, the Te/CdSe vdWHs exhibit stable and excellent self-powered characteristics, including ultrahigh responsivity of 0.94 A W^-1, remarkable detectivity of 8.36 × 10¹² Jones at optical power density of 1.18 mW cm^-2 under illumination of 405 nm laser, fast response speed of 24 µs, large light on/off ratio exceeding 10⁵, as well as broadband photoresponse (405-1064 nm), which surpass most of the reported vdWHs photodetectors. In addition, the devices display superior photovoltaic characteristics under 532 nm illumination, such as large V_oc of 0.55 V, and ultrahigh I_sc of 2.73 µA. These results demonstrate the construction of 2D/non-layered semiconductor vdWHs with strong interlayer coupling is a promising strategy for high-performance and low-power consumption devices.

Fast, Multi-Bit, and Vis-Infrared Broadband Nonvolatile Optoelectronic Memory with MoS2 /2D-Perovskite Van der Waals Heterojunction

Nonvolatile optoelectronic memory (NVOM) integrating the functions of optical sensing and long-term memory can efficiently process and store a large amount of visual scene information, which has become the core requirement of multiple intelligence scenarios. However, realizing NVOM with vis-infrared broadband response is still challenging. Herein, the room temperature vis-infrared broadband NVOM based on few-layer MoS₂ /2D Ruddlesden-Popper perovskite (2D-RPP) van der Waals heterojunction is realized. It is found that the 2D-RPP converts the initial n-type MoS₂ into p-type and facilitates hole transfer between them. Furthermore, the 2D-RPP rich in interband states serves as an effective electron trapping layer as well as broadband photoresponsive layer. As a result, the dielectric-free MoS₂ /2D-RPP heterojunction enables the charge to transfer quickly under external field, which enables a large memory window (104 V), fast write speed of 20 µs, and optical programmable characteristics from visible light (405 nm) to telecommunication wavelengths (i.e., 1550 nm) at room temperature. Trapezoidal optical programming can produce up to 100 recognizable states (>6 bits), with operating energy as low as 5.1 pJ per optical program. These results provide a route to realize fast, low power, multi-bit optoelectronic memory from visible to the infrared wavelength.