Artificial visual systems enabled by quasi-two-dimensional electron gases in oxide superlattice nanowires

Ultralow Power Optoelectronic Memtransistors Based on Vertical WS2/In2Se3 van der Waals Heterostructures

Memtransistors composed of 2D van der Waals (vdW) heterostructures are crucial for constructing artificial synaptic devices and realizing neuromorphic computing. The functional integration containing ultralow power, nonvolatile memory, and biomimetic synaptic behavior endows such devices with broad prospects. Here, we develop an optoelectronic memtransistor based on the WS2/In2Se3 vdW heterostructure and realize significant optical and electrical synaptic properties, which can simulate both short-range plasticity (STP) and long-range plasticity (LTP) of biological synapses. Under optical stimulation, the device demonstrates an ultralow power consumption (only 7.7 aJ per spike) significantly lower than biological synapses, indicating the application potential in large-scale neuromorphic hardware. Combining optical and electrical stimuli, we can perform multiple logic operations by controlling the optical and electrical inputs of the WS2/In2Se3-based memtransistor. Besides, simulated recognition utilizing the Modified National Institute of Standards and Technology data set can achieve a recognition accuracy of 85.41%. Notably, this accuracy can remain above 80% even with the introduction of Gaussian noise. These results demonstrate the promising potential of WS2/In2Se3-based memtransistors in future neuromorphic computing.

Retina-Inspired Flexible Visual Synaptic Device for Dynamic Image Processing

Exploiting biomimetic perception of invisible spectra in flexible artificial human vision systems (HVSs) is crucial for real-time dynamic information processing. Nevertheless, the fast processing of motion objects in natural environments poses a challenge, necessitating that these artificial HVSs simultaneously have swift photoresponse and nonvolatile memory. Here, inspired by the human retina, we propose a flexible UV neuromorphic visual synaptic device (NeuVSD) based on GaOx@GaN-composited nanowires for dynamic visual perception. Benefiting from the combined action of oxygen adsorption kinetics on the GaOx shell and photoelectronic excitation in the GaN core, the NeuVSD can achieve rapid photoresponse and long-term plasticity simultaneously, a feature that surpasses traditional devices based on persistent photoconductivity mechanisms. Beyond the optoelectronic synaptic plasticity, the flexible NeuVSD on the PET/PI substrate exhibits good performance stability after 1000 bending cycles, profiting from the high adaptability of nanowires. Furthermore, target recognition and motion detection with weak light intensities are achieved through the establishment of neuromorphic visual neural networks, relying on dynamic exposures and edge information processing, respectively. Real-time edge detection can still be realized under a 40% noise factor and effectively remove the noise background. The flexible NeuVSD array-based artificial visual system can enhance the capability of dynamic visual information processing in low-light and high-noise conditions, thereby fostering the evolution of in-sensor computing and artificial intelligence.

Bias-Switchable Photodetection and Photosynapse Dual-Functional Devices Based on 2D Perovskite/Organic Heterojunction for Imaging-to-Recognition Conversion

Optoelectronic devices with imaging and recognition capabilities are crucial for developing artificial visual system (AVS). Bias-switchable photodetection and photosynaptic devices have been developed using 2D perovskite oxide/organic heterojunctions. This unique structure allows for modulated carrier dynamics under varied bias conditions, enabling the devices to function as photodetectors without bias and as photosynapses with bias. At zero bias, the device achieves high responsivity (≈0.36 A W-1 at 320 nm) and rapid response speed (0.57 s). Under a -0.5 V bias, it exhibits persistent photoconductivity (PPC), resulting in neuromorphic synaptic behaviors with a paired-pulse facilitation (PPF) index exceeding 300%. Moreover, an 8 × 8 sensor array demonstrates image sensing and memory capabilities, showing in situ enhanced imaging when switching the bias from 0 to -0.5 V, and over 200 s of image memory. The image processing and recognition abilities are further explored by constructing an AVS using a 28 × 28 device array combined with an artificial neural network (ANN). The adjustable synaptic weight under different reverse biases allowed for optimized simulated recognition, achieving an accuracy of 92% after 160 training epochs. This work presents a novel method for creating dual-functional photodetection and photosynaptic devices, paving the way for a more integrated and efficient AVS.

Mechano-gated iontronic piezomemristor for temporal-tactile neuromorphic plasticity

In bioneuronal systems, the synergistic interaction between mechanosensitive piezo channels and neuronal synapses can convert and transmit pressure signals into complex temporal plastic pulses with excitatory and inhibitory features. However, existing artificial tactile neuromorphic systems struggle to replicate the elaborate temporal plasticity observed between excitatory and inhibitory features in biological systems, which is critical for the biomimetic processing and memorizing of tactile information. Here we demonstrate a mechano-gated iontronic piezomemristor with programmable temporal-tactile plasticity. This system utilizes a bicontinuous phase-transition heterogel as a stiffness-governed iontronic mechanogate to achieve bidirectional piezoresistive signals, resulting in wide-span dynamic tactile sensing. By micro-integrating the mechanogate with an oscillatory iontronic memristor, it exhibits stiffness-induced bipolarized excitatory and inhibitory neuromorphics, thereby enabling the activation of temporal-tactile memory and learning functions (e.g., Bienenstock-Cooper-Munro and Hebbian learning rules). Owing to dynamic covalent bond network and iontronic features, reconfigurable tactile plasticity can be achieved. Importantly, bridging to bioneuronal interfaces, these systems possess the capacity to construct a biohybrid perception-actuation circuit. We anticipate that such temporal plastic piezomemristor devices for abiotic-biotic interfaces can serve as promising hardware systems for interfacing dynamic tactile behaviors into diverse neuromodulations.

All-Optically Controlled Memristive Device Based on Cu2O/TiO2 Heterostructure Toward Neuromorphic Visual System

The optoelectronic memristor integrates the multifunctionalities of image sensing, storage, and processing, which has been considered as the leading candidate to construct novel neuromorphic visual system. In particular, memristive materials with all-optical modulation and complementary metal oxide semiconductor (CMOS) compatibility are highly desired for energy-efficient image perception. As a p-type oxide material, Cu2O exhibits outstanding theoretical photoelectric conversion efficiency and broadband photoresponse. In this work, an all-optically controlled memristor based on the Cu2O/TiO2/sodium alginate nanocomposite film is developed. Optical potentiation and depression behaviors have been implemented by utilizing visible (680 nm) and ultraviolet (350 nm) light. Furthermore, a 7 × 9 optoelectronic memristive array with satisfactory device variation and environment stability is constructed to emulate the image preprocessing function in biological retina. The random noise can be reduced effectively by utilizing bidirectional optical input. Beneficial from the image preprocessing function, the accuracy of handwritten digit classification increases more than 60%. Our work presents a pathway toward high-efficient neuromorphic visual system and promotes the development of artificial intelligence technology.

Tunable synaptic behaviors of solution-processed InGaO films for artificial visual systems

Due to their persistent photoconductivity, amorphous metal oxide thin films are promising for construction of artificial visual systems. In this work, large-scale, uniformly distributed amorphous InGaO thin films with an adjustable In/Ga ratio and thickness are prepared successfully by a low-cost environmentally friendly and easy-to-handle solution process for constructing artificial visual systems. With the increase of the In/Ga ratio and film thickness, the number of oxygen vacancies increases, along with the increase of post-synaptic current triggered by illumination, benefiting the transition of short-term plasticity to long-term plasticity. With an optimal In/Ga ratio and film thickness, the conductance response difference at a decay of 0 s between the 1st and the 10th views of a 5 × 5 array InGaO thin film transistor is up to 2.88 μA, along with an increase in the Idecay 30s/Idecay 0s ratio from 45.24% to 53.24%, resulting in a high image clarity and non-volatile artificial visual memory. Furthermore, a three-layer artificial vision network is constructed to evaluate the image recognition capability, exhibiting an accuracy of up to 91.32%. All results promise low-cost and easy-to-handle amorphous InGaO thin films for future visual information processing and image recognition.

Artificial organic afferent nerves enable closed-loop tactile feedback for intelligent robot

The emulation of tactile sensory nerves to achieve advanced sensory functions in robotics with artificial intelligence is of great interest. However, such devices remain bulky and lack reliable competence to functionalize further synaptic devices with proprioceptive feedback. Here, we report an artificial organic afferent nerve with low operating bias (-0.6 V) achieved by integrating a pressure-activated organic electrochemical synaptic transistor and artificial mechanoreceptors. The dendritic integration function for neurorobotics is achieved to perceive directional movement of object, further reducing the control complexity by exploiting the distributed and parallel networks. An intelligent robot assembled with artificial afferent nerve, coupled with a closed-loop feedback program is demonstrated to rapidly implement slip recognition and prevention actions upon occurrence of object slippage. The spatiotemporal features of tactile patterns are well differentiated with a high recognition accuracy after processing spike-encoded signals with deep learning model. This work represents a breakthrough in mimicking synaptic behaviors, which is essential for next-generation intelligent neurorobotics and low-power biomimetic electronics.

Unveiling cutting-edge developments: architectures and nanostructured materials for application in optoelectronic artificial synapses

One possible result of low-level characteristics in the traditional von Neumann formulation system is brain-inspired photonics technology based on human brain idea. Optoelectronic neural devices, which are accustomed to imitating the sensory role of biological synapses by adjusting connection measures, can be used to fabricate highly reliable neurologically calculating devices. In this case, nanosized materials and device designs are attracting attention since they provide numerous potential benefits in terms of limited cool contact, rapid transfer fluidity, and the capture of photocarriers. In addition, the combination of classic nanosized photodetectors with recently generated digital synapses offers promising results in a variety of practical applications, such as data processing and computation. Herein, we present the progress in constructing improved optoelectronic synaptic devices that rely on nanomaterials, for example, 0-dimensional (quantum dots), 1-dimensional, and 2-dimensional composites, besides the continuously developing mixed heterostructures. Furthermore, the challenges and potential prospects linked with this field of study are discussed in this paper.

Conformal Neuromorphic Bioelectronics for Sense Digitalization

Sense digitalization, the process of transforming sensory experiences into digital data, is an emerging research frontier that links the physical world with human perception and interaction. Inspired by the adaptability, fault tolerance, robustness, and energy efficiency of biological senses, this field drives the development of numerous innovative digitalization techniques. Neuromorphic bioelectronics, characterized by biomimetic adaptability, stand out for their seamless bidirectional interactions with biological entities through stimulus-response and feedback loops, incorporating bio-neuromorphic intelligence for information exchange. This review illustrates recent progress in sensory digitalization, encompassing not only the digital representation of physical sensations such as touch, light, and temperature, correlating to tactile, visual, and thermal perceptions, but also the detection of biochemical stimuli such as gases, ions, and neurotransmitters, mirroring olfactory, gustatory, and neural processes. It thoroughly examines the material design, device manufacturing, and system integration, offering detailed insights. However, the field faces significant challenges, including the development of new device/system paradigms, forging genuine connections with biological systems, ensuring compatibility with the semiconductor industry and overcoming the absence of standardization. Future ambition includes realization of biocompatible neural prosthetics, exoskeletons, soft humanoid robots, and cybernetic devices that integrate smoothly with both biological tissues and artificial components.

An inorganic-blended p-type semiconductor with robust electrical and mechanical properties

Inorganic semiconductors typically have limited p-type behavior due to the scarcity of holes and the localized valence band maximum, hindering the progress of complementary devices and circuits. In this work, we propose an inorganic blending strategy to activate the hole-transporting character in an inorganic semiconductor compound, namely tellurium-selenium-oxygen (TeSeO). By rationally combining intrinsic p-type semimetal, semiconductor, and wide-bandgap semiconductor into a single compound, the TeSeO system displays tunable bandgaps ranging from 0.7 to 2.2 eV. Wafer-scale ultrathin TeSeO films, which can be deposited at room temperature, display high hole field-effect mobility of 48.5 cm2/(Vs) and robust hole transport properties, facilitated by Te-Te (Se) portions and O-Te-O portions, respectively. The nanosphere lithography process is employed to create nanopatterned honeycomb TeSeO broadband photodetectors, demonstrating a high responsibility of 603 A/W, an ultrafast response of 5 μs, and superior mechanical flexibility. The p-type TeSeO system is highly adaptable, scalable, and reliable, which can address emerging technological needs that current semiconductor solutions may not fulfill.

Reconfigurable optoelectronic transistors for multimodal recognition

Biological nervous system outperforms in both dynamic and static information perception due to their capability to integrate the sensing, memory and processing functions. Reconfigurable neuromorphic transistors, which can be used to emulate different types of biological analogues in a single device, are important for creating compact and efficient neuromorphic computing networks, but their design remains challenging due to the need for opposing physical mechanisms to achieve different functions. Here we report a neuromorphic electrolyte-gated transistor that can be reconfigured to perform physical reservoir and synaptic functions. The device exhibits dynamics with tunable time-scales under optical and electrical stimuli. The nonlinear volatile property is suitable for reservoir computing, which can be used for multimodal pre-processing. The nonvolatility and programmability of the device through ion insertion/extraction achieved via electrolyte gating, which are required to realize synaptic functions, are verified. The device's superior performance in mimicking human perception of dynamic and static multisensory information based on the reconfigurable neuromorphic functions is also demonstrated. The present study provides an exciting paradigm for the realization of multimodal reconfigurable devices and opens an avenue for mimicking biological multisensory fusion.

Anti-Ambipolar Heterojunctions: Materials, Devices, and Circuits

Anti-ambipolar heterojunctions are vital in constructing high-frequency oscillators, fast switches, and multivalued logic (MVL) devices, which hold promising potential for next-generation integrated circuit chips and telecommunication technologies. Thanks to the strategic material design and device integration, anti-ambipolar heterojunctions have demonstrated unparalleled device and circuit performance that surpasses other semiconducting material systems. This review aims to provide a comprehensive summary of the achievements in the field of anti-ambipolar heterojunctions. First, the fundamental operating mechanisms of anti-ambipolar devices are discussed. After that, potential materials used in anti-ambipolar devices are discussed with particular attention to 2D-based, 1D-based, and organic-based heterojunctions. Next, the primary device applications employing anti-ambipolar heterojunctions, including anti-ambipolar transistors (AATs), photodetectors, frequency doublers, and synaptic devices, are summarized. Furthermore, alongside the advancements in individual devices, the practical integration of these devices at the circuit level, including topics such as MVL circuits, complex logic gates, and spiking neuron circuits, is also discussed. Lastly, the present key challenges and future research directions concerning anti-ambipolar heterojunctions and their applications are also emphasized.

Biomimetic Wearable Sensors: Emerging Combination of Intelligence and Electronics

Owing to the advancement of interdisciplinary concepts, for example, wearable electronics, bioelectronics, and intelligent sensing, during the microelectronics industrial revolution, nowadays, extensively mature wearable sensing devices have become new favorites in the noninvasive human healthcare industry. The combination of wearable sensing devices with bionics is driving frontier developments in various fields, such as personalized medical monitoring and flexible electronics, due to the superior biocompatibilities and diverse sensing mechanisms. It is noticed that the integration of desired functions into wearable device materials can be realized by grafting biomimetic intelligence. Therefore, herein, the mechanism by which biomimetic materials satisfy and further enhance system functionality is reviewed. Next, wearable artificial sensory systems that integrate biomimetic sensing into portable sensing devices are introduced, which have received significant attention from the industry owing to their novel sensing approaches and portabilities. To address the limitations encountered by important signal and data units in biomimetic wearable sensing systems, two paths forward are identified and current challenges and opportunities are presented in this field. In summary, this review provides a further comprehensive understanding of the development of biomimetic wearable sensing devices from both breadth and depth perspectives, offering valuable guidance for future research and application expansion of these devices.

Hierarchies in Visual Pathway: Functions and Inspired Artificial Vision

The development of artificial intelligence has posed a challenge to machine vision based on conventional complementary metal-oxide semiconductor (CMOS) circuits owing to its high latency and inefficient power consumption originating from the data shuffling between memory and computation units. Gaining more insights into the function of every part of the visual pathway for visual perception can bring the capabilities of machine vision in terms of robustness and generality. Hardware acceleration of more energy-efficient and biorealistic artificial vision highly necessitates neuromorphic devices and circuits that are able to mimic the function of each part of the visual pathway. In this paper, we review the structure and function of the entire class of visual neurons from the retina to the primate visual cortex within reach (Chapter 2) are reviewed. Based on the extraction of biological principles, the recent hardware-implemented visual neurons located in different parts of the visual pathway are discussed in detail in Chapters 3 and 4. Furthermore, valuable applications of inspired artificial vision in different scenarios (Chapter 5) are provided. The functional description of the visual pathway and its inspired neuromorphic devices/circuits are expected to provide valuable insights for the design of next-generation artificial visual perception systems.

Integrated Graphene Heterostructures in Optical Sensing

Graphene-an outstanding low-dimensional material-exhibited many physics behaviors that are unknown over the past two decades, e.g., exceptional matter-light interaction, large light absorption band, and high charge carrier mobility, which can be adjusted on arbitrary surfaces. The deposition approaches of graphene on silicon to form the heterostructure Schottky junctions was studied, unveiling new roadmaps to detect the light at wider-ranged absorption spectrums, e.g., far-infrared via excited photoemission. In addition, heterojunction-assisted optical sensing systems enable the active carriers' lifetime and, thereby, accelerate the separation speed and transport, and then they pave new strategies to tune high-performance optoelectronics. In this mini-review, an overview is considered concerning recent advancements in graphene heterostructure devices and their optical sensing ability in multiple applications (ultrafast optical sensing system, plasmonic system, optical waveguide system, optical spectrometer, or optical synaptic system) is discussed, in which the prominent studies for the improvement of performance and stability, based on the integrated graphene heterostructures, have been reported and are also addressed again. Moreover, the pros and cons of graphene heterostructures are revealed along with the syntheses and nanofabrication sequences in optoelectronics. Thereby, this gives a variety of promising solutions beyond the ones presently used. Eventually, the development roadmap of futuristic modern optoelectronic systems is predicted.

Van der Waals nanomesh electronics on arbitrary surfaces

Chemical bonds, including covalent and ionic bonds, endow semiconductors with stable electronic configurations but also impose constraints on their synthesis and lattice-mismatched heteroepitaxy. Here, the unique multi-scale van der Waals (vdWs) interactions are explored in one-dimensional tellurium (Te) systems to overcome these restrictions, enabled by the vdWs bonds between Te atomic chains and the spontaneous misfit relaxation at quasi-vdWs interfaces. Wafer-scale Te vdWs nanomeshes composed of self-welding Te nanowires are laterally vapor grown on arbitrary surfaces at a low temperature of 100 °C, bringing greater integration freedoms for enhanced device functionality and broad applicability. The prepared Te vdWs nanomeshes can be patterned at the microscale and exhibit high field-effect hole mobility of 145 cm²/Vs, ultrafast photoresponse below 3 μs in paper-based infrared photodetectors, as well as controllable electronic structure in mixed-dimensional heterojunctions. All these device metrics of Te vdWs nanomesh electronics are promising to meet emerging technological demands.

Dynamic machine vision with retinomorphic photomemristor-reservoir computing

Dynamic machine vision requires recognizing the past and predicting the future of a moving object based on present vision. Current machine vision systems accomplish this by processing numerous image frames or using complex algorithms. Here, we report motion recognition and prediction in recurrent photomemristor networks. In our system, a retinomorphic photomemristor array, working as dynamic vision reservoir, embeds past motion frames as hidden states into the present frame through inherent dynamic memory. The informative present frame facilitates accurate recognition of past and prediction of future motions with machine learning algorithms. This in-sensor motion processing capability eliminates redundant data flows and promotes real-time perception of moving objects for dynamic machine vision.

Emerging photoelectric devices for neuromorphic vision applications: principles, developments, and outlooks

The traditional von Neumann architecture is gradually failing to meet the urgent need for highly parallel computing, high-efficiency, and ultra-low power consumption for the current explosion of data. Brain-inspired neuromorphic computing can break the inherent limitations of traditional computers. Neuromorphic devices are the key hardware units of neuromorphic chips to implement the intelligent computing. In recent years, the development of optogenetics and photosensitive materials has provided new avenues for the research of neuromorphic devices. The emerging optoelectronic neuromorphic devices have received a lot of attentions because they have shown great potential in the field of visual bionics. In this paper, we summarize the latest visual bionic applications of optoelectronic synaptic memristors and transistors based on different photosensitive materials. The basic principle of bio-vision formation is first introduced. Then the device structures and operating mechanisms of optoelectronic memristors and transistors are discussed. Most importantly, the recent progresses of optoelectronic synaptic devices based on various photosensitive materials in the fields of visual perception are described. Finally, the problems and challenges of optoelectronic neuromorphic devices are summarized, and the future development of visual bionics is also proposed.

Au-Seeded CsPbI3 Nanowire Optoelectronics via Exothermic Nucleation

Converting vapor precursors to solid nanostructures via a liquid noble-metal seed is a common vapor deposition principle. However, such a noble-metal-seeded process is excluded from the crystalline halide perovskite synthesis, mainly hindered by the growth mechanism shortness. Herein, powered by a spontaneous exothermic nucleation process (ΔH < 0), the Au-seeded CsPbI₃ nanowires (NWs) growth is realized based on a vapor-liquid-solid (VLS) growth mode. It is energetically favored that the Au seeds are reacted with a Pb vapor precursor to form molten Au-Pb droplets at temperatures down to 212 °C, further triggering the low-temperature VLS growth of CsPbI₃ NWs. More importantly, this Au-seeded process reduces in-bandgap trap states and consequently avoids Shockley-Read-Hall recombination, contributing to outstanding photodetector performances. Our work extends the powerful Au-seeded VLS growth mode to the emerging halide perovskites, which will facilitate their nanostructures with tailored material properties.

One-Dimensional Atomic Chains for Ultimate-Scaled Electronics

The continuous downscaling of semiconducting channels in transistors has driven the development of modern electronics. However, with the component transistors becoming smaller and denser on a single chip, the continued downscaling progress has touched the physical limits. In this Perspective, we suggest that the emerging one-dimensional (1D) material system involving inorganic atomic chains (ACs) that are packed by van der Waals (vdW) interactions may tackle this issue. Stemming from their 1D crystal structures and naturally terminated surfaces, 1D ACs could potentially shrink transistors to atomic-scale diameters. Also, we argue that 1D ACs with few-atom widths allow us to revisit 1D materials and uncover physical properties distinct from conventional materials. These ultrathin 1D AC materials demand substantive attention. They may bring opportunities to develop ultimate-scaled AC-based electronic, optoelectronic, thermoelectric, spintronic, memory devices, etc.

Co-assembled perylene/graphene oxide photosensitive heterobilayer for efficient neuromorphics

Neuromorphic electronics, which use artificial photosensitive synapses, can emulate biological nervous systems with in-memory sensing and computing abilities. Benefiting from multiple intra/interactions and strong light-matter coupling, two-dimensional heterostructures are promising synaptic materials for photonic synapses. Two primary strategies, including chemical vapor deposition and physical stacking, have been developed for layered heterostructures, but large-scale growth control over wet-chemical synthesis with comprehensive efficiency remains elusive. Here we demonstrate an interfacial coassembly heterobilayer films from perylene and graphene oxide (GO) precursors, which are spontaneously formed at the interface, with uniform bilayer structure of single-crystal perylene and well-stacked GO over centimeters in size. The planar heterostructure device exhibits an ultrahigh specific detectivity of 3.1 × 10¹³ Jones and ultralow energy consumption of 10⁻⁹ W as well as broadband photoperception from 365 to 1550 nm. Moreover, the device shows outstanding photonic synaptic behaviors with a paired-pulse facilitation (PPF) index of 214% in neuroplasticity, the heterosynapse array has the capability of information reinforcement learning and recognition.

Layered heterostructures are promising photosensitive materials for advanced optoelectronics. Here, the authors introduce an interfacial coassembly method to construct large-scale perylene/grahene oxide (GO) heterobilayer for broadband photoreception and efficient neuromorphics.

Deep Ultraviolet Light Stimulated Synaptic Transistors Based on Poly(3-hexylthiophene) Ultrathin Films

Deep ultraviolet (DUV)-light-stimulated artificial synaptic devices exhibit potential applications in various disciplines including intelligent military monitoring, biological and medical analysis, flame detection, etc. Along these lines, we report here a DUV-light-stimulated synaptic transistor fabricated on a poly(3-hexylthiophene) (P3HT) ultrathin film that responds selectively to DUV light. Significantly, our devices have the ability to successfully simulate various synapse-like behaviors including excitatory postsynaptic currents (EPSCs), paired-pulse facilitation (PPF), short-term memory (STM), long-term memory (LTM), STM-to-LTM transition, and learning and forgetting behaviors. Moreover, the proposed artificial synaptic structures were also fabricated on flexible poly(ethylene terephthalate) (PET) substrates and also successfully simulated typical synaptic behaviors, which could be of great importance for wearable applications.

2D Heterostructures for Ubiquitous Electronics and Optoelectronics: Principles, Opportunities, and Challenges

A grand family of two-dimensional (2D) materials and their heterostructures have been discovered through the extensive experimental and theoretical efforts of chemists, material scientists, physicists, and technologists. These pioneering works contribute to realizing the fundamental platforms to explore and analyze new physical/chemical properties and technological phenomena at the micro-nano-pico scales. Engineering 2D van der Waals (vdW) materials and their heterostructures via chemical and physical methods with a suitable choice of stacking order, thickness, and interlayer interactions enable exotic carrier dynamics, showing potential in high-frequency electronics, broadband optoelectronics, low-power neuromorphic computing, and ubiquitous electronics. This comprehensive review addresses recent advances in terms of representative 2D materials, the general fabrication methods, and characterization techniques and the vital role of the physical parameters affecting the quality of 2D heterostructures. The main emphasis is on 2D heterostructures and 3D-bulk (3D) hybrid systems exhibiting intrinsic quantum mechanical responses in the optical, valley, and topological states. Finally, we discuss the universality of 2D heterostructures with representative applications and trends for future electronics and optoelectronics (FEO) under the challenges and opportunities from physical, nanotechnological, and material synthesis perspectives.

Reversible Manipulation of Photoconductivity Caused by Surface Oxygen Vacancies in Perovskite Stannates with Ultraviolet Light

Programmable optoelectronic devices call for the reversible control of the photocarrier recombination process by in-gap states in oxide semiconductors. However, previous approaches to produce oxygen vacancies as a source of in-gap states in oxide semiconductors have hampered the reversible formation of oxygen vacancies and their related phenomena. Here, a new strategy to manipulate the 2D photoconductivity from perovskite stannates is demonstrated by exploiting spatially selective photochemical reaction under ultraviolet illumination at room temperature. Remarkably, the ideal trap-free photocurrent of air-illuminated BaSnO₃ (≈200 pA) is reversibly switched into three orders of magnitude higher photocurrent of vacuum-illuminated BaSnO₃ (≈335 nA) with persistent photoconductivity depending on ambient oxygen pressure under illumination. Multiple characterizations elucidate that ultraviolet illumination of BaSnO₃  under low oxygen pressure induces surface oxygen vacancies as a result of surface photolysis combined with the low oxygen-diffusion coefficient of BaSnO₃ ; the concentrated oxygen vacancies are likely to induce a two-step transition of photocurrent response by changing the characteristics of in-gap states from the shallow level to the deep level. These results suggest a novel strategy that uses light-matter interaction in a reversible and spatially confined way to manipulate functionalities related to surface defect states, for the emerging applications using newly discovered oxide semiconductors.

GaOx@GaN Nanowire Arrays on Flexible Graphite Paper with Tunable Persistent Photoconductivity

Flexible optoelectronic synaptic devices that functionally imitate the neural behavior with tunable optoelectronic characteristics are crucial to the development of advanced bioinspired neural networks. In this work, amorphous oxide-decorated GaN nanowire arrays (GaO_x@GaN NWAs) are prepared on flexible graphite paper. A GaO_x@GaN NWA-based flexible device has tunable persistent photoconductivity (PPC) and shows a conversible fast/slow decay process (SDP). Photoconductivity can be modulated by single or double light pulses with different illumination powers and biases. PPC gives rise to the high-performance SDP such as a long decay time of 2.3 × 10⁵ s. The modulation mechanism is proposed and discussed. Our results reveal an innovative and efficient strategy to produce decorated NWAs on a flexible substrate with tunable optoelectronic properties and exhibit potential for flexible neuromorphic system applications.

Transparent photovoltaic memory for neuromorphic device

Bio-inspired electronic devices have significant potential for use in memory devices of the future, including in the context of neuromorphic computing and architecture. This study proposes a transparent heterojunction device for the artificial human visual cortex. Owing to their high transparency, such devices directly react to incoming light to mimic neurological and biological processes in the nervous system. Metal-oxide materials are applied to form a transparent heterojunction (n-type ZnO/p-type NiO) in the proposed device that also provides the photovoltaic function to realize the optic nerve system. The device also exhibits nociceptive features. Its transparent photovoltaic feature endows it with self-powered operation that ensures long-term reliability without needing to replace the power system. This self-powered and highly transparent visual electronic device can provide a route for sustainable applications of neuromorphic computing, including artificial eyes.

Retina-Inspired Organic Heterojunction-Based Optoelectronic Synapses for Artificial Visual Systems

For the realization of retina-inspired neuromorphic visual systems which simulate basic functions of human visual systems, optoelectronic synapses capable of combining perceiving, processing, and memorizing in a single device have attracted immense interests. Here, optoelectronic synaptic transistors based on tris(2-phenylpyridine) iridium (Ir(ppy)₃) and poly(3,3-didodecylquarterthiophene) (PQT-12) heterojunction structure are presented. The organic heterojunction serves as a basis for distinctive synaptic characteristics under different wavelengths of light. Furthermore, synaptic transistor arrays are fabricated to demonstrate their optical perception efficiency and color recognition capability under multiple illuminating conditions. The wavelength-tunability of synaptic behaviors further enables the mimicry of mood-modulated visual learning and memorizing processes of humans. More significantly, the computational dynamics of neurons of synaptic outputs including associated learning and optical logic functions can be successfully demonstrated on the presented devices. This work may locate the stage for future studies on optoelectronic synaptic devices toward the implementation of artificial visual systems.