Two-dimensional ferroelectric channel transistors integrating ultra-fast memory and neural computing

Van der Waals Layer Transfer of 2D Materials for Monolithic 3D Electronic System Integration: Review and Outlook

Two-dimensional materials (2DMs) have attracted a great deal of interest due to their immense potential for scientific breakthroughs and technological innovations. While some 2D transition metal dichalcogenides (TMDC) such as MoS₂ and WS₂ are considered as the ultimate channel materials in unltrascaled transistors as replacements for Si, there has also been increasing interest in the monolithic 3D integration of 2DMs on the Si CMOS platform or in flexible electronics as back-end-of-line transistors, memory devices/selectors, and sensors, taking advantage of 2DM properties such as a high current driving capability with low leakage current, nonvolatile switching characteristics, a large surface-to-volume ratio, and a tunable bandgap. However, the realization of both of these scenarios critically depends on the development of manufacturing-viable high-yield 2DM layers transfer from the growth substrate to the Si, since the growth of high-quality 2DM layers often requires a high-temperature growth process on template substrates. Motivated by this, extensive efforts have been made by the 2DM research community to develop various 2DM layer transfer methods, leveraging the van der Waals transfer capability of the layer-structured 2DMs. These efforts have led to a number of successful demonstrations of wafer-scale 2D TMDC layer transfer, while 2DM-enabled template growth/transfer of some functional bulk materials such as III-V, Ge, and AlN has also been demonstrated. This review surveys and compares different 2DM transfer methods developed recently, with a focus on large-area 2D TMDC film transfer along with an introduction of 2DM template-assisted van der Waals growth/transfer of non-2D thin films. We will also briefly present an outlook of our envisioned multifunctionalities in 3D integrated electronic systems enabled by monolithic 3D integration of 2DMs and III-V via van der Waals transfer and discuss possible technology options for overcoming remaining challenges.

Phase-controllable large-area two-dimensional In2Se3 and ferroelectric heterophase junction

Memory transistors based on two-dimensional (2D) ferroelectric semiconductors are intriguing for next-generation in-memory computing. To date, several 2D ferroelectric materials have been unveiled, among which 2D In₂Se₃ is the most promising, as all the paraelectric (β), ferroelectric (α) and antiferroelectric (β') phases are found in 2D quintuple layers. However, the large-scale synthesis of 2D In₂Se₃ films with the desired phase is still absent, and the stability for each phase remains obscure. Here we show the successful growth of centimetre-scale 2D β-In₂Se₃ film by chemical vapour deposition including distinct centimetre-scale 2D β'-In₂Se₃ film by an InSe precursor. We also demonstrate that as-grown 2D β'-In₂Se₃ films on mica substrates can be delaminated or transferred onto flexible or uneven substrates, yielding α-In₂Se₃ films through a complete phase transition. Thus, a full spectrum of paraelectric, ferroelectric and antiferroelectric 2D films can be readily obtained by means of the correlated polymorphism in 2D In₂Se₃, enabling 2D memory transistors with high electron mobility, and polarizable β'-α In₂Se₃ heterophase junctions with improved non-volatile memory performance.

Quasi-Volatile MoS2 Barristor Memory for 1T Compact Neuron by Correlative Charges Trapping and Schottky Barrier Modulation

Artificial neurons as the basic units of spiking neural network (SNN) have attracted increasing interest in energy-efficient neuromorphic computing. 2D transition metal dichalcogenide (TMD)-based devices have great potential for high-performance and low-power artificial neural devices, owing to their unique ion motion, interface engineering, and resistive switching behaviors. Although there are widespread applications of TMD-based artificial synapses in neural networks, TMD-based neurons are seldom reported due to the lack of bio-plausible multi-mechanisms to mimic leaking, integrating, and firing biological behaviors without external assistance. In this work, for the first time, a methodology is developed by introducing the hybrid effect of charge trapping (CT) and Schottky barrier (SB) in MoS₂ FETs for barristor memory and one-transistor (1T) compact artificial neuron realization. By correlating the CT and SB processes, quasi-volatile and resistive switching behaviors are realized on the fabricated MoS₂ FET and utilized to mimic the accumulating, leaking, and firing biological behaviors of neurons. Therefore, based on a single quasi-volatile CT-SB MoS₂ barristor memory, a 1T compact neuron of the basic leaky-integral-and-fire (LIF) function is demonstrated without a peripheral circuit. Furthermore, a spiking neural network (SNN) based on the CT-SB MoS₂ barristor neurons is simulated and implemented in pattern classification with high accuracy approaching 95.82%. This work provides a highly integrated and inherently low-energy implementation for neural networks.

Self-Powered Bidirectional Photoresponse in High-Detectivity WSe2 Phototransistor with Asymmetrical van der Waals Stacking for Retinal Neurons Emulation

An artificial retina system shows a promising potential to achieve fast response, low power consumption, and high integration density for vision sensing systems. Optoelectronic sensors, which can emulate the neurobiological functionalities of retinal neurons, are crucial in the artificial retina systems. Here, we propose a WSe₂ phototransistor with asymmetrical van der Waals (vdWs) stacking that can be used as an optoelectronic sensor in artificial retina systems. Through the utilization of the gate-tunable self-powered bidirectional photoresponse of this phototransistor, the neurobiological functionalities of both bipolar cells and cone cells, as well as the hierarchical connectivity between these two types of retinal neurons, are successfully mimicked by a single device. This self-powered bidirectional photoresponse is attributed to the asymmetrical vdWs stacking structure, which enables the transition from an n-p to p⁺-p homojunction in the WSe₂ channel under different polarities of gate bias. Moreover, the detectivity and ON/OFF ratio of this phototransistor reach as high as 1.8 × 10¹³ Jones and 5.3 × 10⁴, respectively, and a rise/fall time <80 μs is achieved, as well, which reveals good photodetection performance. The proof of this device provides a pathway for the future development of neuromorphic vision devices and systems.

Bulk Photovoltage Effect in Ferroelectric BaTiO3

Due to the unusual charge separation mechanism and anomalous photovoltaic effects, the bulk photovoltage effect in ferroelectric semiconductors has attracted a great deal of attention in solar energy conversion, especially in attempts to utilize nonthermalized carriers. Among the various mechanisms that have been proposed for interpreting the photovoltaic effect, a shift mechanism was derived from quantum phenomena, which have been modeled and studied for many years. However, the concurrent shift and ballistic mechanism make investigating the ferroelectric bulk photovoltage effect complex and challenging. Here, taking a tetragonal ferroelectric BaTiO₃ single crystal as a prototype, we report an approach for distinguishing the shift and ballistic mechanism-induced surface photovoltage. The results indicate different effects on the charge separation of the ballistic mechanism and shift mechanisms, as evidenced by surface photovoltage measurement. Interestingly, the shift and ballistic mechanisms afford charge separation in two opposite directions but on the same order of magnitude under monochromatic superband illumination. Our results provide facile and efficient methods for clarifying the shift and ballistic mechanisms in ferroelectrics.

Multilayer Reservoir Computing Based on Ferroelectric α-In2 Se3 for Hierarchical Information Processing

Dynamic physical systems such as reservoir computing (RC) architectures show a great prospect in temporal information processing, whereas hierarchical information processing capability is still lacking due to the absence of advanced multilayer reservoir elements. Here, a stackable reservoir system is constructed based on ferroelectric α-In₂ Se₃ devices with voltage input and output, which is realized by dynamic voltage division between a ferroelectric field-effect transistor and a planar device and therefore allows the reservoirs to cascade, enabling multilayer RC. Fast Fourier transformation analysis shows high-harmonic generation in the first layer as a result of inherent nonlinearity of the reservoir, and progressive low-pass filtering effect is realized where higher-frequency components are progressively filtered in deeper-layer RCs. Time-series prediction and waveform classification tasks are also demonstrated, serving as evidence for the memory capacity and computing capability of the deep reservoir architecture. This work can provide a promising pathway in exploiting emerging 2D materials and dynamics for advanced neuromorphic computing architectures.

The Road for 2D Semiconductors in the Silicon Age

Continued reduction in transistor size can improve the performance of silicon integrated circuits (ICs). However, as Moore's law approaches physical limits, high-performance growth in silicon ICs becomes unsustainable, due to challenges of scaling, energy efficiency, and memory limitations. The ultrathin layers, diverse band structures, unique electronic properties, and silicon-compatible processes of 2D materials create the potential to consistently drive advanced performance in ICs. Here, the potential of fusing 2D materials with silicon ICs to minimize the challenges in silicon ICs, and to create technologies beyond the von Neumann architecture, is presented, and the killer applications for 2D materials in logic and memory devices to ease scaling, energy efficiency bottlenecks, and memory dilemmas encountered in silicon ICs are discussed. The fusion of 2D materials allows the creation of all-in-one perception, memory, and computation technologies beyond the von Neumann architecture to enhance system efficiency and remove computing power bottlenecks. Progress on the 2D ICs demonstration is summarized, as well as the technical hurdles it faces in terms of wafer-scale heterostructure growth, transfer, and compatible integration with silicon ICs. Finally, the promising pathways and obstacles to the technological advances in ICs due to the integration of 2D materials with silicon are presented.

Bipolar charge collecting structure enables overall water splitting on ferroelectric photocatalysts

Ferroelectrics are considered excellent photocatalytic candidates for solar fuel production because of the unidirectional charge separation and above-gap photovoltage. Nevertheless, the performance of ferroelectric photocatalysts is often moderate. A few studies showed that these types of photocatalysts could achieve overall water splitting. This paper proposes an approach to fabricating interfacial charge-collecting nanostructures on positive and negative domains of ferroelectric, enabling water splitting in ferroelectric photocatalysts. The present study observes efficient accumulations of photogenerated electrons and holes within their thermalization length (~50 nm) around Au nanoparticles located in the positive and negative domains of a BaTiO3 single crystal. Photocatalytic overall water splitting is observed on a ferroelectric BaTiO3 single crystal after assembling oxidation and reduction cocatalysts on the positively and negatively charged Au nanoparticles, respectively. The fabrication of bipolar charge-collecting structures on ferroelectrics to achieve overall water splitting offers a way to utilize the energetic photogenerated charges in solar energy conversion.

Integrated Memory Devices Based on 2D Materials

With the advent of the Internet of Things and big data, massive data must be rapidly processed and stored within a short timeframe. This imposes stringent requirements on memory hardware implementation in terms of operation speed, energy consumption, and integration density. To fulfill these demands, 2D materials, which are excellent electronic building blocks, provide numerous possibilities for developing advanced memory device arrays with high performance, smart computing architectures, and desirable downscaling. Over the past few years, 2D-material-based memory-device arrays with different working mechanisms, including defects, filaments, charges, ferroelectricity, and spins, have been increasingly developed. These arrays can be used to implement brain-inspired computing or sensing with extraordinary performance, architectures, and functionalities. Here, recent research into integrated, state-of-the-art memory devices made from 2D materials, as well as their implications for brain-inspired computing are surveyed. The existing challenges at the array level are discussed, and the scope for future research is presented.

Van der Waals-Interface-Dominated All-2D Electronics

The interface is the device. As the feature size rapidly shrinks, silicon-based electronic devices are facing multiple challenges of material performance decrease and interface quality degradation. Ultrathin 2D materials are considered as potential candidates in future electronics by their atomically flat surfaces and excellent immunity to short-channel effects. Moreover, due to naturally terminated surfaces and weak van der Waals (vdW) interactions between layers, 2D materials can be freely stacked without the lattice matching limit to form high-quality heterostructure interfaces with arbitrary components and twist angles. Controlled interlayer band alignment and optimized interfacial carrier behavior allow all-2D electronics based on 2D vdW interfaces to exhibit more comprehensive functionality and better performance. Especially, achieving the same computing capacity of multiple conventional devices with small footprint all-2D devices is considered to be the key development direction of future electronics. Herein, the unique properties of all-2D vdW interfaces and their construction methods are systematically reviewed and the main performance contributions of different vdW interfaces in 2D electronics are summarized, respectively. Finally, the recent progress and challenges for all-2D vdW electronics are discussed, and how to improve the compatibility of 2D material devices with silicon-based industrial technology is pointed out as a critical challenge.

Highly Linear and Symmetric Synaptic Memtransistors Based on Polarization Switching in Two-Dimensional Ferroelectric Semiconductors

Brain-inspired neuromorphic computing hardware based on artificial synapses offers efficient solutions to perform computational tasks. However, the nonlinearity and asymmetry of synaptic weight updates in reported artificial synapses have impeded achieving high accuracy in neural networks. Here, this work develops a synaptic memtransistor based on polarization switching in a two-dimensional (2D) ferroelectric semiconductor (FES) of α-In₂ Se₃ for neuromorphic computing. The α-In₂ Se₃ memtransistor exhibits outstanding synaptic characteristics, including near-ideal linearity and symmetry and a large number of programmable conductance states, by taking the advantages of both memtransistor configuration and electrically configurable polarization states in the FES channel. As a result, the α-In₂ Se₃ memtransistor-type synapse reaches high accuracy of 97.76% for digit patterns recognition task in simulated artificial neural networks. This work opens new opportunities for using multiterminal FES memtransistors in advanced neuromorphic electronics.

Superlow Power Consumption Artificial Synapses Based on WSe2 Quantum Dots Memristor for Neuromorphic Computing

As the emerging member of zero-dimension transition metal dichalcogenide, WSe₂ quantum dots (QDs) have been applied to memristors and exhibited better resistance switching characteristics and miniaturization size. However, low power consumption and high reliability are still challenges for WSe₂ QDs-based memristors as synaptic devices. Here, we demonstrate a high-performance, superlow power consumption memristor device with the structure of Ag/WSe₂ QDs/La_0.3Sr_0.7MnO₃/SrTiO₃. The device displays excellent resistive switching memory behavior with a R_OFF/R_ON ratio of ~5 × 10³, power consumption per switching as low as 0.16 nW, very low set, and reset voltage of ~0.52 V and~ -0.19 V with excellent cycling stability, good reproducibility, and decent data retention capability. The superlow power consumption characteristic of the device is further proved by the method of density functional theory calculation. In addition, the influence of pulse amplitude, duration, and interval was studied to gradually modulating the conductance of the device. The memristor has also been demonstrated to simulate different functions of artificial synapses, such as excitatory postsynaptic current, spike timing-dependent plasticity, long-term potentiation, long-term depression, and paired-pulse facilitation. Importantly, digit recognition ability based on the WSe₂ QDs device is evaluated through a three-layer artificial neural network, and the digit recognition accuracy after 40 times of training can reach up to 94.05%. This study paves a new way for the development of memristor devices with advanced significance for future low power neuromorphic computing.

2D Multiferroicity with Ferroelectric Switching Induced Spin-Constrained Photoelectricity

Multiferroic materials with tunable magnetoelectric orders enable the integration of sensing, data storage, and processing into one single device. The scarcity of single-phase multiferroics spurs extensive research in pursuit of composite systems combining different types of ferroic materials. In this work, spin-constrained photoelectric memory is proposed in two-dimensional (2D) layered magnetic/ferroelectric heterostructures, holding the possibility of low-power electrical write operation and nondestructive optical read operation. The ground state of ferromagnetic (FM) and antiferromagnetic (AFM) orderings in the magnetic layer is altered by polarization direction of the ferroelectric layer. Specifically, the FM heterostructure exhibits a type-II band alignment. Due to the light-induced charge transfer, spin-polarized/unpolarized current arises from the FM/AFM state, which can be recorded as the "1"/"0" state and served for logic processing and memory applications. Our first-principles calculations demonstrate that the NiI₂/In₂Se₃ heterobilayer is an ideal candidate to realize such a spin-dependent photoelectric memory. The reversible FM state (easy-axis magnetic anisotropy) and AFM state (easy-plane magnetic orientation) in the NiI₂ layer originate from interfacial charge transfer and effective electric field due to the proximity effect. This work offers considerable potential in the integration of memory processing capability into one single device with 2D layered multiferroic heterostructures.

Ferroelectric Field-Effect-Transistor Integrated with Ferroelectrics Heterostructure

To address the demands of emerging data-centric computing applications, ferroelectric field-effect transistors (Fe-FETs) are considered the forefront of semiconductor electronics owing to their energy and area efficiency and merged logic-memory functionalities. Herein, the fabrication and application of an Fe-FET, which is integrated with a van der Waals ferroelectrics heterostructure (CuInP₂ S₆ /α-In₂ Se₃ ), is reported. Leveraging enhanced polarization originating from the dipole coupling of CIPS and α-In₂ Se₃ , the fabricated Fe-FET exhibits a large memory window of 14.5 V at V_GS = ±10 V, reaching a memory window to sweep range of ≈72%. Piezoelectric force microscopy measurements confirm the enhanced polarization-induced wider hysteresis loop of the double-stacked ferroelectrics compared to single ferroelectric layers. The Landau-Khalatnikov theory is extended to analyze the ferroelectric characteristics of a ferroelectric heterostructure, providing detailed explanations of the hysteresis behaviors and enhanced memory window formation. The fabricated Fe-FET shows nonvolatile memory characteristics, with a high on/off current ratio of over 10⁶ , long retention time (>10⁴ s), and stable cyclic endurance (>10⁴ cycles). Furthermore, the applicability of the ferroelectrics heterostructure is investigated for artificial synapses and for hardware neural networks through training and inference simulation. These results provide a promising pathway for exploring low-dimensional ferroelectronics.

Nonvolatile Ferroelectric Memory with Lateral β/α/β In2Se3 Heterojunctions

The electric dipole locking effect observed in van der Waals (vdW) ferroelectric α-In₂Se₃ has resulted in a surge of applied research in electronics with nonvolatile functionality. However, ferroelectric tunnel junctions with advantages of lower power consumption and faster writing/reading operations have not been realized in α-In₂Se₃. Here, we demonstrate the tunneling electroresistance effect in a lateral β/α/β In₂Se₃ heterojunction built by local laser irradiation. Switchable in-plane polarizations of the vdW ferroelectric control the tunneling conductance of the heterojunction device by 4000% of magnitude. The electronic logic bit can be represented and stored with different orientations of electric dipoles. This prototype enables a new approach to rewritable nonvolatile memory with in-plane ferroelectricity in vdW 2D materials.

Stretchable Temperature-Responsive Multimodal Neuromorphic Electronic Skin with Spontaneous Synaptic Plasticity Recovery

Multimodal electronic skin devices capable of detecting multimodal signals provide the possibility for health monitoring. Sensing and memory for temperature and deformation by human skin are of great significance for the perception and monitoring of physiological changes of the human body. Electronic skin is highly expected to have similar functions as human skin. Here, by implementing intrinsically stretchable neuromorphic transistors with mechanoreceptors and thermoreceptors in an array, we have realized stretchable temperature-responsive multimodal neuromorphic electronic skin (STRM-NES) with both sensory and memory functions, in which synaptic plasticity can be modulated by multiple modalities, in situ temperature variations, and stretching deformations. Temperature-responsive functions, spontaneous recovery, and temperature-dependent multitrial learning are proposed. Furthermore, a stretchable temperature neuromorphic array composed of multiple fully functional subcells is demonstrated to identify temperature distributions and variations at different regions and conditions after various strains of skin. The STRM-NES has temperature- and strain-responsive neuromorphic functions, excellent self-healing, and reusable capability, showing similar abilities as human skin to sense, transmit, memory, and recovery from external stimuli. It is expected to facilitate the development of wearable electronics, intelligent robotics, and prosthetic applications.

High-TC Two-Dimensional Ferroelectric CuCrS2 Grown via Chemical Vapor Deposition

Two-dimensional (2D) ferroelectrics have attracted intensive attention. However, the 2D ferroelectrics remain rare, and especially few of them represent high ferroelectric transition temperature (T_C), which is important for the usability of ferroelectrics. Herein, CuCrS₂ nanoflakes are synthesized by salt-assisted chemical vapor deposition and exhibit switchable ferroelectric polarization even when the thickness is downscaled to 6 nm. On the contrary, a CuCrS₂ nanoflake shows a T_C as high as ∼700 K, which can be attributed to the robust tetrahedral bonding configurations of Cu cations. Such robustness can be further clarified by a theoretically predicted high order-disorder transition barrier and structure evolution from 600 to 800 K. Additionally, the interlocked out-of-plane (OOP) and in-plane (IP) ferroelectric domains are observed and two kinds of devices based on OOP and IP polarizations are demonstrated.

Large-Scale Domain Engineering in Two-Dimensional Ferroelectric CuInP2S6 via Giant Flexoelectric Effect

Room-temperature ferroelectricity in two-dimensional (2D) materials is a potential for developing atomic-scale functional devices. However, as a key step for the technology implementations of 2D ferroelectrics in electronics, the controllable generation of uniform domains remains challenging at the current stage because domain engineering through an external electric field at the 2D limit inevitably leads to large leakage currents and material breakdown. Here, we demonstrate a voltage-free method, the flexoelectric effect, to artificially generate large-scale stripe domains in 2D ferroelectric CuInP₂S₆ with single domain lateral size at the scale of several hundred microns. With giant strain gradients (∼10⁶ m^-1), we mechanically switch the out-of-plane polarization in ultrathin CuInP₂S₆. The flexoelectric control of polarization is understood with a distorted Landau-Ginzburg-Devonshire double well model. Through substrate strain engineering, the stripe domain density is controllable. Our results highlight the potential of developing van der Waals ferroelectrics-based flexible electronics.

Two-Dimensional CIPS-InSe van der Waal Heterostructure Ferroelectric Field Effect Transistor for Nonvolatile Memory Applications

Channel current conduction modulation with the spontaneous polarization of ferroelectric films in ferroelectric field-effect transistors (FeFETs) has been widely investigated. Low interface quality and thermodynamic instability owing to the presence of dangling bonds in the conventional ferroelectrics have limited the memory retention and endurance of FeFETs. This, in turn, prevents their commercialization. However, the atomically thin nature of 2D ferroelectric, semiconducting, and insulating films facilitate the achievement of trap-free interfaces as van der Waal heterostructures (vdWHs) to develop FeFETs with long data retention and endurance characteristics. Here, we demonstrate a 2D vdWH FeFET fabricated with ferroelectric CuInP₂S₆ (CIPS), hexagonal boron nitride (h-BN) as the dielectric, and InSe as the ferroelectric semiconductor channel. The device shows an excellent performance as nonvolatile memory (NVM) with its large memory window (4.6 V at a voltage sweep of 5 V), high drain current on/off ratio (>10⁴), high endurance, and long data retention (>10⁴ s). These results demonstrate the considerable potential of vdWHs for the development of FeFETs for logic and NVM applications.

Filament Engineering of Two-Dimensional h-BN for a Self-Power Mechano-Nociceptor System

The switching variability caused by intrinsic stochasticity of the ionic/atomic motions during the conductive filaments (CFs) formation process largely limits the applications of diffusive memristors (DMs), including artificial neurons, neuromorphic computing and artificial sensory systems. In this study, a DM device with improved device uniformity based on well-crystallized two-dimensional (2D) h-BN, which can restrict the CFs formation from three to two dimensions due to the high migration barrier of Ag⁺ between h-BN interlayer, is developed. The BN-DM has potential arrayable feature with high device yield of 88%, which can be applied for building a reservoir computing system for digital pattern recognition with high accuracy rate of 96%, and used as an artificial nociceptor to sense the external noxious stimuli and mimic the important biological nociceptor properties. By connecting the BN-DM to a self-made triboelectric nanogenerator (TENG), a self-power mechano-nociceptor system, which can successfully mimic the important nociceptor features of "threshold", "relaxation" and "allodynia" is designed.

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.

Discovery of Robust Ferroelectricity in 2D Defective Semiconductor α-Ga2 Se3

2D ferroelectrics with robust polar order in the atomic-scale thickness at room temperature are needed to miniaturize ferroelectric devices and tackle challenges imposed by traditional ferroelectrics. These materials usually have polar point group structure regarding as a prerequisite of ferroelectricity. Yet, to introduce polar structure into otherwise nonpolar 2D materials for producing ferroelectricity remains a challenge. Here, by combining first-principles calculations and experimental studies, it is reported that the native Ga vacancy-defects located in the asymmetrical sites in cubic defective semiconductor α-Ga₂ Se₃ can induce polar structure. Meanwhile, the induced polarization can be switched in a moderate energy barrier. The switched polarization is observed in 2D α-Ga₂ Se₃ nanoflakes of ≈4 nm with a high switching temperature up to 450 K. Such polarization switching could arise from the displacement of Ga vacancy between neighboring asymmetrical sites by applying an electric field. This work removes the point group limit for ferroelectricity, expanding the range of 2D ferroelectrics into the native defective semiconductors.

All-in-one two-dimensional retinomorphic hardware device for motion detection and recognition

With the advent of the Internet of Things era, the detection and recognition of moving objects is becoming increasingly important¹. The current motion detection and recognition (MDR) technology based on the complementary metal oxide semiconductor (CMOS) image sensors (CIS) platform contains redundant sensing, transmission conversion, processing and memory modules, rendering the existing systems bulky and inefficient in comparison to the human retina. Until now, non-memory capable vision sensors have only been used for static targets, rather than MDR. Here, we present a retina-inspired two-dimensional (2D) heterostructure based retinomorphic hardware device with all-in-one perception, memory and computing capabilities for the detection and recognition of moving trolleys. The proposed 2D retinomorphic device senses an optical stimulus to generate progressively tuneable positive/negative photoresponses and memorizes it, combined with interframe differencing computations, to achieve 100% separation detection of moving trichromatic trolleys without ghosting. The detected motion images are fed into a conductance mapped neural network to achieve fast trolley recognition in as few as four training epochs at 10% noise level, outperforming previous results from similar customized datasets. The prototype demonstration of a 2D retinomorphic device with integrated perceptual memory and computation provides the possibility of building compact, efficient MDR hardware.

Phase-Tunable Synthesis and Etching-Free Transfer of Two-Dimensional Magnetic FeTe

Two-dimensional (2D) Fe-chalcogenides (e.g., FeS, FeSe, and FeTe, etc.) have sparked extensive interest due to their rich phase diagrams including superconductivity, magnetism, and topological state, as well as versatile applications in electronic devices and energy related fields. However, the phase-tunable synthesis and green transfer of such fascinating materials still remain challenging. Herein, we develop a temperature-mediated chemical vapor deposition (CVD) approach to grow ultrathin nonlayered hexagonal and layered tetragonal FeTe nanosheets on mica substrates, with their thicknesses down to ∼2.3 and ∼4.0 nm, respectively. Interestingly, we have observed exciting ferromagnetism with the Curie temperature approaching ∼300 K and high conductivity (∼1.96 × 10⁵ S m^-1) in 2D hexagonal FeTe. More significantly, we have designed a swift, high-efficiency, and etching-free method for the transfer of 2D FeTe nanosheets onto arbitrary substrates, and such a transfer strategy enables the cyclic utilization of growth substrates. These results should propel the further development of phase-tunable synthesis and green transfer of 2D Fe-chalcogenides, as well as their potential applications in spintronic devices.

Activating Silent Synapses in Sulfurized Indium Selenide for Neuromorphic Computing

The transformation from silent to functional synapses is accompanied by the evolutionary process of human brain development and is essential to hardware implementation of the evolutionary artificial neural network but remains a challenge for mimicking silent to functional synapse activation. Here, we developed a simple approach to successfully realize activation of silent to functional synapses by controlled sulfurization of chemical vapor deposition-grown indium selenide crystals. The underlying mechanism is attributed to the migration of sulfur anions introduced by sulfurization. One of our most important findings is that the functional synaptic behaviors can be modulated by the degree of sulfurization and temperature. In addition, the essential synaptic behaviors including potentiation/depression, paired-pulse facilitation, and spike-rate-dependent plasticity are successfully implemented in the partially sulfurized functional synaptic device. The developed simple approach of introducing sulfur anions in layered selenide opens an effective new avenue to realize activation of silent synapses for application in evolutionary artificial neural networks.

Logic and in-memory computing achieved in a single ferroelectric semiconductor transistor

Exploring materials with multiple properties who can endow a simple device with integrated functionalities has attracted enormous attention in the microelectronic field. One reason is the imperious demand for processors with continuously higher performance and totally new architecture. Combining ferroelectric with semiconducting properties is a promising solution. Here, we show that logic, in-memory computing, and optoelectrical logic and non-volatile computing functionalities can be integrated into a single transistor with ferroelectric semiconducting α-In₂Se₃ as the channel. Two-input AND, OR, and non-volatile NOR and NAND logic operations with current on/off ratios reaching up to five orders, good endurance (1000 operation cycles), and fast operating speed (10 μs) are realized. In addition, optoelectrical OR logic and non-volatile implication (IMP) operations, as well as ternary-input optoelectrical logic and in-memory computing functions are achieved by introducing light as an additional input signal. Our work highlights the potential of integrating complex logic functions and new-type computing into a simple device based on emerging ferroelectric semiconductors.

An Optogenetics-Inspired Flexible van der Waals Optoelectronic Synapse and its Application to a Convolutional Neural Network

Optogenetics refers to a technique that uses light to modulate neuronal activity with a high spatiotemporal resolution, which enables the manipulation of learning and memory functions in the human brain. This strategy of controlling neuronal activity using light can be applied for the development of intelligent systems, including neuromorphic and in-memory computing systems. Herein, a flexible van der Waals (vdW) optoelectronic synapse is reported, which is a core component of optogenetics-inspired intelligent systems. This synapse is fabricated on 2D vdW layered rhenium disulfide (ReS₂ ) that features an inherent photosensitive memory nature derived from the persistent photoconductivity (PPC) effect, successfully mimicking the dynamics of biological synapses. Based on first-principles calculations, the PPC effect is identified to originate from sulfur vacancies in ReS₂ that have an inherent tendency to form shallow defect states near the conduction band edges and under optical excitation lead to large lattice relaxation. Finally, the feasibility of applying the synapses in optogenetics-inspired intelligent systems is demonstrated via training and inference tasks for the CIFAR-10 dataset using a convolutional neural network composed of vdW optoelectronic synapse devices.

2D materials-based homogeneous transistor-memory architecture for neuromorphic hardware

[Figure: see text].

Ambipolar Charge Storage in Type-I Core/Shell Semiconductor Quantum Dots toward Optoelectronic Transistor-Based Memories

Efficient charge storage media play a pivotal role in transistor-based memories and thus are under intense research. In this work, the charge storage ability of type-I InP/ZnS core/shell quantum dots is well revealed through studying a pentacene-based organic transistor with the quantum dots (QDs) integrated. The quantum well-like energy band structure enables the QDs to directly confine either holes or electrons in the core, signifying a dielectric layer-free nonvolatile memory. Especially, the QDs in this device can be charged by electrons using light illumination as the exclusive method. The electron charging process is ascribed to the photoexcitation process in the InP-core and the hot holes induced. The QDs layer demonstrates an electron storage density of ≈5.0 × 1011  cm-2 and a hole storage density of ≈6.4 × 1011  cm-2 . Resultingly, the output device shows a fast response speed to gate voltage (10 µs), large memory window (42 V), good retention (>4.0 × 104 s), and reliable endurance. This work suggests that the core/shell quantum dot as a kind of charge storage medium is of great promise for optoelectronic memories.

Two-dimensional ferroelasticity in van der Waals β'-In2Se3

Two-dimensional (2D) materials exhibit remarkable mechanical properties, enabling their applications as flexible and stretchable ultrathin devices. As the origin of several extraordinary mechanical behaviors, ferroelasticity has also been predicted theoretically in 2D materials, but so far lacks experimental validation and investigation. Here, we present the experimental demonstration of 2D ferroelasticity in both exfoliated and chemical-vapor-deposited β'-In₂Se₃ down to few-layer thickness. We identify quantitatively 2D spontaneous strain originating from in-plane antiferroelectric distortion, using both atomic-resolution electron microscopy and in situ X-ray diffraction. The symmetry-equivalent strain orientations give rise to three domain variants separated by 60° and 120° domain walls (DWs). Mechanical switching between these ferroelastic domains is achieved under ≤0.5% external strain, demonstrating the feasibility to tailor the antiferroelectric polar structure as well as DW patterns through mechanical stimuli. The detailed domain switching mechanism through both DW propagation and domain nucleation is unraveled, and the effects of 3D stacking on such 2D ferroelasticity are also discussed. The observed 2D ferroelasticity here should be widely available in 2D materials with anisotropic lattice distortion, including the 1T' transition metal dichalcogenides with Peierls distortion and 2D ferroelectrics such as the SnTe family, rendering tantalizing potential to tune 2D functionalities through strain or DW engineering.