Ferroelectric Field-Effect-Transistor Integrated with Ferroelectrics Heterostructure

Low-Temperature Nanosecond Laser Process of HZO-IGZO FeFETs toward Monolithic 3D System on Chip Integration

Ferroelectric field-effect transistors (FeFETs) are increasingly important for in-memory computing and monolithic 3D (M3D) integration in system-on-chip (SoC) applications. However, the high-temperature processing required by most ferroelectric memories can lead to thermal damage to the underlying device layers, which poses significant physical limitations for 3D integration processes. To solve this problem, the study proposes using a nanosecond pulsed laser for selective annealing of hafnia-based FeFETs, enabling precise control of heat penetration depth within thin films. Sufficient thermal energy is delivered to the IGZO oxide channel and HZO ferroelectric gate oxide without causing thermal damage to the bottom layer, which has a low transition temperature (<250 °C). Using optimized laser conditions, a fast response time (<1 µs) and excellent stability (cycle > 106, retention > 106 s) are achieved in the ferroelectric HZO film. The resulting FeFET exhibited a wide memory window (>1.7 V) with a high on/off ratio (>105). In addition, moderate ferroelectric properties (2·Pr of 14.7 µC cm-2) and pattern recognition rate-based linearity (potentiation: 1.13, depression: 1.6) are obtained. These results demonstrate compatibility in HZO FeFETs by specific laser annealing control and thin-film layer design for various structures (3D integrated, flexible) with neuromorphic applications.

Intercorrelated Ferroelectricity and Bulk Photovoltaic Effect in Two-Dimensional Sn2P2S6 Semiconductor for Polarization-Sensitive Photodetection

A two-dimensional (2D) ferroelectric semiconductor, which is coupled with photosensitivity and room-temperature ferroelectricity, provides the possibility of coordinated conductance modulation by both electric field and light illumination and is promising for triggering the revolution of optoelectronics for monolithic multifunctional integration. Here, we report that semiconducting Sn2P2S6 crystals can be achieved in a 2D morphology using a chemical vapor transport approach with the assistant of space confinement and experimentally demonstrate the robust ferroelectricity in atomic-thin Sn2P2S6 nanosheet at room temperature. The intercorrelated programming of ferroelectric order along out-of-plane (OOP) and in-plane (IP) directions enables a tunable bulk photovoltaic (BPV) effect through multidirectional electrical control. By combining the capability of anisotropic in-plane optical absorption, a highly integrated Sn2P2S6 optoelectronic device vertically sandwiched with graphene electrodes yields the polarization-dependent open-circuit photovoltage with a dichroic ratio of 2.0 under 405 nm light illumination. The reintroduction of ferroelectric Sn2P2S6 to the 2D asymmetric semiconductor family provides possibilities to hardware implement of the self-powered polarization-sensitive photodetection and spotlights the promising applications for next-generation photovoltaic devices.

Two-Terminal Perovskite Optoelectronic Synapse for Rapid Trained Neuromorphic Computation with High Accuracy

Emerging neural morphological vision sensors inspired by biological systems that integrate image perception, memory, and information computing are expected to transform the landscape of machine vision and artificial intelligence. However, stable and reconfigurable light-induced synaptic behavior always relies on independent gateport modulation. Despite its potential, the limitations of uncontrollable defects and ionic characteristics have led to simpler, smaller, and more integration-friendly two-terminal devices being used as sidelines. In this work, the synergy between ion migration barriers and readout voltage is proven to be the key to realizing stable, reconfigurable, and precisely controllable postsynaptic current in two-terminal devices. Following the same mechanism, optical and electrical signal synchronous triggering is proposed to serve as a preprocessing method to achieve a recognition accuracy of 96.5%. Impressively, the gradual ion accumulation during the training process induces photocurrent evolution, serving as a reference for the dynamic learning rate and boosting accuracy to 97.8% in just 10 epochs. The PSC modulation potential under short optical pulse of 20 ns is also revealed. This optoelectronic device with perception, memory, and computation capabilities can promote the development of new devices for future photonic neural morphological circuits and artificial vision.

Realization of sextuple polarization states and interstate switching in antiferroelectric CuInP2S6

Realization of higher-order multistates with mutual interstate switching in ferroelectric materials is a perpetual drive for high-density storage devices and beyond-Moore technologies. Here we demonstrate experimentally that antiferroelectric van der Waals CuInP2S6 films can be controllably stabilized into double, quadruple, and sextuple polarization states, and a system harboring polarization order of six is also reversibly tunable into order of four or two. Furthermore, for a given polarization order, mutual interstate switching can be achieved via moderate electric field modulation. First-principles studies of CuInP2S6 multilayers help to reveal that the double, quadruple, and sextuple states are attributable to the existence of respective single, double, and triple ferroelectric domains with antiferroelectric interdomain coupling and Cu ion migration. These findings offer appealing platforms for developing multistate ferroelectric devices, while the underlining mechanism is transformative to other non-volatile material systems.

Tandem Synergistic Effect of Cu-In Dual Sites Confined on the Edge of Monolayer CuInP2 S6 toward Selective Photoreduction of CO2 into Multi-Carbon Solar Fuels

One-unit-cell, single-crystal, hexagonal CuInP2 S6 atomically thin sheets of≈0.81 nm in thickness was successfully synthesized for photocatalytic reduction of CO2 . Exciting ethene (C2 H4 ) as the main product was dominantly generated with the yield-based selectivity reaching ≈56.4 %, and the electron-based selectivity as high as ≈74.6 %. The tandem synergistic effect of charge-enriched Cu-In dual sites confined on the lateral edge of the CuInP2 S6 monolayer (ML) is mainly responsible for efficient conversion and high selectivity of the C2 H4 product as the basal surface site of the ML, exposing S atoms, can not derive the CO2 photoreduction due to the high energy barrier for the proton-coupled electron transfer of CO2 into *COOH. The marginal In site of the ML preeminently targets CO2 conversion to *CO under light illumination, and the *CO then migrates to the neighbor Cu sites for the subsequent C-C coupling reaction into C2 H4 with thermodynamic and kinetic feasibility. Moreover, ultrathin structure of the ML also allows to shorten the transfer distance of charge carriers from the interior onto the surface, thus inhibiting electron-hole recombination and enabling more electrons to survive and accumulate on the exposed active sites for CO2 reduction.

Tuning the interface of MIMII(OH)F@MIMII1-xS (MⅠ: Ni, Co; MⅡ: Co, Fe) by atomic replacement strategy toward high performance overall water splitting

Constructing heterostructure is considered as one of the most promising strategies to reveal high efficiency hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) performance. Nevertheless, it is highly challenging to obtain stable interfaces and sufficient active sites via conventional method. In addition, Ni, Co and Fe elements share the valence electron structures of 3d6-84s2, the appropriate integration of these metals to induce synergistic effect in multicomponent electrocatalysts can enhance electrochemical activity. Herein, in this work, the MIMII(OH)F@MIMII1-xS (NiFe(OH)F@NiFe1-xS, NiCo(OH)F@NiCo1-xS, CoFe(OH)F@CoFe1-xS) autogenous heterostructure on nickel foam are constructed. As a result, NiFe(OH)F@NiFe1-xS-0.05, NiCo(OH)F@NiCo1-xS-0.05, and CoFe(OH)F@CoFe1-xS-0.05 demonstrate outstanding overpotential for HER (70 mV, 90 mV, 81 mV at -10 mA cm-2) and OER (370 mV, 470 mV, 370 mV at 10 mA cm-2) in alkaline electrolyte, while the overpotential for HER is 176 mV, 189 mV, 167 mV at -10 mA cm-2 and corresponding OER is 290 mV, 390 mV, 300 mV at 10 mA cm-2 in simulated seawater, respectively. In addition, the NiFe, NiCo, CoFe-based electrolyzer acquire favorable overall water splitting activity in alkaline (1.72 V, 1.87 V, 1.66 V) and simulated seawater (1.73 V, 1.75 V, 1.69 V) at 10 mA cm-2. Overall, the above results authenticate the feasibility of developing autogenous heterostructure electrocatalysts for providing hydrogen and oxygen in alkaline and simulated seawater.

Integrated In-Memory Sensor and Computing of Artificial Vision Based on Full-vdW Optoelectronic Ferroelectric Field-Effect Transistor

The development and application of artificial intelligence have led to the exploitation of low-power and compact intelligent information-processing systems integrated with sensing, memory, and neuromorphic computing functions. The 2D van der Waals (vdW) materials with abundant reservoirs for arbitrary stacking based on functions and enabling continued device downscaling offer an attractive alternative for continuously promoting artificial intelligence. In this study, full 2D SnS2 /h-BN/CuInP2 S6 (CIPS)-based ferroelectric field-effect transistors (Fe-FETs) and utilized light-induced ferroelectric polarization reversal to achieve excellent memory properties and multi-functional sensing-memory-computing vision simulations are designed. The device exhibits a high on/off current ratio of over 105 , long retention time (>104  s), stable cyclic endurance (>350 cycles), and 128 multilevel current states (7-bit). In addition, fundamental synaptic plasticity characteristics are emulated including paired-pulse facilitation (PPF), short-term plasticity (STP), long-term plasticity (LTP), long-term potentiation, and long-term depression. A ferroelectric optoelectronic reservoir computing system for the Modified National Institute of Standards and Technology (MNIST) handwritten digital recognition achieved a high accuracy of 93.62%. Furthermore, retina-like light adaptation and Pavlovian conditioning are successfully mimicked. These results provide a strategy for developing a multilevel memory and novel neuromorphic vision systems with integrated sensing-memory-processing.

Large-Area Growth of Ferroelectric 2D γ-In2 Se3 Semiconductor by Spray Pyrolysis for Next-Generation Memory

In2 Se3 , 2D ferroelectric-semiconductor, is a promising candidate for next-generation memory device because of its outstanding electrical properties. However, the large-area manufacturing of In2 Se3 is still a big challenge. In this work, spray pyrolysis technique is introduced for the growth of large-area In2 Se3 thin film. A polycrystalline γ-In2 Se3 layer can be grown on 15 cm × 15 cm glasss at the substrate temperature of 275 °C. The In2 Se3 ferroelectric-semiconductor field effect transistor (FeS-FET) on glass substrate demonstrates a large hysteresis window of 40.3 V at the ±40 V of gate voltage sweep and excellent uniformity. The FeS-FET exhibits an electron field effect mobility of 0.97 cm2 V-1 s-1 and an on/off current ratio of >107 in the transfer curves. The memory behavior of the large-area, In2 Se3 FeS-FETs for next-generation memory is demonstrated.

Controllable Electrocatalytic to Photocatalytic Conversion in Ferroelectric Heterostructures

Photocatalytic and electrocatalytic reactions to produce value-added chemicals offer promising solutions for addressing the energy crisis and environmental pollution. Photocatalysis is driven by light excitation and charge separation and relies on semiconducting catalysts, while electrocatalysis is driven by external electric current and is mostly based on metallic catalysts with high electrical conductivity. Due to the distinct reaction mechanism, the conversion between the two catalytic types has remained largely unexplored. Herein, by means of density functional theory (DFT) simulations, we demonstrated that the ferroelectric heterostructures Mo-BN@In2Se3 and WSe2@In2Se3 can exhibit semiconducting or metallic features depending on the polarization direction as a result of the built-in field and electron transfer. Using the nitrogen reduction reaction (NRR) and hydrogen evolution reaction (HER) as examples, the metallic heterostructures act as excellent electrocatalysts for these reactions, while the semiconducting heterostructures serve as the corresponding photocatalysts with improved optical absorption, enhanced charge separation, and low Gibbs free energy change. The findings not only bridge physical phenomena of the electronic phase transition with chemical reactions but also offer a new and feasible approach to significantly improve the catalytic efficiency.

Reconfigurable Neuromorphic Computing: Materials, Devices, and Integration

Neuromorphic computing has been attracting ever-increasing attention due to superior energy efficiency, with great promise to promote the next wave of artificial general intelligence in the post-Moore era. Current approaches are, however, broadly designed for stationary and unitary assignments, thus encountering reluctant interconnections, power consumption, and data-intensive computing in that domain. Reconfigurable neuromorphic computing, an on-demand paradigm inspired by the inherent programmability of brain, can maximally reallocate finite resources to perform the proliferation of reproducibly brain-inspired functions, highlighting a disruptive framework for bridging the gap between different primitives. Although relevant research has flourished in diverse materials and devices with novel mechanisms and architectures, a precise overview remains blank and urgently desirable. Herein, the recent strides along this pursuit are systematically reviewed from material, device, and integration perspectives. At the material and device level, one comprehensively conclude the dominant mechanisms for reconfigurability, categorized into ion migration, carrier migration, phase transition, spintronics, and photonics. Integration-level developments for reconfigurable neuromorphic computing are also exhibited. Finally, a perspective on the future challenges for reconfigurable neuromorphic computing is discussed, definitely expanding its horizon for scientific communities.

Artificial Visual Systems Fabricated with Ferroelectric van der Waals Heterostructure for In-Memory Computing Applications

Rapid developments in artificial neural network techniques and retina-inspired artificial visual systems are required to realize the sensing, processing, and memorization of an optical signal in a single device. Herein, a ferroelectric field-effect transistor fabricated with CuInP2S6 and α-In2Se3 van der Waals heterostructures is proposed and demonstrated for the development of an artificial visual system. The dipole polarizations are coupled and bidirectionally locked inside the ferroelectric α-In2Se3 along the in-plane and out-of-plane directions and are controlled by the gate voltages. Furthermore, light-induced polarization can change the order of polarization of the dipoles inside α-In2Se3. We demonstrate that using the combined control of these electrical and optical signals, the device may function like a retina-inspired vision system. The device can operate across a wide wavelength range (405-850 nm) and detect very low incident light (0.03 mW/cm2). Color recognition, high paired-pulse facilitation (∼170%), and short- to long-term memory transitions through quick learning are observed using this device. Additionally, this device demonstrates different complex processing abilities, including pattern recognition, light adaptation, optical logic operation, and event learning. The proposed ferroelectric heterostructure-based artificial visual system can serve as an essential bridge for fulfilling the future requirements of all-in-one sensing and memory-processing devices.

High-Speed Optoelectronic Nonvolatile Memory Based on van der Waals Heterostructures

High-performance optoelectronic nonvolatile memory is promising candidate for next-generation information memory devices. Here, a floating-gate memory is constructed based on van der Waals heterostructure, which exhibits a large storage window ratio (≈75.5%) and an extremely high on/off ratio (107 ), as well as an ultrafast electrical writing/erasing speed (40 ns). The enhanced performance enables as-fabricated devices to present excellent multilevel data storage, robust retention, and endurance performance. Moreover, stable optical erasing operations can be achieved by illuminating the device with a laser pulse, showcasing outstanding optoelectronic storage performance (optical erasing speed ≈ 2.3 ms). The nonvolatile and high-speed characteristics of these devices hold significant potential for the integration of high-performance nonvolatile memory.

Polarization-tunable interfacial properties in monolayer-MoS2 transistors integrated with ferroelectric BiAlO3(0001) polar surfaces

With the explosion of data-centric applications, new in-memory computing technologies, based on nonvolatile memory devices, have become competitive due to their merged logic-memory functionalities. Herein, employing first-principles quantum transport simulation, we theoretically investigate for the first time the electronic and contact properties of two types of monolayer (ML)-MoS2 ferroelectric field-effect transistors (FeFETs) integrated with ferroelectric BiAlO3(0001) (BAO(0001)) polar surfaces. Our study finds that the interfacial properties of the investigated partial FeFET devices are highly tunable by switching the electric polarization of the ferroelectric BAO(0001) dielectric. Specifically, the transition from quasi-Ohmic to the Schottky contact, as well as opposite contact polarity of respective n-type and p-type Schottky contact under two polarization states can be obtained, suggesting their superior performance metrics in terms of nonvolatile information storage. In addition, due to the feature of (quasi-)Ohmic contact in some polarization states, the explored FeFET devices, even when operating in the regular field-effect transistor (FET) mode, can be extremely significant in realizing a desirable low threshold voltage and interfacial contact resistance. In conjunction with the formed van der Waals (vdW) interfaces in ML-MoS2/ferroelectric systems with an interlayer, the proposed FeFETs are expected to provide excellent device performance with regard to cycling endurance and memory density.

2D Ferroic Materials for Nonvolatile Memory Applications

The emerging nonvolatile memory technologies based on ferroic materials are promising for producing high-speed, low-power, and high-density memory in the field of integrated circuits. Long-range ferroic orders observed in 2D materials have triggered extensive research interest in 2D magnets, 2D ferroelectrics, 2D multiferroics, and their device applications. Devices based on 2D ferroic materials and heterostructures with an atomically smooth interface and ultrathin thickness have exhibited impressive properties and significant potential for developing advanced nonvolatile memory. In this context, a systematic review of emergent 2D ferroic materials is conducted here, emphasizing their recent research on nonvolatile memory applications, with a view to proposing brighter prospects for 2D magnetic materials, 2D ferroelectric materials, 2D multiferroic materials, and their relevant devices.

Van der Waals Ferroelectrics: Theories, Materials, and Device Applications

In recent years, an increasing number of 2D van der Waals (vdW) materials are theory-predicted or laboratory-validated to possess in-plane (IP) and/or out-of-plane (OOP) spontaneous ferroelectric polarization. Due to their dangling-bond-free surfaces, interlayer charge coupling, robust polarization, tunable energy band structures, and compatibility with silicon-based technologies, vdW ferroelectric materials exhibit great promise in ferroelectric memories, neuromorphic computing, nanogenerators, photovoltaic devices, spintronic devices, and so on. Here, the very recent advances in the field of vdW ferroelectrics (FEs) are reviewed. First, theories of ferroelectricity are briefly discussed. Then, a comprehensive summary of the non-stacking vdW ferroelectric materials is provided based on their crystal structures and the emerging sliding ferroelectrics. In addition, their potential applications in various branches/frontier fields are enumerated, with a focus on artificial intelligence. Finally, the challenges and development prospects of vdW ferroelectrics are discussed.

Asymmetric two-dimensional ferroelectric transistor with anti-ambipolar transport characteristics

Two-dimensional (2D) ferroelectric transistors hold unique properties and positions, especially talking about low-power memories, in-memory computing, and multifunctional logic devices. To achieve better functions, appropriate design of new device structures and material combinations is necessary. We present an asymmetric 2D heterostructure integrating MoTe₂, h-BN, and CuInP₂S₆ as a ferroelectric transistor, which exhibits an unusual property of anti-ambipolar transport characteristic under both positive and negative drain biases. Our results demonstrate that the anti-ambipolar behavior can be modulated by external electric field, achieving a peak-to-valley ratio up to 10³. We also provide a comprehensive explanation for the occurrence and modulation of the anti-ambipolar peak based on a model describing linked lateral-and-vertical charge behaviors. Our findings provide insights for designing and constructing anti-ambipolar transistors and other 2D devices with significant potential for future applications.

Memristor-based neural networks: a bridge from device to artificial intelligence

Since the beginning of the 21st century, there is no doubt that the importance of artificial intelligence has been highlighted in many fields, among which the memristor-based artificial neural network technology is expected to break through the limitation of von Neumann so as to realize the replication of the human brain by enabling strong parallel computing ability and efficient data processing and become an important way towards the next generation of artificial intelligence. A new type of nanodevice, namely memristor, which is based on the variability of its resistance value, not only has very important applications in nonvolatile information storage, but also presents obsessive progressiveness in highly integrated circuits, making it one of the most promising circuit components in the post-Moore era. In particular, memristors can effectively simulate neural synapses and build neural networks; thus, they can be applied for the preparation of various artificial intelligence systems. This study reviews the research progress of memristors in artificial neural networks in detail and highlights the structural advantages and frontier applications of neural networks based on memristors. Finally, some urgent problems and challenges in current research are summarized and corresponding solutions and future development trends are put forward.

Robust Threshold-Switching Behavior Assisted by Cu Migration in a Ferroionic CuInP2S6 Heterostructure

The two-dimensional layered material CuInP₂S₆ (CIPS) has attracted significant research attention due to its nontrivial physical properties, including room-temperature ferroelectricity at the ultrathin limit and substantial ionic conductivity. Despite many efforts to control its ionic conductance and develop electronic devices, such as memristors, improving the stability of these devices remains a challenge. This work presents a highly stable threshold-switching device based on the Cu/CIPS/graphene heterostructure, achieved after a comprehensive investigation of the activation of Cu's ionic conductivity. The device exhibits exceptional threshold-switching performance, including good cycling endurance, a high on/off ratio of up to 10⁴, low operation voltages, and an ultrasmall subthreshold swing of less than 1.8 mV/decade for the resistance-switching process. Through temperature-dependent electrical and Raman spectroscopy measurements, the stable resistive-switching mechanism is interpreted with a drifting and diffusion model of Cu ions under the electric field, rather than the conventional conducting filament mechanism. These results make the layered ferroionic CIPS material a promising candidate for information storage devices, demonstrating a compelling approach to achieving high-performance threshold-switching memristor devices.

Environmentally Stable and Reconfigurable Ultralow-Power Two-Dimensional Tellurene Synaptic Transistor for Neuromorphic Edge Computing

While neuromorphic computing can define a new era for next-generation computing architecture, the introduction of an efficient synaptic transistor for neuromorphic edge computing still remains a challenge. Here, we envision an atomically thin 2D Te synaptic device capable of achieving a desirable neuromorphic edge computing design. The hydrothermally grown 2D Te nanosheet synaptic transistor apparently mimicked the biological synaptic nature, exhibiting 100 effective multilevel states, a low power consumption of ∼110 fJ, excellent linearity, and short-/long-term plasticity. Furthermore, the 2D Te synaptic device achieved reconfigurable MNIST recognition accuracy characteristics of 88.2%, even after harmful detergent environment infection. We believe that this work serves as a guide for developing futuristic neuromorphic edge computing.

Selective Enhancement of Photoresponse with Ferroelectric-Controlled BP/In2 Se3 vdW Heterojunction

Owing to the large built-in field for efficient charge separation, heterostructures facilitate the simultaneous realization of a low dark current and high photocurrent. The lack of an efficient approach to engineer the depletion region formed across the interfaces of heterojunctions owing to doping differences hinders the realization of high-performance van der Waals (vdW) photodetectors. This study proposes a ferroelectric-controlling van der Waals photodetector with vertically stacked two-dimensional (2D) black phosphorus (BP)/indium selenide (In₂ Se₃ ) to realize high-sensitivity photodetection. The depletion region can be reconstructed by tuning the polarization states generated from the ferroelectric In₂ Se₃ layers. Further, the energy bands at the heterojunction interfaces can be aligned and flexibly engineered using ferroelectric field control. Fast response, self-driven photodetection, and three-orders-of-magnitude detection improvements are achieved in the switchable visible or near-infrared operation bands. The results of the study are expected to aid in improving the photodetection performance of vdW optoelectronic devices.

Nonvolatile Electrical Control and Reversible Gas Capture by Ferroelectric Polarization Switching in 2D FeI2/In2S3 van der Waals Heterostructures

Nonvolatile electrical control is the core of future magnetoelectric nanodevices. In this work, we systematically explore both the electronic structures and transport properties of multiferroic van der Waals (vdW) heterostructures consisting of a ferromagnetic FeI₂ monolayer and a ferroelectric In₂S₃ monolayer using density functional theory and the nonequilibrium Green's function method. The results reveal that the FeI₂ monolayer can be reversibly switched between semiconducting and half-metallic properties by nonvolatile control of the In₂S₃ ferroelectric polarization states. Correspondingly, the proof-of-concept two-probe nanodevice based on the FeI₂/In₂S₃ vdW heterostructure exhibits a significant valving effect by modulating the ferroelectric switching. Moreover, it is also found that the preference of nitrogen-containing gases such as NH₃, NO, and NO₂ for adsorption on the surface of FeI₂/In₂S₃ vdW heterostructures strongly depends on the polarization direction of the ferroelectric layer. In particular, the FeI₂/In₂S₃ heterostructure shows reversible capture behavior for NH₃. As a result, the FeI₂/In₂S₃ vdW heterostructure-based gas sensor demonstrates high selectivity and sensitivity. These findings may open up a new route for the application of multiferroic heterostructures to spintronics, nonvolatile memories, and gas sensors.

Electrically Switchable Polarization in Bi2 O2 Se Ferroelectric Semiconductors

Atomically 2D layered ferroelectric semiconductors, in which the polarization switching process occurs within the channel material itself, offer a new material platform that can drive electronic components toward structural simplification and high-density integration. Here, a room-temperature 2D layered ferroelectric semiconductor, bismuth oxychalcogenides (Bi₂ O₂ Se), is investigated with a thickness down to 7.3 nm (≈12 layers) and piezoelectric coefficient (d₃₃ ) of 4.4 ± 0.1 pm V^-1 . The random orientations and electrically dependent polarization of the dipoles in Bi₂ O₂ Se are separately uncovered owing to the structural symmetry-breaking at room temperature. Specifically, the interplay between ferroelectricity and semiconducting characteristics of Bi₂ O₂ Se is explored on device-level operation, revealing the hysteresis behavior and memory window (MW) formation. Leveraging the ferroelectric polarization originating from Bi₂ O₂ Se, the fabricated device exhibits "smart" photoresponse tunability and excellent electronic characteristics, e.g., a high on/off current ratio > 10⁴ and a large MW to the sweeping range of 47% at V_GS  = ±5 V. These results demonstrate the synergistic combination of ferroelectricity with semiconducting characteristics in Bi₂ O₂ Se, laying the foundation for integrating sensing, logic, and memory functions into a single material system that can overcome the bottlenecks in von Neumann architecture.

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.