Artificial Synapse Emulated through Fully Aqueous Solution-Processed Low-Voltage In2O3 Thin-Film Transistor with Gd2O3 Solid Electrolyte

Oxide Ionic Neuro-Transistors for Bio-inspired Computing

Current computing systems rely on Boolean logic and von Neumann architecture, where computing cells are based on high-speed electron-conducting complementary metal-oxide-semiconductor (CMOS) transistors. In contrast, ions play an essential role in biological neural computing. Compared with CMOS units, the synapse/neuron computing speed is much lower, but the human brain performs much better in many tasks such as pattern recognition and decision-making. Recently, ionic dynamics in oxide electrolyte-gated transistors have attracted increasing attention in the field of neuromorphic computing, which is more similar to the computing modality in the biological brain. In this review article, we start with the introduction of some ionic processes in biological brain computing. Then, electrolyte-gated ionic transistors, especially oxide ionic transistors, are briefly introduced. Later, we review the state-of-the-art progress in oxide electrolyte-gated transistors for ionic neuromorphic computing including dynamic synaptic plasticity emulation, spatiotemporal information processing, and artificial sensory neuron function implementation. Finally, we will address the current challenges and offer recommendations along with potential research directions.

Solution-processed bilayer InGaZnO/In2O3thin film transistors at low temperature by lightwave annealing

At low temperatures about 230 °C, bilayer InGaZnO/In2O3thin film transistors (TFTs) were prepared by a solution process with lightwave annealing. The InGaZnO/In2O3bilayer TFTs with SiO2as dielectric layer show high electrical performances, such as a mobility of 7.63 cm2V-1s-1, a threshold voltage (Vth) of 3.8 V, and an on/off ratio higher than 107, which are superior to single-layer InGaZnO TFTs or In2O3TFTs. Moreover, bilayer InGaZnO/In2O3TFTs demonstrated a great bias stability enhancement due to the introduction of top InGaZnO film act as a passivation layer, which could prevent the interaction of ambient air with the bottom In2O3layer. By using high dielectric constant AlOxfilm, the InGaZnO/In2O3TFTs exhibit an improved mobility of 47.7 cm2V-1s-1. The excellent electrical performance of the solution-based InGaZnO/In2O3TFTs shows great application potential for low-cost flexible printed electronics.

Metal-Oxide Heterojunction: From Material Process to Neuromorphic Applications

As technologies like the Internet, artificial intelligence, and big data evolve at a rapid pace, computer architecture is transitioning from compute-intensive to memory-intensive. However, traditional von Neumann architectures encounter bottlenecks in addressing modern computational challenges. The emulation of the behaviors of a synapse at the device level by ionic/electronic devices has shown promising potential in future neural-inspired and compact artificial intelligence systems. To address these issues, this review thoroughly investigates the recent progress in metal-oxide heterostructures for neuromorphic applications. These heterostructures not only offer low power consumption and high stability but also possess optimized electrical characteristics via interface engineering. The paper first outlines various synthesis methods for metal oxides and then summarizes the neuromorphic devices using these materials and their heterostructures. More importantly, we review the emerging multifunctional applications, including neuromorphic vision, touch, and pain systems. Finally, we summarize the future prospects of neuromorphic devices with metal-oxide heterostructures and list the current challenges while offering potential solutions. This review provides insights into the design and construction of metal-oxide devices and their applications for neuromorphic systems.

Multifunctional Multigate One-Transistor with Thin Advanced Materials, Logic-in-Memory, and Artificial Synaptic Behaviors

The high device density and fabrication complexity have hampered the development of the electronics. The advanced designs, which could implement the functions of the circuits with higher device density but less fabrication complexity, are hence required. Meanwhile, the MoS2-based devices have recently attracted considerable attention owing to their advantages such as the ultrathin thickness. However, the MoS2-based multifunctional multigate one-transistor (MGT) designs with logic-in-memory and artificial synaptic functions have rarely been reported. Here, an MGT structure based on the MoS2 channel is proposed, with both the logic-in-memory and artificial synaptic behaviors and with more controllable processes than the manual transfer. The proposed MoS2-based MGT functions could be attributed to the semijunction mechanism and enhanced effect of the additional terminals with improved controllability. This study is the first to demonstrate that the neuromorphic computing, logic gate, and memory functions can all be achieved in a MoS2 MGT device without using any additional layers or plasticity to a transistor. The reported results provide a new strategy for developing brain-like systems and next-generation electronics using multifunctional designs and ultrathin materials.

Mimicking Pain-Perceptual Sensitization and Pattern Recognition Based on Capacitance- and Conductance-Regulated Neuroplasticity in Neural Network

Neuromorphic computing, inspired by the biological neuronal system, is a high potential approach to substantially alleviate the cost of computational latency and energy for massive data processing. Artificial synapses with regulable synaptic weights are the basis of neuromorphic computation, providing an efficient and low-power system to overcome the constraints of the von Neumann architecture. Here, we report an ITO/TaOx-based synaptic capacitor and transistor. With the drift motion of mobile-charged ions in the TaOx, the capacitance and channel conductance can be tuned to exhibit synaptic weight modulation. Robust stability in the cycle-to-cycle (C2C) variation is found in capacitance and conductance potentiation/depression weight updating of 0.9 and 1.8%, respectively. Simulation results show a higher classification accuracy of handwritten digit recognition (95%) in capacitance synapses than that in conductance synapses (84%). Besides, the synaptic capacitor consumes much less energy than the synaptic transistor. Moreover, the ITO/TaOx-based capacitor successfully emulates the pain-perceptual sensitization on top of the superior performance, indicating its promising potential in applying the capacitive neural network.

Recent Progress in Thin-Film Transistors toward Digital, Analog, and Functional Circuits

Thin-film transistors have been extensively developed due to their process merit: high compatibility with various substrates, large-area processes, and low-cost processes. Despite these advantages, most efforts for thin-film transistors still remain at the level of unit devices, so the circuit level for practical use needs to be further developed. In this regard, this review revisits digital and analog thin-film circuits using carbon nanotubes (CNTs), organic electrochemical transistors (OECTs), organic semiconductors, metal oxides, and two-dimensional materials. This review also discusses how to integrate thin-film circuits at the unit device level and some key issues such as metal routing and interconnection. Challenges and opportunities are also discussed to pave the way for developing thin-film circuits and their practical applications.

Sputtered Electrolyte-Gated Transistor with Temperature-Modulated Synaptic Plasticity Behaviors

Temperature has always been considered as an essential factor for almost all kinds of semiconductor-based electronic components. In this work, temperature-dependent synaptic plasticity behaviors, which are mimicked by the indium-gallium-zinc oxide thin-film transistors gated with sputtered SiO₂ electrolytes, have been studied. With the temperature increasing from 303 to 323 K, the electrolyte capacitance decreases from 0.42 to 0.11 μF cm^-2. The mobility increases from 1.4 to 3.7 cm² V^-1 s^-1, and the threshold voltage negatively shifts from -0.23 to -0.51 V. Synaptic behaviors under both a single pulse and multiple pulses are employed to study the temperature dependence. With the temperature increasing from 303 to 323 K, the post-synaptic current (PSC) at the resting state increases from 1.8 to 7.3 μA. Under a single gate pulse of 1 V and 1 s, the PSC signal altitude and the PSC retention time decrease from 2.0 to 0.7 μA and 5.1 × 10² to 2.5 ms, respectively. A physical model based on the electric field-induced ion drifting, ionic-electronic coupling, and gradient-coordinated ion diffusion is proposed to understand these temperature-dependent synaptic behaviors. Based on the experimental data on individual transistors, temperature-modulated pattern learning and memorizing behaviors are conceptually demonstrated. The in-depth investigation of the temperature dependence helps pave the way for further electrolyte-gated transistor-based neuromorphic applications.

Artificial Synapses Based on WSe2 Homojunction via Vacancy Migration

Artificial synapses based on two-dimensional (2D) transition metal dichalcogenides (TMDs) materials have attracted wide attention to boost the development of neuromorphic computing in recent years. Various structures have been adopted to build 2D-material-based artificial synapses. In lateral- and vertical-structures, the realization of synaptic function mainly results from the migration of the defects and vacancies, which requires the strong ion diffusion ability. Here, we successfully demonstrate an artificial synapse based on lateral WSe₂ homojunction. The migration of Se vacancies from the thin region to the thick region has been promoted by applying negative gate voltage, resulting in n-type doping in the thick region due to the accumulation of Se vacancies, which would diminish the barrier width of the metal-semiconductor junctions in the thick region. Consequently, the transformation from a high-resistance state (HRS) to a low-resistance state (LRS) is achieved. Significantly, our device can efficiently emulate the biological synaptic functions with a large synaptic weight change. Additionally, the transition from short-term memory (STM) to long-term memory (LTM) can be accomplished with a simpler structure, which would be beneficial to realizing the large-scale integration of transistor-based artificial synapses.

Engineering Bilayer AlOx /YAlOx Dielectric Stacks for Hysteresis-Free Switching in Solution-Processed Metal-Oxide Thin-Film Transistors

Solution processing and low-temperature annealing (T < 300°C) of the precursor compounds promise low-cost manufacturing for future applications of flexible oxide electronics. However, thermal budget reduction comes at the expense of increased charge trapping residuals in the dielectric layers, which result in hysteretic switching of transistors. This work reports on a novel bilayer dielectric scheme combining aluminum oxide (AlOx) as a positive charge trapping insulator and yttrium aluminum oxide (YAlOx) as a negative charge trapping dielectric to obtain hysteresis free switching in the solution-processed metal-oxide thin-film transistors. Devices were processed at a thermal budget of 250°C, without an encapsulation layer. The presence of H+ and OH− in the AlOx were found responsible for the hysteresis in the switching, which was suppressed successfully with the thickness optimization of the YAlOx in the dielectric stack. Fabricated devices yield ON/OFF ratios of 106, sub-pA level gate leakage currents, a subthreshold swing of 150 mV/decade, and field-effect mobility of 1.5 cm2/V-sec.

Asymmetric carrier transport in flexible interface-type memristor enables artificial synapses with sub-femtojoule energy consumption

Flexible and transparent artificial synapses with extremely low energy consumption have potential for use in brain-like neuromorphic electronics. However, most of the transparent materials for flexible memristive artificial synapses were reported to show picojoule-scale high energy consumption with kiloohm-scale low resistance, which limits the scalability for parallel operation. Here, we report on a flexible memristive artificial synapse based on Cs₃Cu₂I₅ with energy consumption as low as 10.48 aJ (= 10.48 × 10^-18 J) μm^-2 and resistance as high as 243 MΩ for writing pulses. Interface-type resistive switching at the Schottky junction between p-type Cu₃Cs₂I₅ and Au is verified, where migration of iodide vacancies and asymmetric carrier transport owing to the effective hole mass is three times heavier than effective electron mass are found to play critical roles in controlling the conductance, leading to high resistance. There was little difference in synaptic weight updates with high linearity and 250 states before and after bending the flexible device. Moreover, the MNIST-based recognition rate of over 90% is maintained upon bending, indicative of a promising candidate for highly efficient flexible artificial synapses.

Synaptic Plasticity Powering Long-Afterglow Organic Light-Emitting Transistors

Long-lasting luminescence in optoelectronic devices is highly sought after for applications in optical data storage and display technology. While in light-emitting diodes this is achieved by exploiting long-afterglow organic materials as active components, such a strategy has never been pursued in light-emitting transistors, which are still rather unexplored and whose technological potential is yet to be demonstrated. Herein, the fabrication of long-afterglow organic light-emitting transistors (LAOLETs) is reported whose operation relies on an unprecedented strategy based on a photoinduced synaptic effect in an inorganic indium-gallium-zinc-oxide (IGZO) semiconducting channel layer, to power a persistent electroluminescence in organic light-emitting materials. Oxygen vacancies in the IGZO layer, produced by irradiation at λ = 312 nm, free electrons in excess yielding to a channel conductance increase. Due to the slow recombination kinetics of photogenerated electrons to oxygen vacancies in the channel layer, the organic material can be fueled by postsynaptic current and displays a long-lived light-emission (hundreds of seconds) after ceasing UV irradiation. As a proof-of-concept, the LAOLETs are integrated in active-matrix light-emitting arrays operating as visual UV sensors capable of long-lifetime green-light emission in the irradiated regions.

Ecofriendly Solution-Combustion-Processed Thin-Film Transistors for Synaptic Emulation and Neuromorphic Computing

The ecofriendly combustion synthesis (ECS) and self-combustion synthesis (ESCS) have been successfully utilized to deposit high-k aluminum oxide (AlO_x) dielectrics at low temperatures and applied for aqueous In₂O₃ thin-film transistors (TFTs) accordingly. The ECS and ESCS processes facilitate the formation of high-quality dielectrics at lower temperatures compared to conventional methods based on an ethanol precursor, as confirmed by thermal analysis and chemical composition characterization. The aqueous In₂O₃ TFTs based on ECS and ESCS-AlO_x show enhanced electrical characteristics and counterclockwise transfer-curve hysteresis. The memory-like counterclockwise behavior in the transfer curve modulated by the gate bias voltage is comparable to the signal modulation by the neurotransmitters. ECS and ESCS transistors are employed to perform synaptic emulation; various short-term and long-term memory functions are emulated with low operating voltages and high excitatory postsynaptic current levels. High stability and reproducibility are achieved within 240 pulses of long-term synaptic potentiation and depression. The synaptic emulation functions achieved in this work match the demand for artificial neural networks (ANN), and a multilayer perceptron (MLP) is developed using an ECS-AlO_x synaptic transistor for image recognition. A superior recognition rate of over 90% is achieved based on ECS-AlO_x synaptic transistors, which facilitates the implementation of the metal-oxide synaptic transistor for future neuromorphic computing via an ecofriendly route.

High-Performance Organic Synaptic Transistors with an Ultrathin Active Layer for Neuromorphic Computing

In recent years, much attention has been focused on two-dimensional (2D) material-based synaptic transistor devices because of their inherent advantages of low dimension, simultaneous read-write operation and high efficiency. However, process compatibility and repeatability of these materials are still a big challenge, as well as other issues such as complex transfer process and material selectivity. In this work, synaptic transistors with an ultrathin organic semiconductor layer (down to 7 nm) were obtained by the simple dip-coating process, which exhibited a high current switch ratio up to 10⁶, well off state as low as nearly 10^-12 A, and low operation voltage of -3 V. Moreover, various synaptic behaviors were successfully simulated including excitatory postsynaptic current, paired pulse facilitation, long-term potentiation, and long-term depression. More importantly, under ultrathin conditions, excellent memory preservation, and linearity of weight update were obtained because of the enhanced effect of defects and improved controllability of the gate voltage on the ultrathin active layer, which led to a pattern recognition rate up to 85%. This is the first work to demonstrate that the pattern recognition rate, a crucial parameter for neuromorphic computing can be significantly improved by reducing the thickness of the channel layer. Hence, these results not only reveal a simple and effective way to improve plasticity and memory retention of the artificial synapse via thickness modulation but also expand the material selection for the 2D artificial synaptic devices.

Solution-processed electronics for artificial synapses

Artificial synaptic devices and systems have become hot topics due to parallel computing, high plasticity, integration of storage, and processing to meet the challenges of the traditional Von Neumann computers. Currently, two-terminal memristors and three-terminal transistors have been mainly developed for high-density storage with high switching speed and high reliability because of the adjustable resistivity, controllable ion migration, and abundant choices of functional materials and fabrication processes. To achieve the low-cost, large-scale, and easy-process fabrication, solution-processed techniques have been extensively employed to develop synaptic electronics towards flexible and highly integrated three-dimensional (3D) neural networks. Herein, we have summarized and discussed solution-processed techniques in the fabrication of two-terminal memristors and three-terminal transistors for the application of artificial synaptic electronics mainly reported in the recent five years from the view of fabrication processes, functional materials, electronic operating mechanisms, and system applications. Furthermore, the challenges and prospects were discussed in depth to promote solution-processed techniques in the future development of artificial synapse with high performance and high integration.

Synaptic transistors with aluminum oxide dielectrics enabling full audio frequency range signal processing

The rapid evolution of the neuromorphic computing stimulates the search for novel brain-inspired electronic devices. Synaptic transistors are three-terminal devices that can mimic the chemical synapses while consuming low power, whereby an insulating dielectric layer physically separates output and input signals from each other. Appropriate choice of the dielectric is crucial in achieving a wide range of operation frequencies in these devices. Here we report synaptic transistors with printed aluminum oxide dielectrics, improving the operation frequency of solution-processed synaptic transistors by almost two orders of magnitude to 50 kHz. Fabricated devices, yielding synaptic response for all audio frequencies (20 Hz to 20 kHz), are employed in an acoustic response system to show the potential for future research in neuro-acoustic signal processing with printed oxide electronics.