Solution-Processed, Electrolyte-Gated In2O3 Flexible Synaptic Transistors for Brain-Inspired Neuromorphic Applications

Nanomaterials for Flexible Neuromorphics

The quest to imbue machines with intelligence akin to that of humans, through the development of adaptable neuromorphic devices and the creation of artificial neural systems, has long stood as a pivotal goal in both scientific inquiry and industrial advancement. Recent advancements in flexible neuromorphic electronics primarily rely on nanomaterials and polymers owing to their inherent uniformity, superior mechanical and electrical capabilities, and versatile functionalities. However, this field is still in its nascent stage, necessitating continuous efforts in materials innovation and device/system design. Therefore, it is imperative to conduct an extensive and comprehensive analysis to summarize current progress. This review highlights the advancements and applications of flexible neuromorphics, involving inorganic nanomaterials (zero-/one-/two-dimensional, and heterostructure), carbon-based nanomaterials such as carbon nanotubes (CNTs) and graphene, and polymers. Additionally, a comprehensive comparison and summary of the structural compositions, design strategies, key performance, and significant applications of these devices are provided. Furthermore, the challenges and future directions pertaining to materials/devices/systems associated with flexible neuromorphics are also addressed. The aim of this review is to shed light on the rapidly growing field of flexible neuromorphics, attract experts from diverse disciplines (e.g., electronics, materials science, neurobiology), and foster further innovation for its accelerated development.

Low voltage electric-double-layer transistor nonenzymic erythromycin sensors based on molecularly imprinted polymers

Erythromycin (Ery) is a commonly used antibiotic that can be found ubiquitously in water bodies. The increasing apprehension over the adverse effects of antibiotic remnants in aquatic environments necessitates the prompt advancement of erythromycin detection techniques that are both highly sensitive and compact. Here, we propose a non-enzyme Ery sensor that integrates a mesoporous SiO2-based low-voltage oxide electric-double-layer transistor (EDLT) with a molecular imprinting technique, featuring a molecularly imprinted polymers (MIP) functionalized gate electrode. The mesoporous SiO2-based oxide transistor exhibits excellent electrical characteristics, including an operating voltage of small than 1.0 V, an on/off ratio exceeding 106 and a mobility of 14.95 cm2V-1s-1. At an ultra-low operating voltage within 0.5 V, the sensor exhibits a linear response to the concentration range of 1 nM-10 μM of Ery, with a detection limit of 0.22 nM and a sensitivity of 23.3 mV dec-1. Besides, the single-spike dynamic sensing mode effectively reduces the power consumption of the detection. The proposed sensor provides a rapid and convenient approach to detect Ery in aqueous environments, with benefits such as miniaturization, high sensitivity, and simplicity.

Hydrogel-Gated FETs in Neuromorphic Computing to Mimic Biological Signal: A Review

Hydrogel-gated synaptic transistors offer unique advantages, including biocompatibility, tunable electrical properties, being biodegradable, and having an ability to mimic biological synaptic plasticity. For processing massive data with ultralow power consumption due to high parallelism and human brain-like processing abilities, synaptic transistors have been widely considered for replacing von Neumann architecture-based traditional computers due to the parting of memory and control units. The crucial components mimic the complex biological signal, synaptic, and sensing systems. Hydrogel, as a gate dielectric, is the key factor for ionotropic devices owing to the excellent stability, ultra-high linearity, and extremely low operating voltage of the biodegradable and biocompatible polymers. Moreover, hydrogel exhibits ionotronic functions through a hybrid circuit of mobile ions and mobile electrons that can easily interface between machines and humans. To determine the high-efficiency neuromorphic chips, the development of synaptic devices based on organic field effect transistors (OFETs) with ultra-low power dissipation and very large-scale integration, including bio-friendly devices, is needed. This review highlights the latest advancements in neuromorphic computing by exploring synaptic transistor developments. Here, we focus on hydrogel-based ionic-gated three-terminal (3T) synaptic devices, their essential components, and their working principle, and summarize the essential neurodegenerative applications published recently. In addition, because hydrogel-gated FETs are the crucial members of neuromorphic devices in terms of cutting-edge synaptic progress and performances, the review will also summarize the biodegradable and biocompatible polymers with which such devices can be implemented. It is expected that neuromorphic devices might provide potential solutions for the future generation of interactive sensation, memory, and computation to facilitate the development of multimodal, large-scale, ultralow-power intelligent systems.

Synaptic Plasticity Modulation of Neuromorphic Transistors through Phosphorus Concentration in Phosphosilicate Glass Electrolyte Gate

This study proposes a phosphosilicate glass (PSG)-based electrolyte gate synaptic transistor with varying phosphorus (P) concentrations. A metal oxide semiconductor capacitor structure device was employed to measure the frequency-dependent (C-f) capacitance curve, demonstrating that the PSG electric double-layer capacitance increased at 103 Hz with rising P concentration. Fourier transform infrared spectroscopy spectra analysis facilitated a theoretical understanding of the C-f curve results, examining peak differences in the P-OH structure based on P concentration. Using the proposed synaptic transistors with different P concentrations, changes in the hysteresis window were investigated by measuring the double-sweep transfer curves. Subsequently, alterations in proton movement within the PSG and charge characteristics at the channel/PSG electrolyte interface were observed through excitatory post-synaptic currents, paired-pulse facilitation, signal-filtering functions, resting current levels, and potentiation and depression characteristics. Finally, we demonstrated the proposed neuromorphic system's feasibility based on P concentration using the Modified National Institute of Standards and Technology learning simulations. The study findings suggest that, by adjusting the PSG film's P concentration for the same electrical stimulus, it is possible to selectively mimic the synaptic signal strength of human synapses. Therefore, this approach can positively contribute to the implementation of various neuromorphic systems.

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.

Weighted-Sum Operation of Three-Terminal Synapse Transistors in Array Configuration Using Spin-Coated Li-Doped ZrO2 Electrolyte Gate Insulator

Artificial synapses with ideal functionalities are essential in hardware neural networks to allow for energy-efficient analog computing. Electrolyte-gated transistors (EGTs) are promising candidates for artificial synaptic devices due to their low voltage operations supported by large specific capacitances of electrolyte gate insulators (EGIs). We investigated the synapse transistor employing an In-Ga-Zn-O channel and a Li-doped ZrO2 (LZO) EGI so as to improve the short-term plasticity (STP) and long-term potentiation (LTP). The LZO EGIs showed distinct differences in characteristics depending on the Li doping concentration, and we adopted the optimum doping concentration of 10%. Based on the strong electric double layer effect secured from the LZO, we successfully demonstrated excellent synaptic operations with gradual modulations of excitatory synaptic plasticity with variations in amplitude, width, and number of applied pulse spikes. The introduction of the LZO EGI was verified to improve typical short-term plasticity such as paired-pulse facilitation. Furthermore, by minutely controlling the pulse spike conditions, the conversion to LTP from STP was clearly accomplished while implementing the anti-Hebbian spike timing-dependent plasticity. Finally, the array configuration of synaptic devices, which is essential for realizing neuromorphic computing, was also demonstrated. In a 3 × 3 array architecture, the weighted-sum operation was well emulated to assign multilevels in seven states with the pulse width modulation scheme.

Synaptic Transistors Based on PVA: Chitosan Biopolymer Blended Electric-Double-Layer with High Ionic Conductivity

This study proposed a biocompatible polymeric organic material-based synaptic transistor gated with a biopolymer electrolyte. A polyvinyl alcohol (PVA):chitosan (CS) biopolymer blended electrolyte with high ionic conductivity was used as an electrical double layer (EDL). It served as a gate insulator with a key function as an artificial synaptic transistor. The frequency-dependent capacitance characteristics of PVA:CS-based biopolymer EDL were evaluated using an EDL capacitor (Al/PVA: CS blended electrolyte-based EDL/Pt configuration). Consequently, the PVA:CS blended electrolyte behaved as an EDL owing to high capacitance (1.53 µF/cm²) at 100 Hz and internal mobile protonic ions. Electronic synaptic transistors fabricated using the PVA:CS blended electrolyte-based EDL membrane demonstrated basic artificial synaptic behaviors such as excitatory post-synaptic current modulation, paired-pulse facilitation, and dynamic signal-filtering functions by pre-synaptic spikes. In addition, the spike-timing-dependent plasticity was evaluated using synaptic spikes. The synaptic weight modulation was stable during repetitive spike cycles for potentiation and depression. Pattern recognition was conducted through a learning simulation for artificial neural networks (ANNs) using Modified National Institute of Standards and Technology datasheets to examine the neuromorphic computing system capability (high recognition rate of 92%). Therefore, the proposed synaptic transistor is suitable for ANNs and shows potential for biological and eco-friendly neuromorphic systems.

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.

Biocompatible Casein Electrolyte-Based Electric-Double-Layer for Artificial Synaptic Transistors

In this study, we proposed a synaptic transistor using an emerging biocompatible organic material, namely, the casein electrolyte as an electric-double-layer (EDL) in the transistor. The frequency-dependent capacitance of the indium-tin-oxide (ITO)/casein electrolyte-based EDL/ITO capacitor was assessed. As a result, the casein electrolyte was identified to exhibit a large capacitance of ~1.74 μF/cm2 at 10 Hz and operate as an EDL owing to the internal proton charge. Subsequently, the implementation of synaptic functions was verified by fabricating the synaptic transistors using biocompatible casein electrolyte-based EDL. The excitatory post-synaptic current, paired-pulse facilitation, and signal-filtering functions of the transistors demonstrated significant synaptic behavior. Additionally, the spike-timing-dependent plasticity was emulated by applying the pre- and post-synaptic spikes to the gate and drain, respectively. Furthermore, the potentiation and depression characteristics modulating the synaptic weight operated stably in repeated cycle tests. Finally, the learning simulation was conducted using the Modified National Institute of Standards and Technology datasets to verify the neuromorphic computing capability; the results indicate a high recognition rate of 90%. Therefore, our results indicate that the casein electrolyte is a promising new EDL material that implements artificial synapses for building environmental and biologically friendly neuromorphic systems.

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.

Biology and bioinspiration of soft robotics: Actuation, sensing, and system integration

Organisms in nature grow with senses, nervous, and actuation systems coordinated in ingenious ways to sustain metabolism and other essential life activities. The understanding of biological structures and functions guide the construction of soft robotics with unprecedented performances. However, despite the progress in soft robotics, there still remains a big gap between man-made soft robotics and natural lives in terms of autonomy, adaptability, self-repair, durability, energy efficiency, etc. Here, the actuation and sensing strategies in the natural biological world are summarized along with their man-made counterparts applied in soft robotics. The development trends of bioinspired soft robotics toward closed loop and embodiment are proposed. Challenges for obtaining autonomous soft robotics similar to natural organisms are outlined to provide a perspective in this field.

Flexible Artificial Synapses with a Biocompatible Maltose-Ascorbic Acid Electrolyte Gate for Neuromorphic Computing

As constructing hardware technology is widely regarded as an important step toward realizing brain-like computers and artificial intelligence systems, the development of artificial synaptic electronics that can simulate biological synaptic functions is an emerging research field. Among the various types of artificial synapses, synaptic transistors using an electrolyte as the gate electrode have been implemented as the high capacitance of the electrolyte increases the driving current and lowers operating voltages. Here, transistors using maltose-ascorbic acid as the proton-conducting electrolyte are proposed. A novel electrolyte composed of maltose and ascorbic acid, both of which are biocompatible, enables the migration of protons. This allows the channel conductance of the transistors to be modulated with the gate input pulse voltage, and fundamental synaptic functions including excitatory postsynaptic current, paired-pulse facilitation, long-term potentiation, and long-term depression can be successfully emulated. Furthermore, the maltose-ascorbic acid electrolyte (MAE)-gated synaptic transistors exhibit high mechanical endurance, with near-linear conductivity modulation and repeatability after 1000 bending cycles under a curvature radius of 5 mm. Benefitting from its excellent biodegradability and biocompatibility, the proposed MAE has potential applications in environmentally friendly, economical, and high-performance neuromorphic electronics, which can be further applied to dermal electronics and implantable electronics in the future.

Wide range modulation of synaptic weight in thin-film transistors with hafnium oxide gate insulator and indium-zinc oxide channel layer for artificial synapse application

Wide range synaptic weight modulation with a tunable drain current was demonstrated in thin-film transistors (TFTs) with a hafnium oxide (HfO2-x) gate insulator and an indium-zinc oxide (IZO) channel layer for application to artificial synapses in neuromorphic systems. The drain current in these TFTs was reduced significantly by four orders of magnitude on application of a negative gate bias, then could be restored to its original value by applying a positive bias. The reduced drain current under negative biasing is interpreted as being caused by voltage-driven oxygen ion migration from the HfO2-x gate insulator to the IZO channel, which reduces the oxygen vacancy concentration in the IZO channel. In addition to emulating the analog-type potentiation and depression motions in artificial synapses, the tunable drain current presents paired-pulse facilitation and short-term and long-term plasticity behaviors. These wide-ranging and nonvolatile synaptic behaviors with tunable drain currents are indicative of the potential of the proposed TFTs for artificial synapse applications.

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.

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.