Organic Synaptic Transistor Research Articles

Organic Optoelectronic Synaptic Transistor with Enhanced UV Light Response Based on Insulating Polymer-Assisted p-n Heterojunction.

Optoelectronic synaptic transistors possess the capability to simultaneously accomplish perception and process functions within a single device, thereby not only addressing the limitations of von Neumann architectures but also serving as a promising candidate for emulating neural vision systems. The extensive range of organic semiconductor materials offers a plethora of possibilities for device fabrication; however, the severe recombination of photogenerated carriers imposes limitations on the utilization of organic p-n bulk heterostructures in synaptic transistor construction. By incorporating an insulating polymer and implementing a p-n planar heterojunction architecture, the 30% PCBM@PAN-DPPDTT transistor was constructed using the PCBM/DPPDTT heterojunction and the PCBM@PAN photoresponsive charge trapping layer. Due to the effect of the photoresponsive charge trapping layer and interface traps, the device not only overcomes the shortcomings of p-n bulk heterojunction and exhibits typical synaptic properties but also demonstrates a significantly enhanced response to ultraviolet (UV) light, exhibiting nearly four times more excitatory postsynaptic current (ΔEPSC) compared to the device lacking PCBM. The transistor matrix was employed to simulate the image perception and memory functions of the human neural vision system. Furthermore, an artificial neural network with high recognition accuracy (∼95%) of handwritten numbers was constructed. This study proposes an additional approach for mitigating the issue of rapid recombination of photogenerated charge carriers in the construction of optoelectronic synaptic transistors by utilizing p-n heterojunction.

Ultrasensitive Flexible Organic Synaptic Transistors Modulated by a Chemically Cross-Linked Solvent-Resistive Ion Composite.

We demonstrate a flexible organic synaptic transistor (FOST) with an ion-composite electrolyte film resistant to chemical reagents, which uses a three-dimensionally cross-linked polyimide matrix to accommodate a high-concentration ionic liquid. FOST shows versatile synaptic plasticity for classical conditioning, high-pass filtering, and the learning-forgetting process. The device achieves low-energy consumption down to 1.02 femtojoule per synaptic event with an ultrasensitive impulse to presynaptic spike down to 0.5 mV. Moreover, the electrical performance of the device is still stable after 1000 mechanical bending cycles. These results demonstrate that the device can be applied to future flexible neuromorphic electronics.

All‐Polymer Organic Electrochemical Synaptic Transistor With Controlled Ionic Dynamics for High‐Performance Wearable and Sustainable Reservoir Computing

All‐Polymer Organic Electrochemical Synaptic Transistor With Controlled Ionic Dynamics for High‐Performance Wearable and Sustainable Reservoir Computing

Bioinspired Flexible and Low-Voltage Organic Synaptic Transistors for UV Light-Driven Vision Systems.

Neuromorphic vision systems, particularly those stimulated by ultraviolet (UV) light, hold great potential applications in portable electronics, wearable technology, biological analysis, military surveillance, etc. Organic artificial synaptic devices hold immense potential in this field due to their ease of processing, flexibility, and biocompatibility. In this work, we have fabricated a flexible organic field-effect transistor (OFET) that utilizes chitosan-silver nanoparticles (AgNPs) composite material as the active dielectric material. During UV light illumination, both silver nanoparticles and the pentacene layer generate a large number of charge carriers. The photogenerated carriers lead to a more significant hole accumulation at the pentacene interface, resulting in a current rise. In the absence of light, the trapped electron in the silver nanoparticles persists for a longer duration, preventing the instant recombination with holes. This extended retention of electrons leads to the observed synaptic performance of the transistor. The use of aluminum oxide (Al2O3) as one of the dielectric layers enables the device to operate effectively at low voltage (<1 V). The device mimics various crucial synaptic properties of the brain, including short-term potentiation and long-term potentiation (STP and LTP), paired-pulse facilitation (PPF), spike-duration dependent plasticity (SDDP), spike-number dependent plasticity (SNDP), and spike-rate dependent plasticity (SRDP), etc. This work introduces an approach to develop flexible organic synaptic transistors that operate efficiently at low voltages, paving the way toward high-performance, UV light-driven neuromorphic vision systems.

Retina-Inspired Large-Area Solution-Processed flexible Multi-Band organic neuromorphic synaptic transistor arrays

The proliferation of high-efficacy, pliable organic neuromorphic synaptic transistors is quintessential for the integration into wearable artificial intelligence ecosystems. Nevertheless, their development is hindered by substantial energy demands and suboptimal charge carrier mobility. To surmount these obstacles, we exploit solution-processed poly(amic acid) (PAA) dielectrics and organic semiconductors to engineer pliable arrays of organic neuromorphic synaptic transistors atop a polyethylene terephthalate (PET) matrix. The polar group and nanogroove structure of PAA obtain excellent semiconductor crystal structure, and the excellent dielectric properties enable these engineered arrays to show a charge carrier mobility peak of 29.83 cm2 V−1 s−1 an aggregate mean mobility of 15.87 cm2 V−1 s−1 (standard deviation is 6.71) at a voltage of −3 V and the energy expenditure per synaptic transaction was only 0.26 fJ. Additionally, the transistors possess the aptitude for photodetection across ultraviolet–visible to near-infrared spectral bands. The successful execution of flexible imaging, Pavlovian classical conditioning reflex associative learning, coupled with a 93.9 % accuracy in handwritten numeral recognition, corroborates the viability of these high-mobility, low-power organic neuromorphic synaptic transistor arrays.

Near-Infrared Response Organic Synaptic Transistor for Dynamic Trace Extraction.

The development of neuromorphic hardware capable of detecting and recognizing moving targets through an in-sensor computing strategy is considered to be an important component of the construction of edge computing systems with distributed computation. In addition to responsiveness to visible light, the implementation of neuromorphic hardware should also demonstrate the ability to sense and process nonvisible light, which is essential for tracking target object trajectories in specialized environments. In this work, we fabricated an organic synaptic transistor with a near-infrared (NIR) response by incorporating doped LaF3: Yb/Ho upconversion quantum dots (UCQDs) into the channel of a Poly3-hexylthiophene (P3HT)-based organic field effect transistor (FET), serving as charge trapping and infrared sensing sites. The obtained synaptic transistor not only replicates common synaptic behaviors when exposed to NIR illumination but also demonstrates potential applications for the dynamic trajectory recognition of animals in the dark. Compared to other monitoring technologies, P3HT transistors doped with LaF3: Yb/Ho UCQDs exhibit distinct advantages, including a NIR response, high-efficiency computing, and sensitivity, which provide an experimental foundation and a design reference for the development of next-generation intelligent dynamic image recognition systems.

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

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

Organic synaptic transistor showing ultralow energy consumption with a microscale channel by laser ablation

Low energy consumption per synaptic event is important for artificial synapses in applications of highly integrated and large-scale neuromorphic computing systems. Reducing the channel length of a synaptic transistor is an effective method to achieve this goal because such devices can work under low operating voltage and current. In this Letter, we use femtosecond laser ablation to fabricate a microscale slit in an Ag film as the channel of an organic synaptic transistor to obtain low energy consumption. The length of the shortest channel is only 1.6 μm. As a result, the device could be driven by a 50 μV drain bias voltage while output 855 pA excitatory postsynaptic current under a gate spike of 50 mV and 30 ms. The calculated energy consumption per synaptic event is 1.28 fJ, which is comparable to that of a biological synapse (1–10 fJ per synaptic event). Femtosecond laser ablation has been demonstrated a rapid and effective process for the fabrication of microscale channel with high resolution for synaptic transistor, showing large potential for the development of neuromorphic electronics.

Modulating Neuromorphic Behavior of Organic Synaptic Electrolyte-Gated Transistors Through Microstructure Engineering and Potential Applications.

Organic synaptic transistors are a promising technology for advanced electronic devices with simultaneous computing and memory functions and for the application of artificial neural networks. In this study, the neuromorphic electrical characteristics of organic synaptic electrolyte-gated transistors are correlated with the microstructural and interfacial properties of the active layers. This is accomplished by utilizing a semiconducting/insulating polyblend-based pseudobilayer with embedded source and drain electrodes, referred to as PB-ESD architecture. Three variations of poly(3-hexylthiophene) (P3HT)/poly(methyl methacrylate) (PMMA) PB-ESD-based organic synaptic transistors are fabricated, each exhibiting distinct microstructures and electrical characteristics, thus serving excellent samples for exploring the critical factors influencing neuro-electrical properties. Poor microstructures of P3HT within the active layer and a flat active layer/ion-gel interface correspond to typical neuromorphic behaviors such as potentiated excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and short-term potentiation (STP). Conversely, superior microstructures of P3HT and a rough active layer/ion-gel interface correspond to significantly higher channel conductance and enhanced EPSC and PPF characteristics as well as long-term potentiation behavior. Such devices were further applied to the simulation of neural networks, which produced a good recognition accuracy. However, excessive PMMA penetration into the P3HT conducting channel leads to features of a depressed EPSC and paired-pulse depression, which are uncommon in organic synaptic transistors. The inclusion of a second gate electrode enables the as-prepared organic synaptic transistors to function as two-input synaptic logic gates, performing various logical operations and effectively mimicking neural modulation functions. Microstructure and interface engineering is an effective method to modulate the neuromorphic behavior of organic synaptic transistors and advance the development of bionic artificial neural networks.

Controlled Migration of Lithium Cations by Diamine Bridges in Water-Processable Polymer-Based Solid-State Electrolyte Memory Layers for Organic Synaptic Transistors.

Synaptic transistors require sufficient retention (memory) performances of current signals to exactly mimic biological synapses. Ion migration has been proposed to achieve high retention characteristics but less attention has been paid to polymer-based solid-state electrolytes (SSEs) for organic synaptic transistors (OSTRs). Here, OSTRs with water-processable polymer-based SSEs, featuring ion migration-controllable molecular bridges, which are prepared by reactions of poly(4-styrenesulfonic acid) (PSSA), diethylenetriamine (DETA), and lithium hydroxide (LiOH) are demonstrated. The ion conductivity of PSSA:LiOH:DETA (1:0.4:X, PLiD) films is remarkably changed by the molar ratio (X) of DETA, which is attributed to the extended distances between the PSSA chains by the DETA bridges. The devices with the PLiD layers deliver noticeably changed hysteresis reaching an optimum at X = 0.2, leading to the longest retention of current signals upon single/double pulses. The long-term potentiation test confirms that the present OSTRs can gradually build up the postsynaptic current by gate pulses of -2V, while the long-term depression can be adjusted by varying the depression gate pulses (≈0.2-1.2V). The artificial neural network simulations disclose that the present OSTRs with the ion migration-controlled PLiD layers can perform synaptic processes with an accuracy of ≈96%.

Simulation of neural functions based on organic semiconductor/MXene synaptic transistors

Artificial synaptic devices, which are the basic units of neuromorphic computing systems, can perform signal processing with low power consumption. Organic synaptic transistors have attracted significant attention owing to their lightweight and good compatibility with flexible substrates. As per the current state of research both domestically and internationally, the majority of the existing organic synaptic transistors are based on floating gate structures, electret configurations, ferroelectric types. Furthermore, additional capture layers are required for the preparation of these devices. Two-dimensional MXenes have great potential in the preparation of synaptic transistors owing to their efficient multiple energy storage capabilities, excellent metallic conductivity, abundant surface functional groups, hydrophilicity, and layered structure. Therefore, high-performance synaptic transistors based on the two-dimensional material MXene were developed in this study. These transistors not only exhibited excellent memory performance with a memory window above 20 V, but also successfully simulated typical synaptic behaviors, including excitatory postsynaptic current/inhibitory postsynaptic current (EPSC/IPSC), paired-pulse facilitation/paired-pulse depression (PPF/PPD), and long-term plasticity (LTP). Synaptic transistors based on MXenes represent a promising approach for the preparation of high-performance organic synaptic transistors.

Induction of Synaptic Plasticity in Flexible Organic Synaptic Transistors with Cross‐Linked Polymer Dielectric

AbstractControlled cross‐linking of polymer dielectric poly (4‐vinylphenol) (PVP) is demonstrated as an effective tool in enhancing the performance of flexible organic synaptic transistors (OSTs). Investigation of variation of concentration of the cross‐linking agent methylated poly (melamine‐co‐formaldehyde) (PMCF) in PVP in bilayer combination with high‐k hafnium oxide (HfO2) as gate dielectric in devices shows that the lower concentration of cross‐linking agent results in better memory performance. OSTs with 26% PMCF concentration in PVP (by mass) exhibit excellent memory performance with memory window &gt; 4 V for VGS sweep of ±5 V, static retention of ≈104 s, dynamic retention for 500 cycles, and ≈125 continuous program/erase cycles. Pulse paired facilitation with relaxation time constants of 370 and 4670 ms respectively for slow and rapid phases with regulating modulation amplitude of ≈1 resemble a biological synapse. Through excitatory post synaptic current characteristics, spike timing dependant plasticity and spike voltage dependant plasticity are clearly observed, with low energy consumption per spike on the order of 10 pJ. Further, by leveraging the intricate interconnected data transfer and computation phenomenon, “AND” logic is effectively implemented using these OSTs. These exciting results may open up new directions toward the development of hardware for neuromorphic computing.

Flexible Organic Ferroelectric Synaptic Transistors for Wearable Neuromorphic Systems

An organic ferroelectric synaptic transistor (OFST) is an excellent candidate for use as an artificial synapse in wearable neuromorphic systems. In OFSTs, polarization switching is achieved by electric stimuli, leading to the modulation of channel conductance. To develop wearable neuromorphic systems employing OFSTs, it is necessary to effectively emulate biological synaptic functions in the devices by controlling dipole switching dynamics. In this paper, the operating mechanisms for the OFSTs, and the organic ferroelectric materials are first discussed. Recent researches for controlling the polarization switching dynamics to emulate synaptic characteristics, including synaptic plasticity, continuous synaptic weight, low operating voltage, and multifunctional capability, are then reviewed. Lastly, future research directions for achieving bio-realistic OFSTs for practical wearable electronics are proposed.

Increasing the stability of electrolyte-gated organic synaptic transistors for neuromorphic implants

Electrolyte-gated organic synaptic transistors (EGOSTs) can have versatile synaptic plasticity in a single device, so they are promising as components of neuromorphic implants that are intended for use in neuroprosthetic electronic nerves that are energy-efficient and have simple system structure. With the advancement in transistor properties of EGOSTs, the commercialization of neuromorphic implants for practical long-term use requires consistent operation, so they must be stable in vivo. This requirement demands strategies that maintain electronic and ionic transport in the devices while implanted in the human body, and that are mechanically, environmentally, and operationally stable. Here, we cover the structure, working mechanisms, and electrical responses of EGOSTs. We then focus on strategies to ensure their stability to maintain these characteristics and prevent adverse effects on biological tissues. We also highlight state-of-the-art neuromorphic implants that incorporate these strategies. We conclude by presenting a perspective on improvements that are needed in EGOSTs to develop practical, neuromorphic implants that are long-term useable.

Organic Synaptic Transistors with Environmentally Friendly Core/Shell Quantum Dots for Wavelength-Selective Memory and Neuromorphic Functions.

Organic transistors based on organic semiconductors together with quantum dots (QDs) are attracting more and more interest because both materials have excellent optoelectronic properties and solution processability. Electronics based on nontoxic QDs are highly desired considering the potential health risks but are limited by elevated surface defects, inadequate stability, and diminished luminescent efficiency. Herein, organic synaptic transistors based on environmentally friendly ZnSe/ZnS core/shell QDs with passivating surface defects are developed, exhibiting optically programmable and electrically erasable characteristics. The synaptic transistors feature linear multibit storage capability and wavelength-selective memory function with a retention time above 6000 s. Various neuromorphic applications, including memory enhancement, optical communication, and memory consolidation behaviors, are simulated. Utilizing an established neuromorphic model, accuracies of 92% and 91% are achieved in pattern recognition and complicated electrocardiogram signal processing, respectively. This research highlights the potential of environmentally friendly QDs in neuromorphic applications and health monitoring.

Self-supported flexible organic electrochemical synaptic transistors on self-healing composite electrolyte membranes

A variety of organic electrochemical transistors have been recently developed; however, their self-healing performance has been largely ignored. In this study, we propose the use of a lithium-ion composite electrolyte membrane as a dielectric layer and the use of poly(3-hexylthiophene) (P3HT) as a channel layer to fabricate flexible self-supporting organic synaptic transistors. A variety of synaptic behaviors were emulated within the proposed organic synaptic transistors. By leveraging the self-healing features of polymer electrolytes, along with cross-linking reactions and low-resistance lithium-ion transmission, the device maintained its electrical performance. Testing involving different curvatures also revealed the device's potential for use in flexible electronics. Significantly, due to the device's self-healing ability, consistent dataset recognition rates were sustained. This work highlights its vast prospects in the field of flexible and wearable electronics.

Intelligent Tribotronic Transistors Toward Tactile Near‐Sensor Computing

AbstractFor the next generation of human‐machine interaction (HMI) systems, the development of a tactile interaction unit with multimodal, high sensitivity, and real‐time perception and recognition is the key. Herein, an artificial tactile near‐sensor computing (ATNSC) unit based on a triboelectric tactile sensor and an organic synaptic transistor is reported. By introducing multi‐peak microstructures, the mechanical performance of the tactile sensor is optimized, showing a high sensitivity of 0.98 V kPa−1 in the pressure range of 0–10 kPa and maintaining 0.11 V kPa−1 at high pressures up to 350 kPa. Additionally, by designing stripe‐like convex structures on the top surface, the sensor is capable of bimodal perception in both pressure and sliding sensations. Furthermore, the organic synaptic transistor, which can be driven by tactile sensing stimuli in a variety of circumstances, is achieved utilizing an ion‐rich gelatin dielectric covered by a hydrophobic polymer coating layer. The ATNSC unit well demonstrates the stimuli‐dependent short‐term memory effect, and it enables tactile near‐sensor computing for feature action recognition in an HMI system, laying a solid foundation for the construction of intelligent interaction devices.

PBDB-T/Pentacene-Based Organic Optoelectronic Synaptic Transistor with Adjustable Critical Flicker Fusion Frequency for Dynamic Vision.

In the era of the Internet of Things and the rapid progress of artificial intelligence, there is a growing demand for advanced dynamic vision systems. Vision systems are no longer confined to static object detection and recognition, as the detection and recognition of moving objects are becoming increasingly important. To meet the requirements for more precise and efficient dynamic vision, the development of adaptive multimodal motion detection devices becomes imperative. Inspired by the varied response rates in biological vision, we introduce the concept of critical flicker fusion frequency (cFFF) and develop an organic optoelectronic synaptic transistor with adjustable cFFF. In situ Kelvin probe force microscopy analysis reveals that light signal recognition in this device originates from charge transfer in the poly[(2,6-(4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:4,5-b']dithiophene)-co-(1,3-di(5-thiophene-2-yl)-5,7-bis(2-ethylhexyl)-benzo[1,2-c:4,5-c']dithiophene-4,8-dione)] (PBDB-T)/pentacene heterojunction, which can be effectively modulated by gate voltage. Building upon this, we implement different cFFF within a single device to facilitate the detection and recognition of objects moving at different speeds. This approach allows for resource allocation during dynamic detection, resulting in a reduction in power consumption. Our research holds great potential for enhancing the capabilities of dynamic visual systems.

A Retina-Inspired Optoelectronic Synapse Using Quantum Dots for Neuromorphic Photostimulation of Neurons.

Neuromorphic electronics, inspired by the functions of neurons, have the potential to enable biomimetic communication with cells. Such systems require operation in aqueous environments, generation of sufficient levels of ionic currents for neurostimulation, and plasticity. However, their implementation requires a combination of separate devices, such as sensors, organic synaptic transistors, and stimulation electrodes. Here, a compact neuromorphic synapse that combines photodetection, memory, and neurostimulation functionalities all-in-one is presented. The artificial photoreception is facilitated by a photovoltaic device based on cell-interfacing InP/ZnS quantum dots, which induces photo-faradaic charge-transfer mediated plasticity. The device sends excitatory post-synaptic currents exhibiting paired-pulse facilitation and post-tetanic potentiation to the hippocampal neurons via the biohybrid synapse. The electrophysiological recordings indicate modulation of the probability of action potential firing due to biomimetic temporal summation of excitatory post-synaptic currents. These results pave the way for the development of novel bioinspired neuroprosthetics and soft robotics, and highlight the potential of quantum dots for achieving versatile neuromorphic functionality in aqueous environments.

Organic Synaptic Transistors with an Ultra‐Short‐Term Weight‐Reconstruction for Processing Multiple Types of Signals

AbstractAn organic synaptic transistor (OST) that utilizes a multiple‐annealing process and an ion gate to achieve significant reductions in operating voltage and increases in transconductance is demonstrated. The OST exhibits an ultra‐short‐term plasticity (USTP) with a maximum retention time of only 20.7 ms, which does not increase with the number and duration of spikes. This is the shortest retention time yet achieved by an ion‐gel‐regulated synaptic transistor. In addition, OST‐integrated array exhibits a tunable weight plasticity and a short weight refresh time for a stable image resetting in ample time of &lt;0.2 s. It is also sensitive to the frequency and amplitude of electrical inputs; a low‐frequency suppression and a nonlinear amplitude gain enables OST‐constructed filter for use in processing multiple types of signals. This work is a step toward constructing high‐performance and multifunctional artificial intelligent systems.