Synaptic Plasticity Powering Long-Afterglow Organic Light-Emitting Transistors

Li Promoting Long Afterglow Organic Light-Emitting Transistor for Memory Optocoupler Module

The artificial brain is conceived as advanced intelligence technology, capable to emulate in-memory processes occurring in the human brain by integrating synaptic devices. Within this context, improving the functionality of synaptic transistors to increase information processing density in neuromorphic chips is a major challenge in this field. In this article, Li-ion migration promoting long afterglow organic light-emitting transistors, which display exceptional postsynaptic brightness of 7000 cd m-2 under low operational voltages of 10 V is presented. The postsynaptic current of 0.1 mA operating as a built-in threshold switch is implemented as a firing point in these devices. The setting-condition-triggered long afterglow is employed to drive the photoisomerization process of photochromic molecules that mimic neurotransmitter transfer in the human brain for realizing a key memory rule, that is, the transition from long-term memory to permanent memory. The combination of setting-condition-triggered long afterglow with photodiode amplifiers is also processed to emulate the human responding action after the setting-training process. Overall, the successful integration in neuromorphic computing comprising stimulus judgment, photon emission, transition, and encoding,  to emulate the complicated decision tree of the human brain is demonstrated.

Stepwise Charge/Energy Transfer in MR-TADF Molecule-Doped Exciplex for Ultralong Persistent Luminescence Activated with Visible Light

Organic long-persistent luminescence (OLPL), which relies on energy storage for delayed light emission by the charge separation state, has attracted intense attention in various optical applications. However, charge separation (CS) is efficient only under ultraviolet excitation in most OLPL systems because it requires a driving force from the large energy difference between the local excited (LE) and charge transfer (CT) states. In this study, a multiresonance thermally activated delayed fluorescence (MR-TADF) molecule is incorporated into an exciplex system to achieve efficient OLPL in a composite material activated by visible light via a stepwise charge/energy transfer process. The enhanced absorption of the composite material facilitated a tenfold increase in the duration of the OLPL, which can last for several hours under visible light excitation. The excited state of the MR-TADF molecule tends to charge transfer to the acceptor, followed by energy transfer to the exciplex, which benefits from the small difference between the LE and CT states owing to the inherent CS characteristics of the opposing resonance effect. Afterglow displays of these composite materials are fabricated to demonstrate their considerable potential in encryption patterns and emergency lights, which take advantage of their excellent processability, visible light activation, and tunable luminescence properties.

Toward Intelligent Display with Neuromorphic Technology

In the era of the Internet and the Internet of Things, display technology has evolved significantly toward full-scene display and realistic display. Incorporating "intelligence" into displays is a crucial technical approach to meet the demands of this development. Traditional display technology relies on distributed hardware systems to achieve intelligent displays but encounters challenges stemming from the physical separation of sensing, processing, and light-emitting modules. The high energy consumption and data transformation delays limited the development of intelligence display, breaking the physical separation is crucial to overcoming the bottlenecks of intelligence display technology. Inspired by the biological neural system, neuromorphic technology with all-in-one features is widely employed across various fields. It proves effective in reducing system power consumption, facilitating frequent data transformation, and enabling cross-scene integration. Neuromorphic technology shows great potential to overcome display technology bottlenecks, realizing the full-scene display and realistic display with high efficiency and low power consumption. This review offers a comprehensive summary of recent advancements in the application of neuromorphic technology in displays, with a focus on interoperability. This work delves into its state-of-the-art designs and potential future developments aimed at revolutionizing display technology.

Towards Artificial Visual Sensory System: Organic Optoelectronic Synaptic Materials and Devices

Developing an artificial visual sensory system requires optoelectronic materials and devices that can mimic the behavior of biological synapses. Organic/polymeric semiconductors have emerged as promising candidates for optoelectronic synapses due to their tunable optoelectronic properties, mechanic flexibility, and biological compatibility. In this review, we discuss the recent progress in organic optoelectronic synaptic materials and devices, including their design principles, working mechanisms, and applications. We also highlight the challenges and opportunities in this field and provide insights into potential applications of these materials and devices in next-generation artificial visual systems. By leveraging the advances in organic optoelectronic materials and devices, we can envision its future development in artificial intelligence.

Enhanced blue afterglow in Ce-doped boroaluminate glass modified by Na. OPTICS LETTERS 2023;48:5739-5742. [PMID: 37910747 DOI: 10.1364/ol.503334]

The alkali metal Na+ is commonly applied as a charge compensator to optimize afterglow performance but rarely reported as a structural regulator to modify afterglow behavior in long afterglow glass materials. In this paper, by preparing the Na + -modified Ce-doped boroaluminate glasses under a high-temperature reducing atmosphere, super-five times brighter blue-violet afterglow lasting up to 30 min was obtained. Results show that appropriate Na+ doping loosens the glass structure and widens the bandgap, thereby regulating most of the electron capture-release modes. This work provides new insights into the behavior of afterglow enhancement in alkali metal-doped glasses.

Emerging photoelectric devices for neuromorphic vision applications: principles, developments, and outlooks

The traditional von Neumann architecture is gradually failing to meet the urgent need for highly parallel computing, high-efficiency, and ultra-low power consumption for the current explosion of data. Brain-inspired neuromorphic computing can break the inherent limitations of traditional computers. Neuromorphic devices are the key hardware units of neuromorphic chips to implement the intelligent computing. In recent years, the development of optogenetics and photosensitive materials has provided new avenues for the research of neuromorphic devices. The emerging optoelectronic neuromorphic devices have received a lot of attentions because they have shown great potential in the field of visual bionics. In this paper, we summarize the latest visual bionic applications of optoelectronic synaptic memristors and transistors based on different photosensitive materials. The basic principle of bio-vision formation is first introduced. Then the device structures and operating mechanisms of optoelectronic memristors and transistors are discussed. Most importantly, the recent progresses of optoelectronic synaptic devices based on various photosensitive materials in the fields of visual perception are described. Finally, the problems and challenges of optoelectronic neuromorphic devices are summarized, and the future development of visual bionics is also proposed.

Optogenetics-Inspired Fluorescent Synaptic Devices with Nonvolatility

Given the synergy of optogenetics and bioimaging in neuroscience, it is possible for light to simultaneously modulate and visualize synaptic events of optoelectronic synaptic devices, which are building blocks of a neuromorphic computing system with optoelectronic integration. Here we demonstrate the realization of the simultaneous modulation and visualization of synaptic events by using optically stimulated synaptic devices based on the heterostructure of fluorescent silicon quantum dots (Si QDs) and monolayer molybdenum disulfide (MoS₂). The charge-transfer-enabled photogating effect of the Si QDs/MoS₂ heterostructure leads to the nonvolatility of the synaptic devices, which exhibit important synaptic functionalities and synchronous fluorescence upon optical stimulation. An array of the Si QDs/MoS₂ optoelectronic synaptic devices is well-employed to mimic robust neural population coding. Defective devices in this array may be pinpointed by the absence of their fluorescence. This work has an important implication for the development of synaptic devices facilitating the system-level diagnosis and device-level positioning of a neuromorphic computing system.

An Electrochemical-Electret Coupled Organic Synapse with Single-Polarity Driven Reversible Facilitation-to-Depression Switching

Neuromorphic engineering and artificial intelligence demands hardware elements that emulates synapse algorithms. During the last decade electrolyte-gated organic conjugated materials have been explored as a platform for artificial synapses for neuromorphic computing. Unlike biological synapses, in current devices the synaptic facilitation and depression are triggered by voltages with opposite polarity. To enhance the reliability and simplify the operation of the synapse without lowering its sophisticated functionality, here, an electrochemical-electret coupled organic synapse (EECS) possessing a reversible facilitation-to-depression switch, is devised. Electret charging counterbalances channel conductance changes due to electrochemical doping, inducing depression without inverting the gate polarity. Overall, EECS functions as a threshold-controlled synaptic switch ruled by its amplitude-dependent, dual-modal operation, which can well emulate information storage and erase as in real synapses. By varying the energy level offset between the channel material and the electret, the EECS's transition threshold can be adjusted for specific applications, e.g., imparting additional light responsiveness to the device operation. The novel device architecture represents a major step forward in the development of artificial organic synapses with increased functional complexity and it opens new perspectives toward the fabrication of abiotic neural networks with higher reliability, efficiency, and endurance.

Wavelength and Polarization Sensitive Synaptic Phototransistor Based on Organic n-type Semiconductor/Supramolecular J-Aggregate Heterostructure

Human retina- and brain-inspired optoelectronic synapses, which integrate light detection and signal memory functions for data processing, have significant interest because of their potential applications for artificial vision technology. In nature, many animals such as mantis shrimp use polarized light information as well as scalar information including wavelength and intensity; however, a spectropolarimetric organic optoelectronic synapse has been seldom investigated. Herein, we report an organic synaptic phototransistor, consisting of a charge trapping liquid-crystalline perylene bisimide J-aggregate and a charge transporting crystalline dichlorinated naphthalene diimide, that can detect both wavelength and polarization information. The device shows persistent positive and negative photocurrents under low and high voltage conditions, respectively. Furthermore, the aligned organic heterostructure in the thin-film enables linearly polarized light to be absorbed with a dichroic ratio of 1.4 and 3.7 under transverse polarized blue and red light illumination, respectively. These features allow polarized light sensitive postsynaptic functions in the device. Consequently, a simple polarization imaging sensor array is successfully demonstrated using photonic synapses, which suggests that a supramolecular material is an important candidate for the development of spectropolarimetric neuromorphic vision systems.

Integration of synaptic phototransistors and quantum dot light-emitting diodes for visualization and recognition of UV patterns

Synaptic photodetectors exhibit photon-triggered synaptic plasticity, which thus can improve the image recognition rate by enhancing the image contrast. However, still, the visualization and recognition of invisible ultraviolet (UV) patterns are challenging, owing to intense background noise. Here, inspired by all-or-none potentiation of synapse, we develop an integrated device of synaptic phototransistors (SPTrs) and quantum dot light-emitting diodes (QLEDs), facilitating noise reduction and visualization of UV patterns through on-device preprocessing. The SPTrs convert noisy UV inputs into a weighted photocurrent, which is applied to the QLEDs as a voltage input through an external current-voltage-converting circuit. The threshold switching characteristics of the QLEDs result in amplified current and visible illumination by the suprathreshold input voltage or nearly zero current and no visible illumination by the input voltage below the threshold. The preprocessing of image data with the SPTr-QLED can amplify the image contrast, which is helpful for high-accuracy image recognition.

Light-Emitting Artificial Synapses for Neuromorphic Computing

As the key connecting points in the neuromorphic computing systems, synaptic devices have been investigated substantially in recent years. Developing optoelectronic synaptic devices with optical outputs is becoming attractive due to many benefits of optical signals in systems. Colloidal quantum dots (CQDs) are potential luminescent materials for information displays. Light-emitting diodes based on CQDs have become appealing candidates for optoelectronic synaptic devices. Moreover, light-emitting transistors exhibit great application potential in these synaptic devices. From this perspective, light-emitting artificial synapses were discussed on the basis of these structures in the devices. Their mechanisms, performance, and future development were analysed and prospected in detail.

Nanofloating gate modulated synaptic organic light-emitting transistors for reconfigurable displays

The use of postsynaptic current to drive long-lasting luminescence holds a disruptive potential for harnessing the next-generation of smart displays. Multiresponsive long afterglow emission can be achieved by integrating light-emitting polymers in electric spiked transistors trigged by distinct presynaptic signals inputs. Here, we report a highly effective electric spiked long afterglow organic light-emitting transistor (LAOLET), whose operation relies on a nanofloating gate architecture. Long afterglow emission with reconfigurable brightness and retention time is observed upon applying specific positive gate voltage spiked. Conversely, when negative gate voltage stimulus is applied, these LAOLETs function as click-on display. Interestingly, upon endowing the device with force sensing capabilities, it can operate as a long afterglow pressure sensor that emits long-lasting green light subsequently to a controlled extrusion action.

Artificial Tactile Sensing System with Photoelectric Output for High Accuracy Haptic Texture Recognition and Parallel Information Processing

Developing multifunctional artificial sensory systems is an important task for constructing future artificial neural networks. A system with multisignal output capability is highly required by the rising demand for high-throughput data processing in the Internet of Things (IoT) society. Here, a novel dual-output artificial tactile sensing (DOATS) system with parallel output of photoelectric signals was proposed. Because of the ionic-electronic coupling mechanism in light-emitting synaptic (LES) devices in the DOATS system, modulating electric current and light emission can coexist through ion accumulation and electron-hole recombination. As a result, the DOATS system can realize the simulation of human tactile information, and the recognition of 16 kinds of fabrics was demonstrated with an accuracy rate of 94.1%. A photoelectric hybrid artificial neural network was proposed, which achieved efficient and accurate multitask operation. The DOATS system proposed in this work is promising for implementing photoelectric hybrid neural network and promoting the development of interactive artificial intelligence.

A robust vertical nanoscaffold for recyclable, paintable, and flexible light-emitting devices

Organic light-emitting devices are key components for emerging opto- and nanoelectronics applications including health monitoring and smart displays. Here, we report a foldable inverted polymer light-emitting diode (iPLED) based on a self-suspended asymmetrical vertical nanoscaffold replacing the conventional sandwich-like structured LEDs. Our empty vertical-yet-open nanoscaffold exhibits excellent mechanical robustness, proven by unaltered leakage current when applying 1000 cycles of 40-kilopascal pressure loading/unloading, sonication, and folding, with the corresponding iPLEDs displaying a brightness as high as 2300 candela per square meter. By using photolithography and brush painting, arbitrary emitting patterns can be generated via a noninvasive and mask-free process with individual pixel resolution of 10 μm. Our vertical nanoscaffold iPLED can be supported on flexible polyimide foils and be recycled multiple times by washing and refilling with a different conjugated polymer capable of emitting light of different color. This technology combines the traits required for the next generation of high-resolution flexible displays and multifunctional optoelectronics.