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Hardware neural networks with mechanical flexibility are promising next‐generation computing systems for smart wearable electronics. Several studies have been conducted on flexible neural networks for practical applications; however, developing systems with complete synaptic plasticity for combinatorial optimization remains challenging. In this study, the metal‐ion injection density is explored as a diffusive parameter of the conductive filament in organic memristors. Additionally, a flexible artificial synapse with bio‐realistic synaptic plasticity is developed using organic memristors that have systematically engineered metal‐ion injections, for the first time. In the proposed artificial synapse, short‐term plasticity (STP), long‐term plasticity, and homeostatic plasticity are independently achieved and are analogous to their biological counterparts. The time windows of the STP and homeostatic plasticity are controlled by the ion‐injection density and electric‐signal conditions, respectively. Moreover, stable capabilities for complex combinatorial optimization in the developed synapse arrays are demonstrated under spike‐dependent operations. This effective concept for realizing flexible neuromorphic systems for complex combinatorial optimization is an essential building block for achieving a new paradigm of wearable smart electronics associated with artificial intelligent systems. Flexible hardware neural networks for complex combinatorial optimization are demonstrated utilizing the organic memristor‐based artificial synapses. In the proposed synapse, metal‐ion injections are systematically engineered, which leads to the bio‐realistic synaptic plasticity. The developed systems are reliably trained and computed for combinatorial optimization such as the complex max‐cut problems.

In this study, we propose an effective strategy for achieving the flexible one organic transistor–one organic memristor (1T–1R) synapse using the multifunctional organic memristor. The dynamics of the conductive nanofilament (CF) in a hydrophobic fluoropolymer medium is explored and a hydrophobic fluoropolymer-based organic memristor is developed. The flexible 1T–1R synapse can be fabricated using the solution process because the hydrophobic fluorinated polymer layer is produced on the organic transistor without degradation of the underlying semiconductor. The developed flexible synapse exhibits multilevel conductance with high reliability and stability because of the fluoropolymer film, which acts as a medium for CF growth and an encapsulating layer for the organic transistor. Moreover, the synapse cell shows potential for high-density memory systems and practical neural networks. This effective concept for developing practical flexible neural networks would be a basic platform to realize the smart wearable electronics.

Organic memristors are promising candidates for the flexible synaptic components of wearable intelligent systems. With heightened concerns for the environment, considerable effort has been made to develop organic transient memristors to realize eco‐friendly flexible neural networks. However, in the transient neural networks, achieving flexible memristors with biorealistic synaptic plasticity for energy efficient learning processes is still challenging. Herein, a biodegradable and flexible polymer‐based memristor, suitable for the spike‐dependent learning process, is demonstrated. An electrochemical metallization phenomenon for the conductive nanofilament growth in a polymer medium of poly (vinyl alcohol) (PVA) is analyzed and a PVA‐based transient and flexible artificial synapse is developed. The developed device exhibits superior biodegradability and stable mechanical flexibility due to the high water solubility and excellent tensile strength of the PVA film, respectively. In addition, the developed flexible memristor is operated as a reliable synaptic device with optimized synaptic plasticity, which is ideal for artificial neural networks with the spike‐dependent operations. The developed device is found to be effectively served as a reliable synaptic component with high energy efficiency in practical neural networks. This novel strategy for developing transient and flexible artificial synapses can be a fundamental platform for realizing eco‐friendly wearable intelligent systems. An interactive preprint version of the article can be found here: https://doi.org/10.22541/au.166603245.58711630/v1. A biodegradable and flexible polymer‐based memristor for eco‐friendly artificial synapses is demonstrated. The developed device exhibits superior biodegradability and mechanical flexibility due to the high water solubility and excellent tensile strength of the polymer, respectively. Moreover, the memristors are operated as reliable synaptic cells with optimized synaptic plasticity, which is ideal for artificial neural networks with high energy efficiency.

In this study, we investigate the bulk effect of photoresponsive gate insulators on the photoresponse of organic phototransistors (OPTs), using OPTs with poly(4-vinylphenol) layers of two different thicknesses. For the photoresponse, the interplay between the charge accumulation (capacitance) and light-absorbance capabilities of a photoresponsive gate insulator was investigated. Although an OPT with a thicker gate insulator exhibits a lower capacitance and hence a lower accumulation capability of photogenerating charges, a thicker poly(4-vinylphenol) layer, in contrast to a thinner one, absorbs more photons to generate more electron–hole pairs, resulting in a higher photoresponse of the device. That is, in these two cases, the degree of light absorption by the photoresponsive gate insulators dominantly governed the photoresponse of the device. Our physical description of the bulk effect of photoresponsive insulators on the performance of OPTs will provide a useful guideline for designing and constructing high-performance organic-based photosensing devices and systems.

Organic synaptic transistors (OSTs) using intrinsic polymer semiconductors are demonstrated to be suitable for neuromorphic bioelectronics. However, diketopyrrolopyrrole (DPP)‐based copolymers are not applicable to neuromorphic computing systems because the DPP polymer film has demonstrated only short‐term plasticity with short retention (<50 ms) in synaptic devices because of their intrinsic difficulty of electrochemical doping. To expand their applications toward neuromorphic computing that requires long‐term plasticity, artificial synapses with extended retention time should be developed. Herein, molecular tailoring approach to extend the retention time in the ion‐gel‐gated OSTs that use DPP is suggested. The molecular structure is controlled by changing alkyl spacer lengths of side chains. As a result, the doping process is more favorable in DPP with long alkyl spacer, which is confirmed by high doping concentration and slow dedoping rate. Therefore, dedoping of ions is more suppressed in DPP with long alkyl side chain that exhibits extended retention time (≈800 s) of the OSTs. These optimized DPP‐based OSTs obtain high pattern recognition accuracy of ≈96.0% in simulations of an artificial neural network. Molecular tailoring strategies provide a guideline to overcome the intrinsic problem of short synaptic retention time of the OSTs for use in neuromorphic computing.

The integration of near-infrared (NIR) light detection with artificial synaptic devices holds immense potential for advancing neuromorphic vision systems, enabling energy-efficient and high-speed data processing beyond conventional von Neumann architectures. NIR wavelengths provide critical information that visible light cannot offer owing to its high permeability and low scattering properties. This capability is particularly valuable for night vision, biomedical imaging, and autonomous sensing applications. However, existing artificial visual systems face challenges such as data transfer bottlenecks and high energy consumption, due to the separation of sensors and processors, as well as the need for digital conversion processes. NIR-responsive artificial synapses address these limitations by integrating NIR optical detection with synaptic computation, mimicking biological neural processing to achieve real-time data integration and adaptive learning. This review provides a comprehensive overview of recent advancements in NIR-detectable artificial synapses. We begin by discussing the fundamental biological synaptic properties essential for artificial synapse operation. Next, we explore the NIR-responsive materials employed in artificial synapses and the principles enabling their synaptic properties, with particular attention to device architectures. Additionally, we examine two practical applications including night vision systems and robotic control systems. Finally, we address the remaining challenges facing the field and propose future research directions for the development of this promising technology.

Solution-processed organic photosynaptic transistors (S-OPTs), inspired by the way biological nervous systems process visual information, offer several advantages such as large bandwidth, low latency, low energy consumption, tunable optoelectronic properties via molecular design, and applicability for simple and low-cost solution process at low temperatures. However, S-OPTs suffer high leakage current with undesirable current pathways, which is unavoidably a result of film formation over the entire substrate during solution processes. Herein, we propose a strategy of improving the photosensitivity of S-OPTs by patterning the organic semiconductor (OSC) film for application in smart and accurate optoelectronic systems. The OSC film of the device is simply patterned through selective evaporation contact printing. The OSC patterns with micrometer scale effectively contribute to reduction in the undesirable current paths and the resultant leakage current. Compared with conventional devices with nonpatterned OSC, our patterned S-OPT exhibits highly improved photosensitivity. Furthermore, our device demonstrates various types of synaptic characteristics, ranging from short- to long-term plasticity. By reducing the off-current level of the OSTs, hardware neural networks built using our patterned cells can successfully achieve recognition accuracy exceeding 90% for recognition of handwritten numerical images, which is comparable to those of ideal software systems. Thus, we believe that this study will introduce new avenues for fabrication of high-photoresponse S-OPTs and their utilization as essential building blocks for construction of neuromorphic systems.

Photonic synapses have attracted increasing interest owing to their ultrafast signal transmission, high bandwidth, and low energy consumption. Dielectrics in organic photonic synaptic transistors (OPSTs) affect the photoinduced charge accumulated at the interface between the dielectrics and organic semiconductor (OSC) layer, modulating a synapse-like behavior. Herein, to investigate the effect of the interfacial properties of polymeric gate insulators on photosensitive synaptic characteristics, two types of polymers, i.e., poly(4-vinylphenol) and poly(styrene), were used as gate dielectrics of OPSTs. We discovered that the functional groups of the polymeric gate dielectrics that induce charge trapping primarily contribute to the synaptic properties of the OPSTs. This result was obtained by analyzing the morphological and physicochemical properties, including surface roughness, surface energy of the insulators, and grain size of the OSC layer on the dielectric layers. Further, the poly(4-vinylphenol)-based OPST with strong interfacial charge-trapping effect showed various synaptic characteristics, such as excitatory postsynaptic currents, paired-pulse facilitation, spike duration-dependent plasticity, spike number-dependent plasticity, and spike rate-dependent plasticity, according to the adjustment of various ultraviolet light information (i.e., exposure duration, number, and rate). In contrast, the poly(styrene)-based OPST did not show synaptic photoresponse. Furthermore, based on the potentiation/depression characteristics of the device, a recognition accuracy of 88% was achieved using handwritten digit recognition designed using datasets from the Modified National Institute of Standards and Technology. Therefore, this study reveals the understanding of the relation between the dielectric/OSC layer and photosensitive synaptic characteristics from the charge-trapping effect. It also provides a strategy for optimizing the photoresponsive synaptic characteristics of OPSTs.

We demonstrate an array of solid-state dye-sensitized solar cells (SS-DSSCs) for a high-voltage power source based on micropatterned titanium dioxide nanoparticles (TNPs) as photoanodes connected in series. The underlying concept of patterning the TNP of a few micrometers thick lies on the combination of the lift-off process of transfer-printed patterns of a sacrificial layer and the soft-cure treatment of the TNP for fixation. This sacrificial layer approach allows for high pattern fidelity and stability, and it enables to construct stable, micrometer-thick, and contamination-free TNP patterns for developing the SS-DSSC array for miniature high-voltage applications. The array of 20 SS-DSSCs integrated in series is found to show a voltage output of around 7 V.

In this study, we developed polymer gate insulator-based organic phototransistors (p-OPTs) with improved optical switching properties by using a hybrid gate insulator configuration. The hybrid gate insulator of our p-OPT has a photoresponsive layer made of poly(4-vinylphenol) (PVP), which enhances the photoresponse, and an interfacial layer of poly(methyl methacrylate) for reliable optical switching of the device. Our hybrid gate insulator-equipped p-OPT exhibits well-defined optical switching characteristics because no specific type of charge is significantly trapped at an interfacial layer/organic semiconductor (OSC) interface. Moreover, our device is more photoresponsive than the conventional p-OPT (here, an OPT with a single-polymer poly(methyl methacrylate) (PMMA) gate insulator), because the characteristic ultraviolet (UV) absorption of the PVP polymer allows the photoresponsive layer and OSC to contribute to the generation of charge carriers when exposed to UV light.