Emerging Artificial Synaptic Devices Based on Organic Semiconductors: Molecular Design, Structure and Applications

ACS Applied Materials & Interfaces, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 9, 2025

In modern computing, the Von Neumann architecture faces challenges such as memory bottleneck, hindering efficient processing of large datasets and concurrent programs. Neuromorphic inspired by brain's architecture, emerges a promising alternative, offering unparalleled computational power while consuming less energy. Artificial synaptic devices play crucial role in this paradigm shift. Various material systems, from organic to inorganic, have been explored for neuromorphic devices, with materials attracting attention their excellent photoelectric properties, diverse choices, versatile preparation methods. Organic semiconductors, particular, offer advantages over transition-metal dichalcogenides, including ease flexibility, making them suitable large-area films. This review focuses on emerging artificial based discussing different branches within semiconductor system, various fabrication methods, device structure designs, applications synapse. Critical considerations achieving truly human-like dynamic perception systems semiconductors are also outlined, reflecting ongoing evolution computing.

Language: Английский

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Ion-Gel Gated Perovskite Field-Effect Transistors with Low Power Consumption and High Stability for Neuromorphic Applications

ACS Applied Materials & Interfaces, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

Ruddlesden–Popper (RP) tin halide perovskites (THPs), exemplified by PEA2SnI4, are promising two-dimensional semiconductors for optoelectronic applications, yet their field-effect transistors (FETs) often suffer from high operating voltages and stability issues. Addressing these challenges, we developed a novel approach integrating ion gel dielectrics composed of PVDF-HFP [EMIM+][TFSI–] with achieving FETs record-low as low 2 V. Additionally, substituting PEA+ BA+ in BA2SnI4 FETs, achieve enhanced device stability, devices exhibiting prolonged functionality exceeding 100 days. Uniform performance was also observed across 30 randomly tested fabricated on inch silicon wafer. These demonstrated synaptic behavior ultralow energy consumption (5 × 10–11 J per operation). Leveraging advancements, constructed artificial neural networks item classification, accuracy (97%). Moreover, the single training process based ion-gel gated is approximately orders magnitude lower than that similar NVIDIA GeForce RTX 4060 GPU. Our results highlight potential low-power, high-stability paving way next generation perovskite-based electronic neuromorphic devices.

Language: Английский

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Organic Synaptic Transistors Based on C8-BTBT/PMMA/PbS QDs for UV to NIR Face Recognition Systems

Nano Letters, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 20, 2025

Developing optoelectronic synaptic devices with low power consumption, broadband response, and biological compatibility is crucial to simulate the functions of optic nerve. Here, an organic synapse transistor based on C8-BTBT/PMMA/PbS quantum dots (PbS QDs) fabricated, which has good stability, consumption (as as 0.49 fJ per event under 800 nm near-infrared optical pulse), response from ultraviolet wavelengths. Based trap release photogenerated carriers by PbS QDs, a series behaviors are simulated device. Furthermore, we use artificial neural network model realize recognition facial feature image in broad spectral range; rate reached 96.25% (350 ultraviolet), 92.14% (580 visible), 90.03% (800 near-infrared). This work beneficial for advancing development future intelligence vision sensing.

Language: Английский

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Low‐Power and Multimodal Organic Photoelectric Synaptic Transistors Modulated by Photoisomerization for UV Damage Perception and Artificial Visual Recognition

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 19, 2025

Abstract Low‐power and efficiently parallel neuromorphic computing is expected to break the bottleneck of von Neumann architecture. Due direct responses optical signals, photonic synaptic devices can work as core components artificial visual systems, accelerating development neural computing. Furthermore, community looking for effective coupling electronic behaviors within an individual organic device achieve further functional integration. Photoisomeric molecules with photo‐regulatable properties are facilitate this process. Herein, photoelectric transistors (OPSTs) constructed by introducing poly(2‐(3′,3′‐dimethyl‐6‐nitrospiro[chromene‐2,2′‐indolin]‐1′‐yl) ethyl methacrylate) (PSPMA) photoisomeric groups, which effectively improves photo‐synaptic response. polarization induction light‐assisted charge trapping PSPMA, OPSTs simulate typical significant conductance modulation at low voltage assistance UV light. The power consumption 84 aJ per event. Moreover, mimic nociceptors, recognize handwritten digits 93.33% accuracy, decode encrypted information, demonstrating potential applications in damage perception recognition. These findings will expand application devices, open up new possibilities hardware architectures synapses.

Language: Английский

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High-performance Flexible Deep Ultraviolet Photodetector Based on Crossed Microwires Heterojunction for Real-time Target Trajectory Tracking System

Nano Energy, Journal Year: 2025, Volume and Issue: unknown, P. 110833 - 110833

Published: March 1, 2025

Language: Английский

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Enhancing the photoelectric synaptic plasticity of β-Ga2O3 films via improving crystalline quality

Journal of Alloys and Compounds, Journal Year: 2025, Volume and Issue: unknown, P. 179771 - 179771

Published: March 1, 2025

Language: Английский

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Responsive Molecules for Organic Neuromorphic Devices: Harnessing Memory Diversification

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: March 26, 2025

In the brain, both recording and decaying of memory information following external stimulus spikes are fundamental learning rules that determine human behaviors. The former is essential to acquire new knowledge update database, while latter filters noise autorefresh cache data reduce energy consumption. To execute these functions, brain relies on different neuromorphic transmitters possessing various kinetics, which can be classified as nonvolatile volatile memory. Inspired by electronic devices have been employed realize artificial neural networks spiking networks, respectively, emerged tools in machine learning. Molecular switches, capable responding electrical, optical, electrochemical, magnetic stimuli, display a disruptive potential for emulating storage devices. This Review highlights recent developments responsive molecules, their interfacing with low-dimensional nanostructures nanomaterials, integration into By capitalizing concepts, unique account neurotransmitter-transfer based molecules ad hoc kinetics provided. Finally, future directions, challenges, opportunities discussed use engineer more complex logic operations computing functions at hardware level.

Language: Английский

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Air‐Stable Hydrogen‐Substituted Graphdiyne/2D Halide Perovskite Heterojunction for Self‐Powered Neuromorphic Vision

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Abstract Neuromorphic visual systems that mimic human vision can efficiently capture and process information with an in‐sensor computing paradigm. However, photoelectronic devices high light sensitivity, stability tunable charge‐carrier interactions are still required for constructing such systems. Herein, a heterojunction of two‐dimensional (2D) hydrogen‐substituted graphdiyne (HsGDY) 2D (BA) 2 PbI 4 perovskite neuromorphic photoelectric sensing processing is demonstrated. The functions as light‐to‐electricity conversion layer, the HsGDY forms layer well‐matched energy bands to allow effective charge injection in at zero‐voltage bias. unique sp‐sp hybridization alkyne bonds thin film provide abundant interactive sites enable efficient processing. device utilized environmentally adaptive experience learning. Excitatory post‐synaptic current (EPSC) gain paired‐pulse facilitation (PPF) index stored ambient air 7 weeks retained 95% 98% initial values. A array fabricated, applicable perceive dynamic information. These results basis future intelligent hardware.

Language: Английский

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Machine‐Learning Enabled Biocompatible Capacitive‐Electromyographic Bimodal Flexible Sensor for Facial Expression Recognition

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 8, 2024

Abstract Single‐mode sensors suffer from poor robustness and insufficient data features in facial expression recognition, so fusing multi‐sensor signals is the key to improving accuracy of recognition systems. Here, a biocompatible capacitive‐electromyographic dual‐mode sensor (CEDS) presented, consisting capacitive pressure sensing unit dry electrodes for electrophysiological signal monitoring, assembled 3D stacking fashion. A double‐coupled microstructure prepared electrical double‐layer effect realized by doping ionic liquid, which significantly improves performance sensor. The application effectively solves problems hydrogel that are prone water loss skin irritation. Besides, good biocompatibility antimicrobial properties CEDS verified through cytotoxicity bacteriostatic tests. Based on single signal, fatigue driving monitoring system manipulator control constructed respectively. By further integrating functions CEDS, 1D convolutional neural network‐assisted constructed, demonstrates great potential systems based flexible technology practical applications.

Language: Английский

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Solution-processed organic/inorganic heterojunction synaptic transistor for neuromorphic computing

Journal of Physics D Applied Physics, Journal Year: 2025, Volume and Issue: 58(13), P. 135110 - 135110

Published: Jan. 24, 2025

Abstract Artificial synaptic devices are the hardware foundation of modern computing systems which have shown great potential in overcoming bottleneck traditional von-Neumann architectures. Organic transistors garnered considerable attention due to their merits, such as low cost, weight, and mechanical flexibility. Various materials utilized for charge-capture layer organic transistors. Indium gallium zinc oxide (IGZO) is a typical metal semiconductor with wide bandgap, high carrier mobility, stable characteristics. Moreover, IGZO an n-type lower highest occupied molecular orbital (HOMO) lowest unoccupied (LUMO) energy level compared p-type semiconductor, has capture material fabricate high-performance devices. However, application trapping received limited attention. Consequently, transistor based on organic/inorganic heterojunction was developed. The impact program/erase time memory performance investigated, revealing that window ratio increased write/erase extended. Additionally, behavior were successfully emulated, including excitatory/inhibitory postsynaptic current, paired-pulse facilitation, depression, high-pass filtering characteristics, transformation short-term plasticity long-term plasticity. Notably, inorganic–organic bilayer achieved recognition accuracy 89.2% using Modified National Institute Standards Technology dataset handwritten digit training. This study provides facile route fabricating transistors, paving way development advanced brain-like computers.

Language: Английский

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