Multifunctional Organic Materials, Devices, and Mechanisms for Neuroscience, Neuromorphic Computing, and Bioelectronics DOI Creative Commons

Felix L Hoch,

Qishen Wang,

Kian Guan Lim

et al.

Nano-Micro Letters, Journal Year: 2025, Volume and Issue: 17(1)

Published: May 8, 2025

Abstract Neuromorphic computing has the potential to overcome limitations of traditional silicon technology in machine learning tasks. Recent advancements large crossbar arrays and silicon-based asynchronous spiking neural networks have led promising neuromorphic systems. However, developing compact parallel for integrating artificial into hardware remains a challenge. Organic computational materials offer affordable, biocompatible devices with exceptional adjustability energy-efficient switching. Here, review investigates made development organic devices. This explores resistive switching mechanisms such as interface-regulated filament growth, molecular-electronic dynamics, nanowire-confined vacancy-assisted ion migration, while proposing methodologies enhance state retention conductance adjustment. The survey examines challenges faced implementing low-power computing, e.g., reducing device size improving time. analyses these adjustable, flexible, consumption applications, viz. biohybrid circuits interacting biological systems, systems that respond specific events, robotics, intelligent agents, bioelectronics, neuroscience, other prospects this technology.

Language: Английский

Low‐Power and Multimodal Organic Photoelectric Synaptic Transistors Modulated by Photoisomerization for UV Damage Perception and Artificial Visual Recognition DOI Open Access
Jingpeng Wu, Xin Wang, Xian Tang

et al.

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

Citations

0
Microstructure-modulated conductive filaments in Ruddlesden-Popper perovskite-based memristors and their application in artificial synapses DOI
Fu-Chiao Wu, Zhicheng Su, Yu‐Chieh Hsu

et al.

Materials Today Physics, Journal Year: 2025, Volume and Issue: unknown, P. 101708 - 101708

Published: March 1, 2025

Language: Английский

Citations

0
Regulating Charge Distribution to Achieve High‐Performance n‐Type Single‐Component Organic Neuromorphic Phototransistors DOI
Yifan Li,

Yanyan Cao,

Cheng-Yu Wang

et al.

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

Published: April 23, 2025

Abstract Organic optoelectronic devices are advancing toward miniaturization and integration, demanding high performance, low energy consumption, simplified manufacturing. The development of single‐component phototransistors is still in its early stages, particularly for high‐performance n‐type polymer semiconductors. Here, thieno[3,2‐b]thiophene‐3,6‐dicarbonitrile (2CNTT) developed a cyano‐mediated torsion‐polarization synergy strategy proposed to construct conjugated polymers via direct (hetero)arylation polycondensation. This structural modification promotes intramolecular decoupling enhances intermolecular interactions, enabling intra‐/interchain charge distribution be regulated. N‐type copolymers based on 2CNTT exhibited broad visible‐light absorption range small exciton binding energy, capable stable generation stepwise dissociation. PFIID2NTT‐based phototransistor showed unipolar electron mobility strong photoresponse with light‐current/dark‐current ratio as 9.02 × 10 4 , paired‐pulse facilitation index over 236% under visible light. also operate at an ultra‐low consumption (13.23 aJ), mimicking neural synapse behavior long‐term memory functionality. optimizes utilization semiconductors, presenting new paradigm developing multifunctional organic optoelectronics.

Language: Английский

Citations

0
Multifunctional Organic Materials, Devices, and Mechanisms for Neuroscience, Neuromorphic Computing, and Bioelectronics DOI Creative Commons

Felix L Hoch,

Qishen Wang,

Kian Guan Lim

et al.

Nano-Micro Letters, Journal Year: 2025, Volume and Issue: 17(1)

Published: May 8, 2025

Abstract Neuromorphic computing has the potential to overcome limitations of traditional silicon technology in machine learning tasks. Recent advancements large crossbar arrays and silicon-based asynchronous spiking neural networks have led promising neuromorphic systems. However, developing compact parallel for integrating artificial into hardware remains a challenge. Organic computational materials offer affordable, biocompatible devices with exceptional adjustability energy-efficient switching. Here, review investigates made development organic devices. This explores resistive switching mechanisms such as interface-regulated filament growth, molecular-electronic dynamics, nanowire-confined vacancy-assisted ion migration, while proposing methodologies enhance state retention conductance adjustment. The survey examines challenges faced implementing low-power computing, e.g., reducing device size improving time. analyses these adjustable, flexible, consumption applications, viz. biohybrid circuits interacting biological systems, systems that respond specific events, robotics, intelligent agents, bioelectronics, neuroscience, other prospects this technology.

Language: Английский

Citations

0