Reconfigurable Neuromorphic Computing Using Methyl-Engineered One-Dimensional Covalent Organic Framework Memristors DOI
Pan‐Ke Zhou, Ziyue Yu, Tao Zeng

и другие.

Nano Letters, Год журнала: 2025, Номер unknown

Опубликована: Март 25, 2025

The rapid evolution of neuromorphic devices seeks to bridge biological neural networks and artificial systems, enabling energy-efficient scalable computing for next-generation intelligence. Herein, we introduce methyl-engineered one-dimensional covalent organic framework (1D COF)-based memristors as a transformative platform reconfigurable computing. incorporation methyl groups enhances localized polarization effects within the COF framework, effectively mitigating random Ag+ migration/diffusion stabilizing conductive filament morphology. This strategic modification yields with exceptional multilevel storage capabilities, exhibiting superior stability, linearity, reproducibility. Moreover, highly ordered architecture customizable chemical environment methyl-functionalized 1D allows precise control over resistive switching behaviors, facilitating emulation synaptic functions development network architectures. Demonstrating performance in tasks such high-accuracy image recognition, these showcase significant promise foundation energy-efficient, systems.

Язык: Английский

Temperature‐Resilient Polymeric Memristors for Effective Deblurring in Static and Dynamic Imaging DOI Creative Commons
Ziyu Lv,

Minghao Jiang,

Huiying Liu

и другие.

Advanced Functional Materials, Год журнала: 2025, Номер unknown

Опубликована: Янв. 24, 2025

Abstract Organic memristors have emerged as promising candidates for neuromorphic computing due to their potential low‐cost fabrication, large‐scale integration, and biomimetic functionality. However, practical applications are often hindered by limited thermal stability device‐to‐device variability. Here, an organic polymer‐based memristor using a thiadiazolobenzotriazole (TBZ) 2,5‐Dioctyl‐3,6‐di(thiophen‐2‐yl)pyrrolo[3,4‐c]pyrrole‐1,4(2H,5H)‐dione (DPP)‐based conjugated polymer is presented that exhibits exceptional reliable resistance switching behavior over wide temperature range (153–573 K). The device leverages charge‐transfer mechanism achieve gradual uniform switching, overcoming the challenges associated with filamentary‐based mechanisms. memristor's consistent performance enable its integration into various applications, including image processing. device's ability demonstrated effectively deblur images, even under varying conditions, showcasing robust computing. This study establishes pathway toward high‐performance, thermally stable advanced artificial intelligence applications.

Язык: Английский

Процитировано

1

MXene Quantum Dots Covalently Modified with Poly[1,4‐diethynylbenzene‐alt‐spiropyran] for Analog‐Type Optoelectronic Dual‐Response Memristor DOI Open Access
Kejia Zhao,

Chenjian Zhang,

Qian Chen

и другие.

Advanced Materials Technologies, Год журнала: 2025, Номер unknown

Опубликована: Фев. 19, 2025

Abstract Quantum dots stand as an outstanding choice for high‐tech applications due to their fascinating edge and quantum confinement effects unique optoelectronic properties. By using 4‐bromobenzenediazonium‐modified MXene a key zero‐dimensional template, highly soluble poly[1,4‐diethynylbenzene‐ alt ‐spiropyran] (PBSP)‐covalently functionalized (PBSP‐MQDs), in which two structural isomers of spiropyran (i.e., ring‐opened merocyanine ring‐closed spiropyran) can interconvert into each other rapidly under different light illumination, are synthesized situ. The weight percentage MQDs PBSP‐MQDs is 10.4%. For comparison purpose, PBSP‐covalently grafted nanosheets (PBSP‐MXene) PBSP also the same conditions. Upon UV or blue these reference materials do not show any memristive effect at sweep range ±0.5 V. On contrary, as‐fabricated ITO/PBSP‐MQDs/ITO device shows history‐dependent switching performance, with 32 distinguishable conductance states, experimental difference current between adjacent conductive states parameters, simple convolutional neural network facial recognition successfully constructed. After 200 epochs training, accuracy reaches up 97.23%.

Язык: Английский

Процитировано

0

Singlet Tetra‐Radical Nickel(II) Complex Based Versatile Molecular Memristor with Adaptive Learning Capability DOI

Subhankar Khanra,

Muhammed Sahad E,

Siuli Das

и другие.

Advanced Functional Materials, Год журнала: 2025, Номер unknown

Опубликована: Фев. 24, 2025

Abstract Molecular memristors have emerged as pivotal components in next‐generation electronics, combining redox‐active functionality at the nanoscale with cognitive behaviors. Synthesis, characterization, and redox‐induced interconversion of a new binuclear open‐shell singlet (S = 0) tetra‐radical nickel(II)‐complex, [Ni II 2 (L •–•– ) ] ( 1 featuring two two‐electron reduced dianionic diradical scaffolds 2,9‐bis(phenyldiazenyl)‐1,10‐phenanthroline L robust resistive switching element is reported. The complex upon one‐electron ligand‐centered oxidation forms mono‐cationic tri‐radical species )(L •– )] + ([ ), which further transforms to di‐cationic monometallic 0 [ 2+ . Controlled reduction presence excess Ni(II)‐sources such NiCl or Ni(ClO 4 mono‐metallic Complex demonstrates exceptional performance molecular memristor, including high endurance over 750 cycles, 2‐h data retention, ultrafast speeds 55 ns. consistent On/Off conductivity difference under varying environmental conditions makes it promising for storage data‐processing applications. Moreover, supports advanced functionalities logic gate operations, 4‐bit edge computing, adaptive learning behavior, positioning versatile building block all‐in‐one electronic technologies.

Язык: Английский

Процитировано

0

Reconfigurable Neuromorphic Computing Using Methyl-Engineered One-Dimensional Covalent Organic Framework Memristors DOI
Pan‐Ke Zhou, Ziyue Yu, Tao Zeng

и другие.

Nano Letters, Год журнала: 2025, Номер unknown

Опубликована: Март 25, 2025

The rapid evolution of neuromorphic devices seeks to bridge biological neural networks and artificial systems, enabling energy-efficient scalable computing for next-generation intelligence. Herein, we introduce methyl-engineered one-dimensional covalent organic framework (1D COF)-based memristors as a transformative platform reconfigurable computing. incorporation methyl groups enhances localized polarization effects within the COF framework, effectively mitigating random Ag+ migration/diffusion stabilizing conductive filament morphology. This strategic modification yields with exceptional multilevel storage capabilities, exhibiting superior stability, linearity, reproducibility. Moreover, highly ordered architecture customizable chemical environment methyl-functionalized 1D allows precise control over resistive switching behaviors, facilitating emulation synaptic functions development network architectures. Demonstrating performance in tasks such high-accuracy image recognition, these showcase significant promise foundation energy-efficient, systems.

Язык: Английский

Процитировано

0