Materials Science in Semiconductor Processing, Год журнала: 2024, Номер 188, С. 109194 - 109194
Опубликована: Дек. 12, 2024
Язык: Английский
Advanced Materials, Год журнала: 2024, Номер unknown
Опубликована: Май 3, 2024
In the era of artificial intelligence (AI), there is a growing interest in replicating human sensory perception. Selective and sensitive bio-inspired receptors with synaptic plasticity have recently gained significant attention developing energy-efficient AI Various their applications perception are reviewed here. The critical challenges for future development outlined, emphasizing need innovative solutions to overcome hurdles sensor design, integration, scalability. can revolutionize various fields, including human-machine interaction, autonomous systems, medical diagnostics, environmental monitoring, industrial optimization, assistive technologies. As advancements sensing continue accelerate, promise creating more intelligent adaptive systems becomes increasingly attainable, marking step forward evolution human-like
Язык: Английский
Процитировано
15
ACS Applied Electronic Materials, Год журнала: 2025, Номер unknown
Опубликована: Фев. 27, 2025
Self-rectifying organic memristors with integrated biosynaptic functionalities show significant potential for enabling high-density neuromorphic networks by inherently suppressing stealth current effects. In this study, we present a fully solution-processed PEDOT:PSS-based memristor that combines resistive switching and self-rectifying properties. The device features spin-coated PEDOT:PSS as both the top bottom electrodes. To enhance conductivity of film, ethylene glycol was added to spin-coating solution, followed sequential methanol cleaning. are achieved through enhancing redox activity PEDOT transformation ionic PSS within hybrid film. inclusion ZnO nanoparticles (ZnO NPs) significantly enhances performance, resulting in higher on/off ratio sophisticated synaptic behaviors, including transitions from short- long-term plasticity improved linear potentiation depression. This work underscores PEDOT-metal oxide systems foundation advancing computing architectures.
Язык: Английский
Процитировано
1
The Journal of Physical Chemistry Letters, Год журнала: 2024, Номер 15(13), С. 3668 - 3676
Опубликована: Март 27, 2024
Memristor holds great potential for enabling next-generation neuromorphic computing hardware. Controlling the interfacial characteristics of device is critical seamlessly integrating and replicating synaptic dynamic behaviors; however, it commonly overlooked. Herein, we report straightforward oxidation a Mo electrode in air to design MoOx memristors that exhibit nonvolatile ultrafast switching (0.6–0.8 mV/decade, <1 mV/decade) with high on/off ratio (>104), long durability (>104 s), low power consumption (17.9 μW), excellent device-to-device uniformity, ingeniously behavior, finely programmable multilevel analog switching. The analyzed physical mechanism observed resistive behavior might be conductive filaments formed by oxygen vacancies. Intriguingly, upon organization into memristor-based crossbar arrays, addition simulated multipattern memorization, edge detection on random images can implemented well parallel processing pixels using 3 × 2 array Prewitt filter groups. These are vital functions neural system hardware efficient in-memory systems massive parallelism beyond von Neumann architecture.
Язык: Английский
Процитировано
7
Small Methods, Год журнала: 2024, Номер unknown
Опубликована: Июнь 28, 2024
Bionic visual systems require multimodal integration of eye-like photodetectors and brain-like image memory. However, the (PDs) artificial optoelectronic synapses devices (OESDs) by one device remains a giant challenge due to their photoresponse discrepancy. Herein, dual-functional PDs OESDs based on VO
Язык: Английский
Процитировано
6
Materials Today Communications, Год журнала: 2025, Номер unknown, С. 111642 - 111642
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
The Journal of Chemical Physics, Год журнала: 2025, Номер 162(4)
Опубликована: Янв. 22, 2025
In the era of artificial intelligence, there has been a rise in novel computing methods due to increased demand for rapid and effective data processing. It is great significance develop memristor devices capable emulating computational neural network brain, especially realm intelligence applications. this work, based on NiAl-layered double hydroxides presented with excellent electrical performance, including analog resistive conversion characteristics effect multi-level conductivity modulation. addition, device's conductance can be continuously adjusted by varying pulse width, interval, amplitude. The successful replication synaptic features achieved. order implement functions “NOT,” “AND,” “OR,” logic gate constructed using two devices. confirmation potential use brain-like was demonstrated. it demonstrates these supporting models beyond von Neumann architecture.
Язык: Английский
Процитировано
0
The Journal of Physical Chemistry Letters, Год журнала: 2025, Номер unknown, С. 1175 - 1183
Опубликована: Янв. 23, 2025
Research on memristive devices to seamlessly integrate and replicate the dynamic behaviors of biological synapses will illuminate mechanisms underlying parallel processing information storage in human brain, thereby affording novel insights for advancement artificial intelligence. Here, an electric synapse is demonstrated a one-step Mo-selenized MoSe2 memristor, having not only long-term stable resistive switching characteristics (reset 0.51 ± 0.01 V, on/off ratio > 30, retention 103 s) but also diverse electrically adjustable synaptic behaviors, including multilevel conductance (synaptic weight), excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), potentiation/depression (LTP/D), spike-timing-dependent plasticity (STDP), especially activity-dependent (ADSP). More significantly, neuromorphic functions both image edge extraction perception imitation have been successfully achieved. These results present promising design toward advancing systems with integrated brain-like neural sensing, memory, recognition.
Язык: Английский
Процитировано
0
Advanced Functional Materials, Год журнала: 2025, Номер unknown
Опубликована: Фев. 19, 2025
Abstract In this study, a highly rectifying memristor composed of Pt/TaO x /TiN stack, incorporating complementary metal‐oxide semiconductor‐friendly metal oxide switching layer, is fabricated to assess its performance in diverse range applications. The exhibits characteristics due the Schottky barrier formed by work function difference between Pt and TiN electrodes. For compliance current 1 mA, displays volatile memory properties, attributed migration oxygen ions within TaO layer. Leveraging behavior, synaptic functions—where changes plasticity occur response incoming spikes—are emulated. Additionally, complete functions biological nociceptor are demonstrated, including threshold, relaxation, no‐adaptation, sensitization, recovery. These dynamic then utilized mimic neuronal firing with array, Morse code implementation enabling data generation, computing through cost‐effective reservoir computing. simplicity fabrication process broad implemented single make device promising candidate for future
Язык: Английский
Процитировано
0
ACS Applied Electronic Materials, Год журнала: 2025, Номер unknown
Опубликована: Март 26, 2025
Brain-inspired neuromorphic systems have recently garnered significant interest owing to their ability effectively overcome the von Neumann bottleneck increase computing and energy efficiency in era of rapid development artificial intelligence. A hardware neuron with a rectified linear unit (ReLU) activation function is highly desired for introducing nonlinear resolving vanishing gradient problem. In this work, we developed ReLU based on threshold switching memristor (TSM) device Pt/Ag/Al2O3/HfO2/Ag-NIs/Pt structure an ultralow voltage. This realizes by correlating amplitude output spike input voltage, which reported first time. To mitigate potential "dying ReLU" problem that can arise when applied deep spiking neural networks (SNNs), LeakyReLU neuron. Experimental results showed successfully high-integration low-power its variant, neuron, realized digital recognition simulated single-layer fully connected SNN, great significance construction large-scale SNNs future.
Язык: Английский
Процитировано
0
Journal of Alloys and Compounds, Год журнала: 2025, Номер unknown, С. 180469 - 180469
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0