Memristor‐Based Neuromorphic Chips

Advanced Materials, Journal Year: 2024, Volume and Issue: 36(14)

Published: Jan. 2, 2024

Abstract In the era of information, characterized by an exponential growth in data volume and escalating level abstraction, there has been a substantial focus on brain‐like chips, which are known for their robust processing power energy‐efficient operation. Memristors widely acknowledged as optimal electronic devices realization neuromorphic computing, due to innate ability emulate interconnection information transfer processes witnessed among neurons. This review paper focuses memristor‐based provide extensive description working principle characteristic features memristors, along with applications realm chips. Subsequently, thorough discussion memristor array, serves pivotal component chip, well examination present mainstream neural networks, is delved. Furthermore, design chip categorized into three crucial sections, including synapse‐neuron cores, networks (NoC), network design. Finally, key performance metrics highlighted, related employed realize both synaptic neuronal components.

Language: Английский

---

Technology and Integration Roadmap for Optoelectronic Memristor

Advanced Materials, Journal Year: 2023, Volume and Issue: 36(9)

Published: Sept. 23, 2023

Optoelectronic memristors (OMs) have emerged as a promising optoelectronic Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic devices and systems. These OMs possess range of desirable features including minimal crosstalk, high bandwidth, low power consumption, zero latency, the ability to replicate crucial neurological functions such vision optical memory. By incorporating large-scale parallel synaptic structures, are anticipated greatly enhance high-performance low-power in-memory computing, effectively overcoming limitations von Neumann bottleneck. However, progress in this field necessitates comprehensive understanding suitable structures techniques integrating low-dimensional materials into integrated circuit platforms. This review aims offer overview fundamental performance, mechanisms, design applications, integration roadmap memristors. establishing connections between materials, multilayer memristor units, monolithic circuits, seeks provide insights emerging technologies future prospects that expected drive innovation widespread adoption near future.

Language: Английский

---

A Network Intrusion Detection System with Broadband WO_3–x/WO_3–x‐Ag/WO_3–x Optoelectronic Memristor

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: 34(23)

Published: Jan. 3, 2024

Abstract Real‐time intrusion detection system based on the von Neumann architecture struggle to balance low power consumption and high computing speed. In this work, a strategy for network WO 3–x /WO ‐Ag/WO structured optoelectronic memristor overcoming aforementioned issues is proposed demonstrated. Through modulation of electrical signals, successfully simulates series important synaptic functionalities including short‐term/long‐term plasticity. Meanwhile, when subjected light stimulus, it demonstrates remarkable behaviors in terms long/short‐term memory “learning‐forgetting‐relearning.” Based array, convolutional neural constructed recognize abnormal records within KDDCup‐99 dataset accurately efficiently. The (10 –6 W) over seven orders magnitude lower than that central processing unit, etc. Subsequently, an established integrate collection, processing, real‐time data, classifying various types records. Hence, work expected promote development high‐density storage neuromorphic technology, provides application idea intelligent electronic devices.

Language: Английский

---

High Temperature Resistant Solar‐Blind Ultraviolet Photosensor for Neuromorphic Computing and Cryptography

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: 34(24)

Published: Feb. 7, 2024

Abstract High‐temperature resistant solar‐blind optoelectronic synapse has a significant demand such as aerospace and fire warning, which integrates sensing processing functions to realize complex like learning, recognition, memory. However, developing device remains tremendous challenge. Herein, two‐terminal GaO X with high‐temperature working ability is proposed, it applied neuromorphic computing cryptography. Benefiting from the high internal gain, can detect light intensity of nW cm −2 , displaying one best figures‐of‐merit in photodetectors. Furthermore, possesses remarkable image memorization because its ultrasensitive detection prominent performance resulting large charge trapping states density. Simultaneously, shows undamped photodetection synaptic performances even at 610 K, reflecting endurance desired property for practical applications under harsh environment. Moreover, by constructing an artificial neural network, high‐precision recognition handwritten digits are realized K. A photosynaptic array 12 × pixels constructed, cryptography that enables simultaneous encryption same devices. This work expected drive progress Ga 2 O 3

Language: Английский

---

Flexible Zn‐TCPP Nanosheet‐Based Memristor for Ultralow‐Power Biomimetic Sensing System and High‐Precision Gesture Recognition

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: 34(26)

Published: Feb. 28, 2024

Abstract The flexible biomimetic sensory system inspired by biology exhibits learning, memory, and cognitive behavior toward external stimuli, providing a promising direction for the future development of artificial intelligence industry. In this work, Zn‐TCPP (TCPP: tetrakis (4‐carboxyphenyl) porphyrin) based memristor with ultra‐low both operating voltage (≈80 mV) power consumption (0.39 nW) that simulates typical synaptic plasticities, under continuously adjustable pulses (50 mV). properties are well maintained even when bending 1000 times at radius 5 mm. Furthermore, bionic sensing integrated cotton fibre piezoresistive sensor can remember pressure deformation current, thus simulate learning‐forgetting‐relearning characteristics mechanical stimuli (power supply = 100 Especially, achieves high recognition rate 97% gestures through self‐built datasets neural network calculations remains level influence 10% Gaussian noise (80%) mm state (91%). Consequently, ultralow‐power shows great potential in field multiple modules, paving way low‐power robots future.

Language: Английский

---

2D materials-memristive devices nexus: From status quo to Impending applications

Progress in Materials Science, Journal Year: 2025, Volume and Issue: unknown, P. 101471 - 101471

Published: Feb. 1, 2025

Language: Английский

---

Recent progress in optoelectronic memristors for neuromorphic and in-memory computation

Neuromorphic Computing and Engineering, Journal Year: 2023, Volume and Issue: 3(2), P. 022002 - 022002

Published: May 12, 2023

Abstract Neuromorphic computing has been gaining momentum for the past decades and appointed as replacer of outworn technology in conventional systems. Artificial neural networks (ANNs) can be composed by memristor crossbars hardware perform in-memory storage, a power, cost area efficient way. In optoelectronic memristors (OEMs), resistive switching (RS) controlled both optical electronic signals. Using light synaptic weigh modulator provides high-speed non-destructive method, not dependent on electrical wires, that solves crosstalk issues. particular, artificial visual systems, OEMs act retina combine sensing high-level image processing. Therefore, several efforts have made scientific community into developing meet demands each specific application. this review, recent advances inorganic are summarized discussed. The engineering device structure means to manipulate RS performance and, thus, comprehensive analysis is performed regarding already proposed materials their characteristics. Moreover, potential applications logic gates, ANNs more detail, systems also assessed, taking account figures merit described so far.

Language: Английский

---

Piezo-phototronic effect modulated optoelectronic artificial synapse based on a-Ga2O3/ZnO heterojunction

Nano Energy, Journal Year: 2023, Volume and Issue: 120, P. 109128 - 109128

Published: Nov. 23, 2023

Language: Английский

---

All‐Optically Controlled Retinomorphic Memristor for Image Processing and Stabilization

Advanced Functional Materials, Journal Year: 2023, Volume and Issue: 33(46)

Published: Sept. 1, 2023

Abstract Image stabilization is a crucial field in machine vision, aiming to eliminate image blurring or distortion caused by the camera object jitter. However, traditional techniques often suffer from drawbacks of requiring complex equipment extensive computing resources, resulting inefficiencies. In contrast, human retina performs highly efficient all‐in‐one system, encompassing detection and processing light stimuli. this study, an all‐optically controlled retinomorphic memristor based on Cs x FA y MA 1‐x‐y Pb(I z Br 1‐z ) 3 proposed, which integrates perception, storage, functions. This exhibits significant advantages stabilization. It capable positively negatively modulating its conductance using specific intensities (11.8 0.9 mW cm −2 , respectively) red (630 nm). To demonstrate effectiveness proposed approach, handwritten digit recognition simulations are conducted. The application stimuli effectively highlights characteristics blurred images. processed images then fed into conductance‐mapped neural network for rapid recognition. Remarkably, rates reach 83.5% after 19 000 iterations, surpassing performance (only 56.2% iterations). These results highlight immense potential memristors as hardware foundation next‐generation systems.

Language: Английский

---

Retina‐Like Chlorophyll Heterojunction‐Based Optoelectronic Memristor with All‐Optically Modulated Synaptic Plasticity Enabling Neuromorphic Edge Detection

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

Published: Aug. 5, 2024

Abstract Optoelectronic memristors, which possess the potential capacities of in‐sensor computing, promote development highly efficient neuromorphic vision. In this work, a novel optoelectronic memristor based on chlorophyll (Chl) heterojunction is proposed, consists two types Chl derivatives (zinc methyl 3‐devinyl‐3‐hydroxymethyl‐pyropheophorbide‐ and 13 1 ‐deoxo‐13 ‐dicyanomethylene‐pyropheophorbide‐ ). improves performance device due to its ability efficiently separate photogenerated electron‐hole pairs. The exhibits synaptic potentiation inhibition behaviors under light stimulations 430 730 nm, respectively, thus demonstrating all‐optically modulated plasticity. switching mechanism can be attributed photo‐ionization/deionization oxygen vacancies at zinc oxide (ZnO)/Chl interface. addition, image pre‐processing functions contrast enhancement noise reduction are implemented in memristive array. particular, edge detection function has been by utilizing reversible optical modulation, highlights object outline. proposed here provides promising foundation for advancing

Language: Английский

---