Hydrogel‐Based Artificial Synapses for Sustainable Neuromorphic Electronics DOI Creative Commons
Jiongyi Yan,

James P. K. Armstrong,

Fabrizio Scarpa

et al.

Advanced Materials, Journal Year: 2024, Volume and Issue: 36(38)

Published: Aug. 1, 2024

Hydrogels find widespread applications in biomedicine because of their outstanding biocompatibility, biodegradability, and tunable material properties. can be chemically functionalized or reinforced to respond physical chemical stimulation, which opens up new possibilities the emerging field intelligent bioelectronics. Here, state-of-the-art functional hydrogel-based transistors memristors is reviewed as potential artificial synapses. Within these systems, hydrogels serve semisolid dielectric electrolytes switching layers memristors. These synaptic devices with volatile non-volatile resistive show good adaptability external stimuli for short-term long-term memory effects, some are integrated into arrays neurons; although, there discrepancies performance efficacy. By comparing different respective properties, an outlook provided on a range biocompatible, environment-friendly, sustainable neuromorphic hardware. How energy-efficient information storage processing achieved using neural networks brain-inspired architecture computing described. The development synapses significantly impact fields bionics, biometrics, biosensing.

Language: Английский

Recent Advances and Future Prospects for Memristive Materials, Devices, and Systems DOI
Min‐Kyu Song, Ji‐Hoon Kang, Xinyuan Zhang

et al.

ACS Nano, Journal Year: 2023, Volume and Issue: 17(13), P. 11994 - 12039

Published: June 29, 2023

Memristive technology has been rapidly emerging as a potential alternative to traditional CMOS technology, which is facing fundamental limitations in its development. Since oxide-based resistive switches were demonstrated memristors 2008, memristive devices have garnered significant attention due their biomimetic memory properties, promise significantly improve power consumption computing applications. Here, we provide comprehensive overview of recent advances including devices, theory, algorithms, architectures, and systems. In addition, discuss research directions for various applications hardware accelerators artificial intelligence, in-sensor computing, probabilistic computing. Finally, forward-looking perspective on the future outlining challenges opportunities further innovation this field. By providing an up-to-date state-of-the-art review aims inform inspire

Language: Английский

Citations

129
Porous crystalline materials for memories and neuromorphic computing systems DOI

Guanglong Ding,

Jiyu Zhao,

Kui Zhou

et al.

Chemical Society Reviews, Journal Year: 2023, Volume and Issue: 52(20), P. 7071 - 7136

Published: Jan. 1, 2023

This review highlights the film preparation methods and application advances in memory neuromorphic electronics of porous crystalline materials, involving MOFs, COFs, HOFs, zeolites.

Language: Английский

Citations

94
Reconfigurable Neuromorphic Computing: Materials, Devices, and Integration DOI
Minyi Xu, Xinrui Chen, Yehao Guo

et al.

Advanced Materials, Journal Year: 2023, Volume and Issue: 35(51)

Published: June 7, 2023

Abstract Neuromorphic computing has been attracting ever‐increasing attention due to superior energy efficiency, with great promise promote the next wave of artificial general intelligence in post‐Moore era. Current approaches are, however, broadly designed for stationary and unitary assignments, thus encountering reluctant interconnections, power consumption, data‐intensive that domain. Reconfigurable neuromorphic computing, an on‐demand paradigm inspired by inherent programmability brain, can maximally reallocate finite resources perform proliferation reproducibly brain‐inspired functions, highlighting a disruptive framework bridging gap between different primitives. Although relevant research flourished diverse materials devices novel mechanisms architectures, precise overview remains blank urgently desirable. Herein, recent strides along this pursuit are systematically reviewed from material, device, integration perspectives. At material device level, one comprehensively conclude dominant reconfigurability, categorized into ion migration, carrier phase transition, spintronics, photonics. Integration‐level developments reconfigurable also exhibited. Finally, perspective on future challenges is discussed, definitely expanding its horizon scientific communities.

Language: Английский

Citations

43
A Human‐Computer Interaction Strategy for An FPGA Platform Boosted Integrated “Perception‐Memory” System Based on Electronic Tattoos and Memristors DOI Creative Commons
Yang Li,

Zhicheng Qiu,

Hao Kan

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: 11(39)

Published: July 24, 2024

The integrated "perception-memory" system is receiving increasing attention due to its crucial applications in humanoid robots, as well the simulation of human retina and brain. Here, a Field Programmable Gate Array (FPGA) platform-boosted that enables sensing, recognition, memory for human-computer interaction reported by combination ultra-thin Ag/Al/Paster-based electronic tattoos (AAP) Tantalum Oxide/Indium Gallium Zinc Oxide (Ta

Language: Английский

Citations

40
Roadmap for unconventional computing with nanotechnology DOI Creative Commons
Giovanni Finocchio, Jean Anne C. Incorvia, Joseph S. Friedman

et al.

Nano Futures, Journal Year: 2024, Volume and Issue: 8(1), P. 012001 - 012001

Published: Feb. 15, 2024

Abstract In the ‘Beyond Moore’s Law’ era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At same time, adopting a variety of nanotechnologies offer benefits in energy cost, computational speed, reduced footprint, cyber resilience, and processing power. The time is ripe for roadmap to guide future research, this collection aims fill that need. authors provide comprehensive neuromorphic using electron spins, memristive devices, two-dimensional nanomaterials, nanomagnets, various dynamical systems. They also address other paradigms such as Ising machines, Bayesian inference engines, probabilistic p-bits, memory, quantum memories algorithms, skyrmions spin waves, brain-inspired incremental learning problem-solving severely resource-constrained environments. These have advantages over traditional Boolean based on von Neumann architecture. As requirements artificial intelligence grow 50 times faster than Law electronics, more signal appear horizon, help identify needs challenges. very fertile field, experts field aim present some dominant most promising technologies be around come. Within holistic approach, goal pathways solidifying guiding impactful discoveries.

Language: Английский

Citations

28
2D Magnetic heterostructures: spintronics and quantum future DOI Creative Commons
Bingyu Zhang,

Pengcheng Lu,

Roozbeh Tabrizian

et al.

npj Spintronics, Journal Year: 2024, Volume and Issue: 2(1)

Published: May 30, 2024

Abstract The discovery of two-dimensional (2D) magnetism within atomically thin structures obtained from layered magnetic crystals has opened up a new realm for exploring heterostructures. This emerging field provides foundational platform investigating unique physical properties and exquisite phenomena at the nanometer molecular/atomic scales. By engineering 2D interfaces using methods selecting interlayer interactions, we can unlock potential extraordinary exchange dynamics, which extends to high-performance high-density memory applications, as well future advancements in neuromorphic quantum computing. review delves into recent advances materials, elucidates mechanisms behind interfaces, highlights development devices spintronics information processing. Particular focus is placed on heterostructures with topological properties, promising resilient low-error system. Finally, discuss trends electronics, considering challenges opportunities physics, material synthesis, technological perspectives.

Language: Английский

Citations

24
Organic photoelectrochemical memtransistor DOI Creative Commons
Zheng Li, Qingqing Wu,

M. Chen

et al.

eScience, Journal Year: 2025, Volume and Issue: unknown, P. 100374 - 100374

Published: Jan. 1, 2025

Language: Английский

Citations

6
Two-Dimensional Materials for Brain-Inspired Computing Hardware DOI
Shreyash Hadke, Min‐A Kang,

Vinod K. Sangwan

et al.

Chemical Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 2, 2025

Recent breakthroughs in brain-inspired computing promise to address a wide range of problems from security healthcare. However, the current strategy implementing artificial intelligence algorithms using conventional silicon hardware is leading unsustainable energy consumption. Neuromorphic based on electronic devices mimicking biological systems emerging as low-energy alternative, although further progress requires materials that can mimic function while maintaining scalability and speed. As result their diverse unique properties, atomically thin two-dimensional (2D) are promising building blocks for next-generation electronics including nonvolatile memory, in-memory neuromorphic computing, flexible edge-computing systems. Furthermore, 2D achieve biorealistic synaptic neuronal responses extend beyond logic memory Here, we provide comprehensive review growth, fabrication, integration van der Waals heterojunctions optoelectronic devices, circuits, For each case, relationship between physical properties device emphasized followed by critical comparison technologies different applications. We conclude with forward-looking perspective key remaining challenges opportunities applications leverage fundamental heterojunctions.

Language: Английский

Citations

5
Integrated Memory Devices Based on 2D Materials DOI
Fei Xue, Chenhui Zhang, Yinchang Ma

et al.

Advanced Materials, Journal Year: 2022, Volume and Issue: 34(48)

Published: May 12, 2022

Abstract With the advent of Internet Things and big data, massive data must be rapidly processed stored within a short timeframe. This imposes stringent requirements on memory hardware implementation in terms operation speed, energy consumption, integration density. To fulfill these demands, 2D materials, which are excellent electronic building blocks, provide numerous possibilities for developing advanced device arrays with high performance, smart computing architectures, desirable downscaling. Over past few years, 2D‐material‐based memory‐device different working mechanisms, including defects, filaments, charges, ferroelectricity, spins, have been increasingly developed. These can used to implement brain‐inspired or sensing extraordinary functionalities. Here, recent research into integrated, state‐of‐the‐art devices made from as well their implications surveyed. The existing challenges at array level discussed, scope future is presented.

Language: Английский

Citations

62
2D-Material-Based Volatile and Nonvolatile Memristive Devices for Neuromorphic Computing DOI

Xuwen Xia,

Wen Huang, Pengjie Hang

et al.

ACS Materials Letters, Journal Year: 2023, Volume and Issue: 5(4), P. 1109 - 1135

Published: March 11, 2023

Neuromorphic computing can process large amounts of information in parallel and provides a powerful tool to solve the von Neumann bottleneck. Constructing an artificial neural network (ANN) is common means realize neuromorphic computing, which has exhibited potential applications pattern recognition, complex sensing, other areas. Reservoir (RC), another approach shown some progress attracted researchers' attention. be generally implemented by fabricating memristive array systems. 2D-material-based systems their ANN RC have been investigated substantially recent years due unique properties these systems, such as atomic-level thickness high carrier mobility. In this Review, we first discuss volatility nonvolatility devices RC. Second, 2D materials that used fabricate are introduced, classification, physical properties, preparation methods presented. Third, working mechanisms synaptic devices, mimicked functions, through Lastly, performance, progress, future development directions analyzed. This work systematically investigates status promotes utilization computing.

Language: Английский

Citations

33