Results 51 to 60 of about 7,322 (252)

Low‐Power Computing with Neuromorphic Engineering

Advanced Intelligent Systems, 2021
The increasing power consumption in the existing computation architecture presents grand challenges for the performance and reliability of very‐large‐scale integrated circuits. Inspired by the characteristics of the human brain for processing complicated
Dingbang Liu, Hao Yu, Yang Chai
doaj   +1 more source

Emerging photoelectric devices for neuromorphic vision applications: principles, developments, and outlooks

Science and Technology of Advanced Materials, 2023
The traditional von Neumann architecture is gradually failing to meet the urgent need for highly parallel computing, high-efficiency, and ultra-low power consumption for the current explosion of data.
Yi Zhang, Zhuohui Huang, Jie Jiang
doaj   +1 more source

Anomalous Pressure‐Temperature Ultrahigh Sensitivities in Atomically Engineered Carbonitride MXenes for Multifunctional Wearable Human–Machine Interfaces: Joint Computational–Experimental Elucidations

Advanced Functional Materials, EarlyView.
Atomically engineered layered 2D Ti3CNTz carbonitride MXene exhibits ultrahigh heat and pressure sensitivity, enabling dual‐mode sensors with 300%–400% performance enhancement and durability for real‐time health‐monitoring interface devices. Precise nitrogen incorporation (e.g., Ti3C1.8N0.2Tz) boosts conductivity, enhancing temperature response, while ...
Debananda Mohapatra, Ju‐Hyoung Han, Hyun Jin Kang, Jeong Eun Byun, Seonghun Lee, Sanghyuk Lee, Yeseul Son, Jaeeun Park, Tae Joo Shin, Youngho Kang, Jung Woo Lee, Soon‐Yong Kwon, Soo‐Hyun Kim   +12 more
wiley   +1 more source

2D multifunctional devices: from material preparation to device fabrication and neuromorphic applications

International Journal of Extreme Manufacturing
Neuromorphic computing systems, which mimic the operation of neurons and synapses in the human brain, are seen as an appealing next-generation computing method due to their strong and efficient computing abilities.
Zhuohui Huang, Yanran Li, Yi Zhang, Jiewei Chen, Jun He, Jie Jiang   +5 more
doaj   +1 more source

Recent Progress in Neuromorphic Computing from Memristive Devices to Neuromorphic Chips

Advanced Devices & Instrumentation
Neuromorphic computing, drawing inspiration from the brain, stands out for its high energy efficiency in executing complex tasks. Memristive device-based neuromorphic computing has demonstrated ultrahigh efficiency. While there are numerous review papers
Yike Xiao, Cheng Gao, Juncheng Jin, Weiling Sun, Bowen Wang, Yukun Bao, Chen Liu, Wei Huang, Hui Zeng, Yefeng Yu   +9 more
doaj   +1 more source

Recent Progress of Protein‐Based Data Storage and Neuromorphic Devices

Advanced Intelligent Systems, 2021
By virtue of energy efficiency, high speed, and parallelism, brain‐inspired neuromorphic computing is a promising technology to overcome the von Neumann bottleneck and capable of processing massive sophisticated tasks in the background of big data.
Junjie Wang, Fangsheng Qian, Shenming Huang, Ziyu Lv, Yan Wang, Xuechao Xing, Meng Chen, Su-Ting Han, Ye Zhou   +8 more
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Biologically-Inspired Neuromorphic Computing [PDF]

Science Progress, 2019
Advances in integrated circuitry from the 1950s to the present day have enabled a revolution in technology across the world. However, fundamental limits of circuitry make further improvements through historically successful methods increasingly challenging. It is becoming clear that to address new challenges and applications, new methods of computation
Wilkie Olin-Ammentorp, Nathaniel Cady
openaire   +2 more sources

Optoelectronic Synaptic Devices Using Molecular Telluride Phase‐Change Inks for Three‐Factor Learning

Advanced Functional Materials, EarlyView.
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner, Dhananjeya Kumaar, Giacomo Torti, Killian Keller, Till Zellweger, Florian M. Schenk, Christoph Weilenmann, Daniel Chelladurai, Vara Prasad Jonnalagadda, Ghazi Sarwat Syed, Vanessa Wood, Jürg Leuthold, Alexandros Emboras, Maksym Yarema, Mathieu Luisier   +14 more
wiley   +1 more source

Binding events through the mutual synchronization of spintronic nano-neurons

Nature Communications, 2022
Spin-torque nano-oscillators have sparked interest for their potential in neuromorphic computing, however concrete demonstration are limited. Here, Romera et al show how spin-torque nano-oscillators can mutually synchronise and recognize temporal ...
Miguel Romera, Philippe Talatchian, Sumito Tsunegi, Kay Yakushiji, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Vincent Cros, Paolo Bortolotti, Maxence Ernoult, Damien Querlioz, Julie Grollier   +11 more
doaj   +1 more source

Photon Avalanching Nanoparticles: The Next Generation of Upconverting Nanomaterials?

Advanced Functional Materials, EarlyView.
This Perspective outlines the mechanistic foundations that enable photon‐avalanche (PA) behavior in lanthanide nanomaterials and contrasts them with emerging application spaces and forward‐looking design strategies. By bridging threshold engineering, energy‐transfer dynamics, and materials engineering, we provide a coherent roadmap for advancing the ...
Kimoon Lee, Yunseo Kim, Hyeong‐ku Jo, Dongjoon Yoon, Byeonghyeok Im, WonJeong Yu, Eui‐Rim On, Changhwan Lee   +7 more
wiley   +1 more source