Results 141 to 150 of about 13,642,405 (235)

Retina‐Inspired Bi‐Based Terahertz Photonic Neuromorphic Devices

Advanced Science, EarlyView.
Combined with effective band alignment and substrate engineering, bismuth materials are introduced to form terahertz photonic bio‐inspired devices with picosecond short‐term plasticity to enable multi‐scene visual perception. Thus obtained hardware through the terahertz optical neural network (THz‐ONN) demonstrates high recognition accuracy, providing ...
Pujing Zhang, Donggang Xie, Longyu Shi, Mengyuan Wang, Huiwen Shi, Yu Wu, Menglei Li, Guangwei She, Peijie Wang, Wensheng Shi, Cunlin Zhang, Kuijuan Jin, Guozhen Yang, Qingli Zhou, Chen Ge   +14 more
wiley   +1 more source

Flexoelectricity in Photoconversion: Fundamentals, Materials, and Outlooks

Advanced Science, EarlyView.
Mechanical bending of a flexible cantilever induces a strain gradient in the photoactive material. The resulting flexoelectric field couples with photovoltaic and photoconductive effects, modulating charge generation, separation, and collection. A comparative analysis of oxide perovskites, halide perovskites, and two‐dimensional materials is presented,
Xiang Huang, Feng Li, Rongkun Zheng
wiley   +1 more source

Low-power design of nanometer FPGAs: architecture and EDA

, 2010
Field Programmable Gate Arrays (FPGAs) have become very popular as embedded components on computing platforms. An FPGA is a viable, reprogrammable design approach that provides a fast time-to-market alternative to Application Specific Integrated Circuits
Hassan, Hassan, Anis, Mohab., Anis, Mohab   +2 more
core  

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Neuromorphic computing at scale

Neuromorphic computing is a brain-inspired approach to hardware and algorithm design that efficiently realizes artificial neural networks. Neuromorphic designers apply the principles of biointelligence discovered by neuroscientists to design efficient ...
Majumdar, Amitava, Kubendran, Rajkumar, Bartolozzi, Chiara, Cardwell, Suma George, Gonzalez, Hector A., Hays, Joe, Aimone, James B., Subramoney, Anand, Schuman, Catherine, Buckley, Sonia, Furber, Steve, Mayr, Christian, Orchard, Garrick, Thakur, Chetan Singh, Benosman, Ryad, Pandit, Tej, Payvand, Melika, Merkel, Cory, Young, Cliff, Kudithipudi, Dhireesha, Kulkarni, Shruti, Cauwenberghs, Gert, Vineyard, Craig M.   +22 more
core   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

Neuromorphic Computing for IoT: Ultra-Low Power AI for Real-Time Intelligence

International Journal For Multidisciplinary Research
Neuromorphic computing presents a promising approach for enabling artificial intelligence capabilities in Internet of Things (IoT) devices with stringent power constraints. This paper explores the potential of neuromorphic architectures to deliver ultra-low power AI for real-time intelligence in IoT applications.
openaire   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source

Retinomorphic Visual Processing Enabled by Contact‐Engineered IGZO Optoelectronic Synaptic Memtransistors

Advanced Science, EarlyView.
Here, we present an optoelectronic synaptic memtransistor (OSMT) integrating photoresponsive IGZO with contact‐engineered HfO2, enabling electrically and optically tunable synaptic weights. The device demonstrates broad range of tunable conductance states and array‐level image processing, highlighting its potential for intelligent machine vision ...
Donghyun Kang, San Nam, Dayul Nam, In‐Soo Kim, Myung‐Gil Kim, Sung Kyu Park, Yong‐Hoon Kim   +6 more
wiley   +1 more source

Molecularly Engineered Wing‐Shaped Azobenzene Memristors for Logic‐in‐Memory and Edge Visual Intelligence

Advanced Science, EarlyView.
Rational engineering of terminal substituents in symmetric azobenzene‐based molecules enables precise control over conformationally coupled charge‐transfer processes. This design yields tunable nonvolatile resistive memory behaviors, ranging from write‐once‐read‐many‐times (WORM) to rewritable switching.
Yanze Liu, Tao Han, Jiahui Ding, Hong Lian, Lingling Yao, Zhaoxin Xu, Xingyu Zhang, Shuanglong Wang, Jiangnan Xia, Tianchi Zhang, Weiwei Kang, Qingchen Dong   +11 more
wiley   +1 more source