Results 101 to 110 of about 6,811 (257)

Fluidic memristor: Bringing chemistry to neuromorphic devices. [PDF]

Innovation (Camb), 2023
Xiong T, Li W, Yu P, Mao L.
europepmc   +1 more source

From Lab to Landscape: Environmental Biohybrid Robotics for Ecological Futures

Advanced Robotics Research, EarlyView.
This Perspective explores environmental biohybrid robotics, integrating living tissues, microorganisms, and insects for operation in real‐world ecosystems. It traces the leap from laboratory experiments to forests, wetlands, and urban environments and discusses key challenges, development pathways, and opportunities for ecological monitoring and ...
Miriam Filippi
wiley   +1 more source

An On‐Demand Neuromorphic Vision System Enabled by a Multi‐Paradigm Neuromorphic Device and Hierarchical Reconfigurability Designed from Device to System Level

Advanced Science, EarlyView.
An on‐demand ultra‐reconfigurable intelligent vision system with hierarchical reconfigurability from device to system levels is demonstrated. Through co‐design of a multi‐paradigm device, reconfigurable circuits, and adaptive system architecture/algorithms, the system enables seamless switching among spiking, non‐spiking, neuromorphic imaging (NI), and
Biyi Jiang, Jiayi Xu, Liang Ran, Xinhe Feng, Khalil Harrabi, Yida Li, Longyang Lin, Feichi Zhou   +7 more
wiley   +1 more source

A Pollen‐Enhanced Bionic Mechanoreceptor Induced by Asymmetric Ionic Convection in Hydrogel for Sensory‐Augmented Prostheses

Advanced Science, EarlyView.
This work proposed a pollen‐enhanced bionic mechanoreceptor based on ionic convection. Leveraging the ion anchoring effect of the pollen particle, the output performance could be ∼12 times higher than the original state. By employing deep learning models as AI brains, the feasibility of a sensory‐augmented prosthesis consisting of a pollen‐enhanced ...
Zi Hao Guo, Jingyu Deng, Yanzhang Xu, Chenchen Zhou, Yangshi Shao, Xiong Pu, Munho Kim, Namjoon Cho   +7 more
wiley   +1 more source

Stretchable neuromorphic electronics for future human-integrated intelligence

International Journal of Extreme Manufacturing
Neuromorphic electronics emulate the computational principles of biological neural systems, offering low-power, adaptive, and parallel signal processing capabilities for next-generation intelligent systems.
Tianda Fu, Ruizhe Yang, Max Weires, Junyi Yin, Yifan Liao, Yifan Guo   +5 more
doaj   +1 more source

Resistive Switching Characteristics of Alloyed AlSiO_x Insulator for Neuromorphic Devices. [PDF]

Materials (Basel), 2022
Lee Y, Jang J, Jeon B, Lee K, Chung D, Kim S.   +5 more
europepmc   +1 more source

Polarization‐Enabled Piezoelectric Tellurium–Selenium (TexSe1–x) Thin Films for Memory Switching and Artificial Synaptic Functions

Advanced Science, EarlyView.
Here, we demonstrate and investigate polarization‐enabled electromechanical responses in cryogenic physical vapor deposition (cryogenic PVD)‐deposited TexSe1‐x thin films, a tellurium‐based compound with a tunable bandgap and enhanced non‐centrosymmetry.
Chia‐Chen Chung, Mayur Chaudhary, Chia‐Hung Lo, Po‐Chien Lai, You‐Jie Lin, Ruei‐Hong Cyu, Yu‐Ren Peng, Bing‐Ni Gu, Zhao‐Feng Lou, Quynh Thi Le, Yi‐Jen Yu, Yen‐Fu Lin, Min‐Hung Lee, Ying‐Hao Chu, Chang‐Hong Shen, Der‐Hsien Lien, Yu‐Lun Chueh   +16 more
wiley   +1 more source

Review and outlook on synaptic devices and chips for neuromorphic systems

Gongneng cailiao yu qijian xuebao
As the limitations of traditional von Neumann architecture in handling big data and artificial intelligence applications become increasingly apparent, new computing architectures such as Computing-In-Memory (CIM) and neuromorphic computing have gradually
Sai-ke ZHU, Yi ZHAO
doaj   +1 more source

Synaptic plasticity realized by selective oxidation of TiS₃ nanosheet for neuromorphic devices. [PDF]

RSC Adv, 2023
Qin JK, Sun HL, Huang PY, Li Y, Zhen L, Xu CY.   +5 more
europepmc   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source