Results 231 to 240 of about 1,636,946 (287)

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

Advanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan, Hocheon Yoo, Benoît H. Lessard, Ioannis Kymissis, Chang‐Hyun Kim   +4 more
wiley   +1 more source

Guillain-Barré Syndrome Following Orthopedic Trauma and Surgical Fixation: A Case of Acute Inflammatory Demyelinating Polyradiculoneuropathy. [PDF]

Cureus
Kakade A, Deoke S, Kolse SD, Shaikh FI, Tiwari N.   +4 more
europepmc   +1 more source

Multi‐Level Saturation Current Encoding in Two‐Dimensional Ferroelectric Source‐Gated Transistors

Advanced Functional Materials, EarlyView.
A 2D ferroelectric source‐gated transistor (SGT) operates with a non‐volatile, multi‐level saturation current controlled by ferroelectric polarization. Operando electrostatic and photocurrent imaging link the current limitation to source‐side depletion, identifying saturation current as a programmable, read‐bias‐tolerant device parameter toward low ...
Joon‐Seok Kim, Ting‐Ching Chu, Zhehao Zhu, Lincoln J. Lauhon   +3 more
wiley   +1 more source

Low-Voltage Resistive Switching and Synaptic Plasticity in Cs2AgBiBr6 Memristors. [PDF]

ACS Appl Mater Interfaces
Miao Z, Kadid A, Löwen A, Kolluru N, Tückmantel C, Maschwitz T, Kreusel C, Aziz J, Janicke S, Wu B, Wang P, Riedl T, Neumaier D.   +12 more
europepmc   +1 more source

Engineered Nanotopography to Modulate Growth and Signaling of Neuronal Networks

Advanced Functional Materials, EarlyView.
This study examines the interaction between neurons and nanoscale topographies on engineered substrates. Neurons cultured on nanowires, nanopillars and nanoneedles exhibit enhanced neurite outgrowth, form more organized neuronal circuits, and display improved synaptic connectivity, compared to flat substrates.
Hao Nguyen Tran, Kalyan Shobhana, Zlatan Trifunovic, Dan Smith, Michael Stuiber, Chennupati Jagadish, Mirella Dottori, Andrea J. O'Connor, Vini Gautam   +8 more
wiley   +1 more source

Artificial intelligence in pediatric arrhythmias: current landscape, unique challenges, and translational perspectives. [PDF]

Front Pediatr
Jia H, Zhu W, Lv J.
europepmc   +1 more source

Reservoir‐Driven Neuromorphic Computing Based on Composite Rare‐Earth/Transition Metal Oxide Memristor

Advanced Functional Materials, EarlyView.
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar, Haider Abbas, Muhammad Rabeel, Honggyun Kim, Ghulam Dastgeer, Muhammad Nasim, Furqan Zahoor, Yawar Abbas, Waqas Ahmad, Deok‐kee Kim   +9 more
wiley   +1 more source

Central neural circuits and their associated mechanisms of inter-organ crosstalk. [PDF]

Front Cell Dev Biol
Kang L, Salas-Hernandez JL, Xu R.
europepmc   +1 more source

Multistage, Self‐Sensing Artificial Muscles With Coordination From Liquid Crystal Elastomer‐Graphene Composite Fibers

Advanced Functional Materials, EarlyView.
Inspired by skeletal muscles’ precision and endurance, CoilLCE integrates a self‐sensing liquid crystal elastomer/graphene artificial muscle with an embedded Joule‐heating copper coil, enabling closed‐loop multistage actuation with programmable intermediate states (strain accuracy of 2%), and antagonistic coordination (32% total strain). These features
Ziyun Zhang, Xuelin Wu, Yinding Chi, Qingya Huang, Yaoye Hong, Antonio Proctor Martinez, Jingxian Wu, Bingzhi He, Cynthia Sung, Shu Yang   +9 more
wiley   +1 more source

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source