Results 101 to 110 of about 16,533 (261)

Multimodal Perception and Machine Learning‐Empowered Human Machine Interfaces With Double‐Network Hydrogel Fibers

Advanced Functional Materials, EarlyView.
This work develops polyacrylamide‐alginate (PAM‐Alg) double‐network hydrogel fibers for multimodal perception and intelligent human‐machine interfaces. The covalent‐ionic network provides high strength, toughness, and stable conductivity. Easily woven into wearables and integrated with soft robots, the fibers enable object and temperature recognitions ...
Yujue Yang, Minyu Qiu, Di Tan, Xinlong Liu, Junze Zhang, Ziyu He, Jing Han, Yuanyuan Gao, Zihua Li, Hong Fu, Bingang Xu   +10 more
wiley   +1 more source

ST-GPINN: a spatio-temporal graph physics-informed neural network for enhanced water quality prediction in water distribution systems

npj Clean Water
Data-driven models often neglect the underlying physical principles, limiting generalization capabilities in water distribution systems (WDSs). This study presents a novel spatio-temporal graph physics-informed neural network (ST-GPINN) for water quality
Tianwei Mu, Feiyu Duan, Baokuan Ning, Bo Zhou, Junyu Liu, Manhong Huang   +5 more
doaj   +1 more source

Densely Multiplied Physics Informed Neural Networks

CoRR
15 pages, 9 ...
Feilong Jiang, Xiaonan Hou, Min Xia 0001
openaire   +2 more sources

Electro‐Steric Ion Confinement in Polyelectrolyte Networks for Robust Nonvolatile Artificial Synapse

Advanced Functional Materials, EarlyView.
Polyelectrolyte stoichiometry governs ion transport and retention in electrolyte‐gated synaptic transistors. A PSS‐rich network creates electro‐steric ion confinement that suppresses ion back‐diffusion and stabilizes channel doping, enabling robust nonvolatile synaptic memory, linear weight updates, and low‐energy operation.
Donghwa Lee, Jinbo Kim, Myeongjin An, Jisoo Park, Junho Sung, Eunsung Hwang, Suhwan Seok, Seong‐Min Bak, Jeonghun Kim, Eunho Lee   +9 more
wiley   +1 more source

Physics-Informed Neural Network for Solving a One-Dimensional Solid Mechanics Problem

Modelling
Our objective in this work is to demonstrate how physics-informed neural networks, a type of deep learning technology, can be utilized to examine the mechanical properties of a helicopter blade.
Vishal Singh, Dineshkumar Harursampath, Sharanjeet Dhawan, Manoj Sahni, Sahaj Saxena, Rajnish Mallick   +5 more
doaj   +1 more source

Dual-Balancing for Physics-Informed Neural Networks

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Physics-informed neural networks (PINNs) have emerged as a new learning paradigm for solving partial differential equations (PDEs) by enforcing the constraints of physical equations, boundary conditions (BCs), and initial conditions (ICs) into the loss function. Despite their successes, vanilla PINNs still suffer from poor accuracy and slow convergence
Chenhong Zhou, Jie Chen 0026, Zaifeng Yang, Ching Eng Png   +3 more
openaire   +2 more sources

Solution‐Processed Thin‐Film Transistors With Tunable Temporal Dynamics for Neuromorphic Computing

Advanced Functional Materials, EarlyView.
Solution‐processed CNT and CNT/P3HT ion‐gated transistors exhibit materials‐defined synaptic timescales: fast CNT devices for high‐frequency spiking and slow hybrid devices for temporal integration. Embedding these dynamics into coupled reservoir‐computing and spiking neural network simulations reveals that a Hybrid‐Reservoir / CNT‐SNN architecture ...
Kevin Schnittker, Haoyi Lin, Zahra Bahrami, Strahinja Marinkovic, Sung Hyun Lee, Joseph Andrews   +5 more
wiley   +1 more source

Loss-attentional physics-informed neural networks

Journal of Computational Physics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Song, Y., Wang, H., Yang, H., Taccari, M.L., Chen, X.   +4 more
openaire   +3 more sources

Oxidized MoS2‐Based Multifunctional Memristive Hardware for Energy‐Efficient mmWave Signal Processing and In‐Memory Matrix Multiplication

Advanced Functional Materials, EarlyView.
Thermally oxidized MoS2‐based radio‐frequency switches enable a multifunctional platform that unifies broadband RF switching and in‐memory computation. The device achieves a cutoff frequency of 33.2 THz with high energy efficiency and supports hardware‐aware signal processing.
Juho Son, Changwoo Pyo, Sungmoon Park, Yoongi Cho, Seungchan Lee, Myungsoo Kim   +5 more
wiley   +1 more source

Multifunctional Gold Nanocluster‐Based PROTAC System for Targeted Degradation of Phosphorylated Tau and Modulation of Neuroinflammation in Alzheimer's Disease

Advanced Functional Materials, EarlyView.
We present a novel proteolysis‐targeting chimera (PROTAC) system conjugated to lipoic acid gold nanoclusters (PLANC), designed to degrade pTau, regulate inflammatory signaling, and effectively traverse the blood‐brain barrier (BBB). PLANC degraded pTau at various phosphorylation sites, with mechanistic studies confirming proteasome‐mediated degradation
Sarah Nevins, Callan D. McLoughlin, Wan‐Kyu Ko, Hye Kyu Choi, Brandon Conklin, Joshua B. Stein, Yannan Hou, Hongwon Kim, Rohan Khulbe, Ki‐Bum Lee   +9 more
wiley   +1 more source