Results 141 to 150 of about 6,454,315 (251)

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics

Advanced Materials, EarlyView.
“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair, Hrisheekesh Thachoth Chandran, Karl Leo, Hans Kleemann   +3 more
wiley   +1 more source

Modeling variable density flow in porous media with physics-informed neural networks: Application to seawater intrusion

International audienceModeling variable density flow in porous media with physics-informed neural networks: Application to seawater ...
Lehmann, Francois, Mansouri Bajgiran, Maryam, Younes, Anis, Fahs, Marwan   +3 more
core  

Going with the flow to solve for symmetry-driven PDE dynamics with physics-informed neural networks. [PDF]

Nat Commun
Kavousanakis ME, Fabiani G, Georgiou AS, Siettos C, Kevrekidis PG, Kevrekidis IG.   +5 more
europepmc   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Prediction of wind turbines power with physics-informed neural networks and evidential uncertainty quantification

Publisher Copyright: © 2025 Elsevier Ltd.The ever-growing use of wind energy requires the optimization of turbine operations through pitch angle controllers and early fault detection.
Gómez-Romero, Juan, Gijón, Alfonso, Perea, Eugenio, Pujana-Goitia, Ainhoa, Molina-Solana, Miguel   +4 more
core   +1 more source

Physics-Informed Neural Networks Meet Multimodal Large Language Models: Biomechanical Simulation in Aortic Aneurysm. [PDF]

Cyborg Bionic Syst
Zhu S, Abudupataer M, Wang Y, Zhang H, Lai H, Zhu K, Sun Y, Chen N.   +7 more
europepmc   +1 more source

“Smelltronics”—From Gas to Smell Sensing

Advanced Materials, EarlyView.
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono, Tsunaki Takahashi, Jiangyang Liu, Haruka Honda, Zeng Jing, Wataru Tanaka, Takuro Hosomi, Takeshi Yanagida   +7 more
wiley   +1 more source

Physics-Informed Neural Networks with Hard Linear Equality Constraints

Surrogate modeling is used to replace computationally expensive simulations. Neural networks have been widely applied as surrogate models that enable efficient evaluations over complex physical systems.
Flores, Gonzalo E. Constante, Chen, Hao, Li, Can   +2 more
core  

Fractional Physics Informed Neural Networks for Surrogate Modeling of Non-Markovian Discrete-Time Quantum Walks. [PDF]

Entropy (Basel)
Zhu Z, Liu M, Liang C, Yang F, Shen J, Wen X, Shen L, Wang Y.   +7 more
europepmc   +1 more source