Results 171 to 180 of about 29,946 (302)

Physics-informed Kolmogorov–Arnold networks to model flow in heterogeneous porous media with a mixed pressure-velocity formulation

Kolmogorov–Arnold networks (KANs), introduced in May 2024, present a novel network structure. Early research shows that they outperform multilayer perceptrons (MLPs) in computational efficiency, interpretability, and interaction.
Hoteit, Hussein, Rao, Xiang, Liu, Yina, He, Xupeng   +3 more
core   +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

Physics-Informed Neural networks for Advanced modeling

Journal of Open Source Software, 2023
Dario Coscia, Anna Ivagnes, Nicola Demo, Gianluigi Rozza   +3 more
openaire   +2 more sources

nPINNS: Nonlocal Physics-Informed Neural Networks.

Proposed for presentation at the SIAM Conference on Computational Science and Engineering (CSE21) held March 1 - February 5, 2021., 2021
Goufei Pang, Marta D'Elia, Michael Parks, George Karniadakis   +3 more
openaire   +2 more sources

Physics-informed machine learning for modeling dynamic electromagnetic systems

reservedNegli ultimi anni, le reti neurali informate dalla fisica (Physics Informed Neural Networks, PINNs) hanno suscitato l'interesse della comunità scientifica per la loro abilità di risolvere equazioni differenziali con modelli di apprendimento ...
BASEI, RICCARDO
core  

Conductive Hydrogels for Exogenous Sensing and Cell Fate Control

Advanced Materials, EarlyView.
We engineer electrically conductive hydrogels by combining sulfated glycosaminoglycans with semiconducting polymers. These hydrogels bind bioactive proteins, including growth factors, whose release or retention can be modulated by low‐voltage stimulation. The hydrogels are also integrated as 3D channels in organic electrochemical transistors as part of
Teuku Fawzul Akbar, Carlos Alejandro Jimenez‐Rodriguez, Railia Biktimirova, Ilka Hermes, Thomas Kurth, My Duyen Pham, Mikhail Tsurkan, Jens Friedrichs, Francis L. C. Morgan, Hans Kleemann, Olga Guskova, Uwe Freudenberg, Peter Fratzl, Carsten Werner, Christoph Tondera, Ivan R. Minev   +15 more
wiley   +1 more source

High‐Performance Transparent, Deformable, and Recoverable Biomimetic Stevia–PVA Hydrogel Triboelectric Nanogenerator with Machine Learning‐Assisted Motion Recognition

Advanced Materials, EarlyView.
A transparent, deformable stevia–PVA hydrogel triboelectric nanogenerator delivers significantly enhanced mechanical strength and electrical output through biomimetic hydrogen‐bonded networks. Coupled with machine learning–assisted signal recognition, the self‐powered hydrogel enables accurate human‐motion sensing for intelligent wearable and IoT ...
Thien Trung Luu, Bui Minh Quang, Toan Minh Pham, Jinsoo Kim, Kyungwho Choi, Dukhyun Choi   +5 more
wiley   +1 more source

Learning variable-order time fractional diffusion equations using Physics-Informed Neural Networks. [PDF]

PLoS One
Ren L, Jin S.
europepmc   +1 more source

Adopting Computational Fluid Dynamics concepts for Physics-Informed Neural Networks

Aerodynamic flows can be described by the compressible Navier-Stokes equations which can be simplified to the compressible Euler equations when neglecting the viscous terms.
Wassing, Simon, Bekemeyer, Philipp, Langer, Stefan   +2 more
core   +1 more source

Advancing Lithium–Oxygen Batteries: Pioneering Cathode Catalyst Innovation and Artificial Intelligence‐Driven Design Paradigms

Advanced Materials, EarlyView.
This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao, Chongyang Hao, Karol Viviana Mejia‐Centeno, Malik Dilshad Khan, Shang Wang, Longqiu Li, Yanhong Tian, Andreu Cabot, Qing Sun   +8 more
wiley   +1 more source