Results 171 to 180 of about 18,341 (302)

Mechanically Spatio‐Chimeric Fibrin Assembly Enables Vascular‐Integrated Muscle Reconstruction for Volumetric Muscle Loss Repair

Advanced Materials, EarlyView.
SPARC (spatio‐chimeric, plasma‐based, anisotropic, and shear‐responsive construct) that integrates myogenic and vascular microenvironments within a single construct. The dual‐modulus matrix directs aligned myotube formation and endothelial network development, enabling a vascularized muscle implant that seamlessly anastomoses with host tissue and ...
Su Hyun Jung, Minjun Kim, Da‐Yoon Kim, Min Kyu Kim, Sieun Lee, Yoonhee Jin, Joo H. Kang   +6 more
wiley   +1 more source

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  

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

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

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

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

Forecasting secular variation using physics-informed neural networks for IGRF-14. [PDF]

Earth Planets Space
Shakespeare-Rees N, Livermore PW, Davies CJ, Rogers HF, Beggan CD, Brown WJ, Finlay CC.   +6 more
europepmc   +1 more source

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

Solving the one dimensional vertical suspended sediment mixing equation with arbitrary eddy diffusivity profiles using temporal normalized physics-informed neural networks

Analytical solutions are practical tools in ocean engineering, but their derivation is often constrained by the complexities of the real world. This underscores the necessity for alternative approaches.
Deng, J, Wang, YG, Zhang, S, Jeng, DS, Wu, J, Li, X, Zhao, Z, Li, W   +7 more
core   +1 more source