Results 131 to 140 of about 15,175 (257)
Surface Flux Transport Modeling Using Physics-informed Neural Networks
Studying the magnetic field properties on the solar surface is crucial for understanding the solar and heliospheric activities, which in turn shape space weather in the solar system.
Jithu J Athalathil +4 more
doaj +1 more source
We demonstrate a neuromorphic synapse in 2D Fe3GaTe2 flakes. The device operates via a current‐driven transformation from a skyrmion‐lattice to a stripe‐domain state, yielding a linear anomalous Hall resistance response with a tunable slope to enable multiply‐accumulate operations. Simulations confirm its viability in artificial neural networks.
Jixiang Huang +20 more
wiley +1 more source
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 +6 more
wiley +1 more source
Physics-Informed Neural networks for Advanced modeling
Dario Coscia +3 more
openaire +2 more sources
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 +8 more
wiley +1 more source
Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics
“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 +3 more
wiley +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
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 +3 more
wiley +1 more source
Clinically, intermittent hypoxia (IH) is often accompanied by periodontitis, which accelerates cognitive impairment induced by IH. Novel Janus mesoporous gold‐silica nanoformulations (RVG‐Au&mSiO2‐TPP‐VB) enable intranasal delivery, achieve hierarchical targeting to neuronal mitochondria, effectively scavenge reactive oxygen species, inhibit the HIF‐1α/
Kai‐Run Zhang +15 more
wiley +1 more source
A reversible, all‐optical modulation strategy enables resist‐free, sub‐diffraction nanolithography of halide perovskite films. Leveraging 800 nm fs laser‐induced crystallization and 365 nm laser driven decomposition, reconfigurable patterning achieves feature sizes down to 93.5 nm. This chemistry‐free approach offers dynamic control over optoelectronic
Zhengfen Wan +4 more
wiley +1 more source
Learning variable-order time fractional diffusion equations using Physics-Informed Neural Networks. [PDF]
Ren L, Jin S.
europepmc +1 more source

