Results 141 to 150 of about 15,175 (257)
nPINNS: Nonlocal Physics-Informed Neural Networks.
Goufei Pang +3 more
openaire +2 more sources
Optoelectronic Nanofluidic Neural Networks for Ionic Computing
An ion‐based optoelectronic nanofluidic memristor enables neuromorphic computing in aqueous environments. With tunable ionic memory and multimodal synaptic plasticity, it realizes densely connected ionic neural networks capable of image classification, motion prediction, logic computation, and real‐time in‐sensor computing, advancing fully connected ...
Yaxin Huang +10 more
wiley +1 more source
Forecasting secular variation using physics-informed neural networks for IGRF-14. [PDF]
Shakespeare-Rees N +6 more
europepmc +1 more source
Electrically Coded Retinomorphic Spectrophotodetector
Self‐powered retinomorphic pyro‐photodetector is demonstrated that avoids machine‐learning post‐processing and covers 365–940 nm. Electrostatic balancing of built‐in potential produces an electrical wavelength code, delivering <3 nm wavelength decoding accuracy with ∼46 µs response.
Mohit Kumar, Hyunmin Dang, Hyungtak Seo
wiley +1 more source
Implementing physics-informed neural networks with deep learning for differential equations. [PDF]
Emmert-Streib F +3 more
europepmc +1 more source
Organic electrochemical synaptic transistors based on sidechain‐engineered conjugated polyelectrolytes reveal that cationic sidechains enable efficient volumetric ion penetration and dense backbone doping, leading to enhanced transconductance and long‐term synaptic retention.
Haim Kwon +6 more
wiley +1 more source
Peristaltic transport and thermodynamic analysis of hybrid nanofluids in porous media using physics-informed neural networks. [PDF]
Vaseem M, Uddin Z, Upreti H.
europepmc +1 more source
Biointegrated Battery‐Based Electroceuticals
Biointegrated batteries go beyond passive power to serve as active therapeutic platforms for delivering programmable electrical cues and bioactive agents. This review examines their mechanisms and applications and provides a framework to guide battery‐based therapeutic design and clinical translation.
Yan Zhou +6 more
wiley +1 more source
Coupled materials design enables a monolithic fiber that integrates complementary sensing regimes into a single wearable strand. By preserving informative signal features across subtle physiological deformation, large body motion, and mixed mechanical inputs, the dual‐gradient architecture generates synchronized, less redundant outputs that improve ...
Yunheum Lee +13 more
wiley +1 more source
River Surface Velocity and Discharge Estimation Using Optical Flow and Unlabeled Physics-Informed Neural Networks. [PDF]
Shu Z, Gao Y, Zhang G, Xu Z, Wang J.
europepmc +1 more source

