Results 101 to 110 of about 15,175 (257)

A Bioinspired Sensory‐CAPode With Dual Functionality: Logic Gate and Real‐Time Biosensing

Advanced Functional Materials, EarlyView.
An electrochemical capacitor diode (CAPode) redefines the frontier of iontronics by seamlessly unifying logic computing and biosensing within a single biocompatible platform. Inspired by nature's own ion‐channel circuitry, this elegant ionic system transforms complex chemical signals into precise electrical responses, paving the way for next‐generation
Hanfeng Zhou, Tianle Zheng, Haolin Jin, Xiongjun Zhou, Jiang Qu, Bilal Riaz, Ahmed Bahrawy, Jiajie Chen, Przemyslaw Galek, Julia Grothe, Stefan Kaskel   +10 more
wiley   +1 more source

Densely Multiplied Physics Informed Neural Networks

CoRR
15 pages, 9 ...
Feilong Jiang, Xiaonan Hou, Min Xia 0001
openaire   +2 more sources

Mimicking Silent Synapse Recruitment: A SiOx/Cu‐Pancake Memristive Device For Analog Neuromorphic Computing

Advanced Functional Materials, EarlyView.
Electroforming‐free TiN/SiOx/Cu/SiOx/TiN memristive devices exploit pancake‐like Cu nanoparticles embedded in a SiOx double layer to create a heterogeneous Schottky‐barrier landscape. Under bias, oxygen‐vacancy redistribution progressively lowers local barriers and recruits initially inactive Cu‐PC pathways into a parallel conduction ensemble, enabling
Rouven Lamprecht, Ole Gronenberg, Sahitya Yarragolla, Tobias Gergs, Richard Marquardt, Victor Witte, Jürgen Carstensen, George Popkirov, Jan Trieschmann, Lorenz Kienle, Hermann Kohlstedt   +10 more
wiley   +1 more source

Advancing deformation calculation: a physics-informed deep graph learning framework for hyperelastic materials

Advanced Modeling and Simulation in Engineering Sciences
In elastohydrodynamic lubrication (EHL) simulations, classical numerical methods like the finite difference method (FDM) and the finite element method (FEM) are commonly employed. While PINNs have proven to be a suitable alternative for fluid simulation,
Faras Brumand-Poor, Matthias Trautmann, Katharina Schmitz   +2 more
doaj   +1 more source

Dual-Balancing for Physics-Informed Neural Networks

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Physics-informed neural networks (PINNs) have emerged as a new learning paradigm for solving partial differential equations (PDEs) by enforcing the constraints of physical equations, boundary conditions (BCs), and initial conditions (ICs) into the loss function. Despite their successes, vanilla PINNs still suffer from poor accuracy and slow convergence
Chenhong Zhou, Jie Chen 0026, Zaifeng Yang, Ching Eng Png   +3 more
openaire   +2 more sources

Magnesium‐Based Transient Bioelectronics, Bio‐Optics and Bio‐Scaffolds

Advanced Functional Materials, EarlyView.
This paper reviews the state of the art and recent advances in magnesium‐based thin‐film, foils, and scaffolds for applications in transient bio‐optics, bioelectronics and tissue engineering. The design principles, fabrication methods, material properties, and integration strategies are discussed in detail.
Massimo Mariello, Yves Leterrier
wiley   +1 more source

Forecasting seasonal influenza epidemics with physics-informed neural networks

Epidemics
Accurate epidemic forecasting is critical for informing public health decisions and timely interventions. While physics-informed neural networks have shown promise in various scientific domains, their potential application to real-time epidemic ...
Martina Rama, Gabriele Santin, Giulia Cencetti, Michele Tizzoni, Bruno Lepri   +4 more
doaj   +1 more source

Loss-attentional physics-informed neural networks

Journal of Computational Physics
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Song, Y., Wang, H., Yang, H., Taccari, M.L., Chen, X.   +4 more
openaire   +3 more sources

Biodegradable and Biocompatible Functional Polymers for Biomedical Applications

Advanced Functional Materials, EarlyView.
Biodegradable and biocompatible functional polymers integrate electrical, mechanical, and stimuli‐responsive functionalities while enabling programmed degradation under physiological conditions. This review introduces recent advances in conductive, shape‐memory, self‐healing, photocurable, and adhesive polymer systems, emphasizing material design ...
Won Bae Han, Shuvra Mondal, Sungkeun Han, Chan‐Hwi Eom, Venkata Ramesh Naganaboina, Suk‐Won Hwang   +5 more
wiley   +1 more source

M‐ENIAC: A Physics‐Informed Machine Learning Recreation of the First Successful Numerical Weather Forecasts

Geophysical Research Letters
In 1950 the first successful numerical weather forecast was obtained by solving the barotropic vorticity equation using the Electronic Numerical Integrator and Computer (ENIAC), which marked the beginning of the age of numerical weather prediction. Here,
Rüdiger Brecht, Alex Bihlo
doaj   +1 more source