Results 101 to 110 of about 6,454,505 (250)

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

Advanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan, Hocheon Yoo, Benoît H. Lessard, Ioannis Kymissis, Chang‐Hyun Kim   +4 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

Inferring Cosmological Parameters with Evidential Physics-Informed Neural Networks

Universe
We examine the use of a novel variant of Physics-Informed Neural Networks to predict cosmological parameters from recent supernovae and baryon acoustic oscillations (BAO) datasets. Our machine learning framework generates uncertainty estimates for target
Hai Siong Tan
doaj   +1 more source

Bio‐Inspired Artificial Ionic Mechanoreceptor

Advanced Functional Materials, EarlyView.
A skin‐inspired artificial mechanoreceptor based on ionic interactions is presented for biomimetic tactile sensing. Pressure‐driven ionic redistribution within microfluidic channels generates a self‐powered electrical signal without external bias. The generated waveform exhibits mechanoreceptor‐like temporal features, including overshoot and undershoot,
Mohammad Akbari, Jeppe Don, Lasse A. N. Pedersen, John Noee, Rassoul Tabassian   +4 more
wiley   +1 more source

Reservoir‐Driven Neuromorphic Computing Based on Composite Rare‐Earth/Transition Metal Oxide Memristor

Advanced Functional Materials, EarlyView.
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar, Haider Abbas, Muhammad Rabeel, Honggyun Kim, Ghulam Dastgeer, Muhammad Nasim, Furqan Zahoor, Yawar Abbas, Waqas Ahmad, Deok‐kee Kim   +9 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

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
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

Electrical‐Programming‐Free Neural Crossbars Enabled by Photochemical Weight Patterning

Advanced Functional Materials, EarlyView.
A flexible neural‐crossbar hardware system enabled by electrical‐programming‐free, mask‐defined, array‐parallel photochemical weight patterning is demonstrated. Trained weights are physically implemented across the array, supporting multilevel programming, bending‐stable operation and reconfiguration, substrate reuse, and low‐energy readout while ...
Hyo‐Bin Jang, Ji‐Hoon Choi, Juhyung Seo, Seungwoo Baek, Hocheon Yoo, Hea‐Lim Park   +5 more
wiley   +1 more source

Applied Physics-Informed Neural Networks for Spacecraft Magnetic Testing

Aerospace
Artificial intelligence and machine learning techniques can be used for performing magnetic testing on spacecraft that has historically been difficult and risky to perform.
Andrew Mentges, Bharat Rawal
doaj   +1 more source