Results 171 to 180 of about 165,995,511 (248)

Maximum‐Entropy‐Based Meshless Modeling of Surface‐Tension‐Driven Large Deformation

open access: yesInternational Journal for Numerical Methods in Engineering, Volume 127, Issue 17, 15 September 2026.
ABSTRACT Soft material modeling is challenging due, among others, to the substantial structural changes these materials undergo. In this context, meshless methods offer a promising alternative to overcome the limitations of established mesh‐based approximations such as finite elements. However, they introduce new challenges.
Rodrigo Castillo‐Acuna   +2 more
wiley   +1 more source

Hybrid Coupling With Operator Inference and the Overlapping Schwarz Alternating Method

open access: yesInternational Journal for Numerical Methods in Engineering, Volume 127, Issue 17, 15 September 2026.
ABSTRACT This paper presents a hybrid approach for coupling subdomain‐local, nonintrusive Operator Inference (OpInf) reduced order models (ROMs) with each other and with subdomain‐local, high‐fidelity full order models (FOMs) using the overlapping Schwarz alternating method (O‐SAM).
Irina Tezaur   +5 more
wiley   +1 more source

Dynamic Generation of Spatially Variable Vector Beams Using Cascaded Moiré Metasurfaces

open access: yesNanophotonics, Volume 15, Issue 17, 11 September 2026.
A three‐layer cascaded moiré metasurface dynamically generates vector beams with tunable polarization order and controllable lateral focal positions. Relative rotation of the first two layers adjusts the conjugate OAM components that form the vector beam, whereas the third layer steers its focus across the transverse plane, preserving the dominant OAM ...
Siyu Guo   +10 more
wiley   +1 more source

Microring Resonator Dispersion Metrology With Neural Networks

open access: yesNanophotonics, Volume 15, Issue 17, 11 September 2026.
We present a machine learning framework for inverse and forward characterization of microring resonators, inferring geometry and material dispersion from sparse spectral data. The approach achieves nanometer‐scale accuracy and > 99% material identification, while reconstructing full dispersion spectra.
Ergun Simsek   +3 more
wiley   +1 more source

PARSEC.py: A Python‐Based Real‐Space Kohn–Sham Density Functional Theory Code Accelerated by Machine Learned Charge Density

open access: yesJournal of Computational Chemistry, Volume 47, Issue 23, September 5, 2026.
PARSEC.py is a Python‐based real‐space Kohn–Sham DFT framework that leverages the Python scientific ecosystem for transparent, modular integration of machine‐learned densities and GPU acceleration. This unified design enables more efficient and scalable first‐principles simulations of large chemical and materials systems. ABSTRACT PARSEC.py is a Python‐
Zeyi Zhang   +4 more
wiley   +1 more source

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