Results 61 to 70 of about 6,504,899 (285)
A deep neural network for general scattering matrix
The scattering matrix is the mathematical representation of the scattering characteristics of any scatterer. Nevertheless, except for scatterers with high symmetry like spheres or cylinders, the scattering matrix does not have any analytical forms and ...
Jing Yongxin +5 more
doaj +1 more source
Ferroelectric nanoclusters create local internal fields in a normally non‐switchable polar film because of polarization mismatch at their interfaces. That field opposes polarization in the regions with larger polarization and reinforces polarization in the regions with smaller polarization.
Anna N. Morozovska +5 more
wiley +1 more source
About gauge equivalent of the generalized Landau-Lifshitz equation
In mathematics an inverse scattering transformation is a method for solving some nonlinear equations with partial derivatives. Discovering of the method became one of the crucial events in mathematical physics in the last 40 years [1]–[6].
Ж. Х. Жунусова +2 more
doaj
AN INVERSE ELECTROMAGNETIC SCATTERING PROBLEM FOR AN ELLIPSOID
The scattering problem of time-harmonic electromagnetic plane waves by an impedance and a dielectric ellipsoid is considered. A low-frequency formulation of the direct scattering problem using the Rayleigh approximation is described. Considering far-field data, an inverse electromagnetic scattering problem is formulated and studied.
Athanasiadou, E.S. +2 more
openaire +2 more sources
Two‐photon grayscale lithography (2GL) enables high‐speed and precise 3D printing of thermolyzed silica glass microstructures with optical‐grade surface quality, high quality factors, and mechanical strength utilizing a custom‐made pre‐glass resist based on polyhedral oligomeric silsesquioxane (POSS) modified with a high‐sensitivity Norrish type II ...
Jonathan L. G. Schneider +4 more
wiley +1 more source
Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery
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 +3 more
wiley +1 more source
Inverse scattering designs of dispersion-engineered single-mode planar waveguides
We use an inverse-scattering (IS) approach to design single-mode waveguides with controlled linear and higher-order dispersion. The technique is based on a numerical solution to the Gelfand-Levitan-Marchenko integral equation, for the inversion of ...
Poletti, F., May, A.R., Zervas, M.N.
core +1 more source
Investigation into a prominent 38 kHz scattering layer in the North Sea [PDF]
The aim of this study was to investigate the composition of an acoustic scattering layer in the North Sea that is particularly strong at 38 kHz. A full definition of the biological composition of the layer, along with its acoustic properties, would allow
Mair, Angus MacDonald
core +2 more sources
An inverse scattering problem for the dielectric ellipsoid
In this work the scattering problem of a time-harmonic electromagnetic plane wave by a dielectric ellipsoid is considered. A low-frequency formulation of the direct scattering problem as well as Rayleigh expansions are described. By using far-field or near-field data the corresponding inverse scattering problem determining both the semiaxes and the ...
Athanasiadis, C. E. +3 more
openaire +2 more sources
Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu +12 more
wiley +1 more source

