Results 31 to 40 of about 2,985 (242)

Historical Foundation and Practical Guideline for Ferroelectric Switching Kinetic Studies

Advanced Functional Materials, EarlyView.
The P and U pulses in the conventional PUND measurements are not identical because of the interplay between switching current and the measurement circuit components. This circuit effect can lead to a shift in polarization transients and misinterpreted physics in the switching kinetics.
Yi Liang, Pat Kezer, John T. Heron
wiley   +1 more source

Long‐Range Coordination Environment Modulates Single‐Atom Local States and Systemic Impact on CO2 Photoconversion

Advanced Functional Materials, EarlyView.
Terminal groups on Cu porphyrins modulate the electronic states of single‐atom Cu centers through a long‐range electronic effect, without altering the Cu coordination geometry. Meanwhile, a multi‐descriptor framework is established that incorporates porphyrin regulation, hybrid catalyst properties, and CO2 photoreduction capabilities.
Yi Zhang, Jintao Dong, Xiahe Chen, Xiyang Wang, Tiange Wei, Yue Zhu, Tai‐Sing Wu, Yun‐Fang Yang, Shao‐Yuan Leu, Keke Wang, Yuanbin She, Huaming Li, Jiexiang Xia, Molly Meng‐Jung Li   +13 more
wiley   +1 more source

Boundary regularity of stochastic PDEs

, 2019
The boundary behaviour of solutions of stochastic PDEs with Dirichlet boundary conditions can be surprisingly—and in a sense, arbitrarily—bad: as shown by Krylov[ SIAM J. Math.
Gerencser, Mate
core   +1 more source

Topology and Material Optimization in Ultra‐Soft Magneto‐Active Structures: Making Advantage of Residual Anisotropies

Advanced Materials, EarlyView.
Residual magnetization induces pronounced mechanical anisotropy in ultra‐soft magnetorheological elastomers, shaping deformation and actuation even without external magnetic fields. This study introduces a computational‐experimental framework integrating magneto‐mechanical coupling into topology optimization for designing soft magnetic actuators with ...
Carlos Perez‐Garcia, Rogelio Ortigosa, Jesús Martínez‐Frutos, Daniel Garcia‐Gonzalez   +3 more
wiley   +1 more source

Positive Solutions for Dirichlet BVP of PDE Involving \({\varphi_{p}}\)-Laplacian

Fractal and Fractional
In this paper, we investigate the existence of infinitely many small solutions for problem (fφp) involving φp-Laplacian by exploiting critical point theory. Moreover, the present study first attempts to address discrete Dirichlet problems with φp-Laplacian in relation to some relative existing references. As far as we know, this research of the partial
Feng Xiong, Wentao Huang
openaire   +2 more sources

BMO Martingales and Positive Solutions of Heat Equations

, 2015
International audienceIn this paper, we develop a new approach to establish gradient estimates for positive solutions to the heat equation of elliptic or subelliptic operators on Euclidean spaces or on Riemannian manifolds.
Hu, Ying, Qian, Zhongmin
core   +1 more source

Toward Intelligent Multimodal Holography for Real‐Time Chemical Imaging of Dynamic Ion Separation

Advanced Intelligent Discovery, EarlyView.
Intelligent multimodal holography integrates digital off‐axis holography, spectroscopic imaging, and AI‐driven reconstruction to visualize ion transport and chemical dynamics in real time. In this perspective paper, we outline how this approach enables label‐free, chemically specific monitoring of complex environments and discuss its potential to ...
Giovanna Ricchiuti, Sarah I. Allec, Maxim Ziatdinov, Venkateshkumar Prabhakaran   +3 more
wiley   +1 more source

Positive solutions to indefinite problems: a topological approach [PDF]

, 2016
The present Ph.D. thesis is devoted to the study of positive solutions to indefinite problems. In particular, we deal with the second order nonlinear differential equation u'' + a(t) g(u) = 0, where g : [0,+∞[→[0,+∞[ is a continuous nonlinearity and a :
Feltrin, Guglielmo
core  

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Impacts of binary chemical reaction with activation energy on MHD thermally radiating blood based hybrid nanofluid flow through shrinking-stenotic artery: Entropy generation and stability analysis

Hybrid Advances
This study investigates numerically the heat and mass transport with entropy generation of MHD human blood as a hybrid nanofluid at the surface of a porous stenotic shrinking artery in the presence of velocity slip and convective boundary conditions ...
Gopinath Mandal, Dulal Pal
doaj   +1 more source