Results 71 to 80 of about 98,087 (266)

The Dynamics of a Continuous Newton-like Method

open access: yes, 2022
The objective of the current work is to invent and introduce the continuous version of Newton’s method. This scheme is used to establish some interesting properties with examples.
Manoj K. Singh, Ioannis K. Argyros
core   +1 more source

Cavity Microelectrode Arrays for Electrical Recordings From Neurons

open access: yesAdvanced Electronic Materials, EarlyView.
Microelectrode arrays (MEAs) are used to study electrophysiological activity. However, their signals are small with high noise. By adding a 100‐nanometer‐high cavity above the electrode, which reduces impedance without affecting resolution, we improve signal quality.
Johannes Lewen   +2 more
wiley   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

open access: yesAdvanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park   +19 more
wiley   +1 more source

Análise e desenvolvimento de metodologias corretivas para a restauração da solução das equações da rede elétrica [PDF]

open access: yes, 2001
Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico.Aborda a análise e o desenvolvimento de metodologias corretivas para a restauração da solução das equações do fluxo de potência de um sistema de energia elétrica.
Barboza, Luciano Vitoria
core  

Trump Tariffs 2.0: Assessing the Impacts on US Distilled Spirits Imports

open access: yesAgribusiness, EarlyView.
ABSTRACT The proposed 25% tariff on Mexico and Canada could have significant repercussions on US imports of distilled spirits. This study estimates US import demand across various spirit categories (e.g., tequila, whiskey) and assesses the potential impact of the proposed tariff.
Andrew Muhammad
wiley   +1 more source

O método de Newton inexato aplicado às equações de Navier-Stokes: Hilbeth Parente de Deus ; orientador, Mário César Zambaldi [PDF]

open access: yes, 2004
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Ciências Físicas e Matemáticas. Programa de Pós-Graduação em Matemática e Computação CientíficaO trabalho aqui presente destina-se a fazer uma análise comparativa, no contexo do ...
Deus, Hilbeth Parente de
core  

A new drag and lift correlation for spherocylinders from fully resolved Immersed Boundary Method

open access: yesAIChE Journal, EarlyView.
Abstract Many industrial processes deal with non‐spherical particles, e.g., mineral mining and biomass conversion. It is crucial to understand the particles' hydrodynamics to control and optimize these processes. To extend the current state‐of‐the‐art from arrays of spherical particles to spherocylindrical particles, we performed extensive particle ...
A. H. Huijgen   +4 more
wiley   +1 more source

Strongly interacting bumps for the schrodinger-newton equations

open access: yes, 2009
We study concentrated bound states of the Schrodinger-Newton equations Moroz, Penrose and Tod proved the existence and uniqueness of ground states.
Winter, M, Wei, J
core  

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas   +4 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

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