Results 71 to 80 of about 1,149,889 (365)

Monte Carlo simulation of boson lattices

open access: yes, 2006
Boson lattices are theoretically well described by the Hubbard model. The basic model and its variants can be effectively simulated using Monte Carlo techniques.
Nightingale M. P.   +2 more
core   +1 more source

Consolidate Overview of Ribonucleic Acid Molecular Dynamics: From Molecular Movements to Material Innovations

open access: yesAdvanced Engineering Materials, EarlyView.
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley   +1 more source

Spreadsheet Data Resampling for Monte-Carlo Simulation

open access: yesSpreadsheets in Education, 2008
The pervasiveness of spreadsheet software resulted in its increased application as a simulation tool for business analysis. Random values generation supporting such evaluations using spreadsheets are simple and yet powerful. However, the typical approach
Thin Yin Leong, Wee Leong Lee
doaj  

Monte Carlo simulation of ice models

open access: yes, 1997
We propose a number of Monte Carlo algorithms for the simulation of ice models and compare their efficiency. One of them, a cluster algorithm for the equivalent three colour model, appears to have a dynamic exponent close to zero, making it particularly ...
[H. G. Evertz   +24 more
core   +3 more sources

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

Monte Carlo simulations of a diffusive shock with multiple scattering angular distributions

open access: yes, 2011
We independently develop a simulation code following the previous dynamical Monte Carlo simulation of the diffusive shock acceleration under the isotropic scattering law during the scattering process, and the same results are obtained.
Wang, Xin, Yan, Yihua
core   +1 more source

First‐Principles Modeling of Solid Solution Softening and Hardening Effects in Al–Mg–Zr–Si Aluminum Alloys

open access: yesAdvanced Engineering Materials, EarlyView.
The role of various alloying elements in face‐centered cubic aluminum on the barrier of a Shockley partial dislocation during its motion is presented. The study aims to understand how alloying atoms such as Mg, Si, and Zr affect the energy landscape for dislocation motion, thus influencing the solid solution hardening and softening in aluminum, which ...
Inna Plyushchay   +3 more
wiley   +1 more source

(Nb,Ti)(C,N)‐Precipitates in High‐Strength Low‐Alloyed Steels—Modeling, Characterization and Validation

open access: yesAdvanced Engineering Materials, EarlyView.
Steel samples are investigated using complementary simulations and measurements. Transmission electron microscopy in bright‐field mode, combined with energy‐dispersive X‐ray spectroscopy maps for titanium and niobium, reveals distinct particle populations. Simulations reproduce these in size and composition.
Marc Laub   +3 more
wiley   +1 more source

Monte Carlo simulation of Touschek effect

open access: yesPhysical Review Special Topics. Accelerators and Beams, 2010
We present a Monte Carlo method implementation in the code elegant for simulating Touschek scattering effects in a linac beam. The local scattering rate and the distribution of scattered electrons can be obtained from the code either for a Gaussian ...
Aimin Xiao, Michael Borland
doaj   +1 more source

Monte Carlo simulation of grain growth

open access: yesMaterials Research, 1999
Understanding and predicting grain growth in Metallurgy is meaningful. Monte Carlo methods have been used in computer simulations in many different fields of knowledge. Grain growth simulation using this method is especially attractive as the statistical
Paulo Blikstein   +1 more
doaj   +1 more source

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