DFT and Monte Carlo study of the structural, mechanical, electronic, magnetic and magnetocaloric properties of the Co2VGa Heusler alloy

2021 ◽  
pp. 139261
Author(s):  
S. Amara ◽  
S. Labidi ◽  
R. Masrour ◽  
A. Jabar ◽  
M. Ellouze
Keyword(s):  
Monte Carlo ◽  
Heusler Alloy ◽  
Monte Carlo Study ◽  
Magnetocaloric Properties

Monte Carlo Study of the Magnetic and Magnetocaloric Properties of La1-xCaxMnO3 (x = 0.33 and 0.5)

2012 ◽  
Vol 190 ◽  
pp. 347-350 ◽  
Author(s):  
O.O. Pavlukhina ◽  
Vasiliy D. Buchelnikov ◽  
V.V. Sokolovskiy ◽  
M.A. Zagrebin
Keyword(s):  
Monte Carlo ◽  
Calcium Ions ◽  
Monte Carlo Study ◽  
Cubic Lattice ◽  
Simple Cubic ◽  
Simple Cubic Lattice ◽  
Magnetocaloric Properties ◽  
Magnetic Ions ◽  
Curie Temperatures ◽  
Good Agreement

In our work the temperature dependencies of magnetization, entropy changes, and the Curie temperature (TC) of La1-xCaxMnO3 (x = 0.33 and 0.5) were investigated using Monte Carlo method and Heisenberg model. In our simulation, magnetic Mn3+ and Mn4+ ions are described by classical Heisenberg spins, while oxygen, lanthanum and calcium ions are considered as non-magnetic. The Mn magnetic ions are distributed on a simple cubic lattice according to the perovskite structure of the manganite. The theoretical Curie temperatures and magnetocaloric values are in a good agreement well with experimental data.

Monte Carlo Study of the Polycrystalline Ni2MnGa Heusler Alloy

2015 ◽  
Vol 233-234 ◽  
pp. 251-254 ◽  
Author(s):  
O.O. Pavlukhina ◽  
V.V. Sokolovskiy ◽  
Vasiliy D. Buchelnikov
Keyword(s):  
Experimental Data ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Single Crystal ◽  
Heusler Alloy ◽  
Theoretical Calculations ◽  
Monte Carlo Study ◽  
Magnetic Domains ◽  
Polycrystalline Structures ◽  
Good Agreement

In this work, we report on the theoretical calculations of the temperature dependence of magnetization in Ni2MnGa alloy by Monte Carlo simulation. The calculations have been carried out for the single crystal and polycrystalline structures with 16, 32 and 64 magnetic domains. The theoretically calculated results are in good agreement with the experimental data.

First-principles and Monte Carlo study of magnetostructural transition and magnetocaloric properties ofNi2+xMn1−xGa

2010 ◽  
Vol 81 (9) ◽  
Author(s):  
V. D. Buchelnikov ◽  
V. V. Sokolovskiy ◽  
H. C. Herper ◽  
H. Ebert ◽  
M. E. Gruner ◽  
...  
Keyword(s):  
Monte Carlo ◽  
First Principles ◽  
Monte Carlo Study ◽  
Magnetostructural Transition ◽  
Magnetocaloric Properties

scholarly journals Monte Carlo study of magnetocaloric properties of Ni-Mn-Ga Heusler alloys

2010 ◽  
Vol 200 (3) ◽  
pp. 032008 ◽  
Author(s):  
V Buchelnikov ◽  
V Sokolovskiy ◽  
S Taskaev ◽  
V Khovaylo ◽  
P Entel
Keyword(s):  
Monte Carlo ◽  
Heusler Alloys ◽  
Monte Carlo Study ◽  
Magnetocaloric Properties

Analyzing Observed Composite Differences Across Groups

Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz
Keyword(s):  
Monte Carlo ◽  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Monte Carlo Study ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Latent Mean Differences ◽  
Partial Invariance ◽  
Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

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