Monte Carlo simulation of magnetic properties of irregular Fe islands on Pb/Si(111) substrate based on the scanning tunneling microscopy image

Du, Haifeng; He, Wei; Sun, Dali; Fang, Yang; Liu, Hao-Liang; Zhang, Xiang-Qun; Cheng, Zhao‐Hua

doi:10.1063/1.3377814

Cited by 7 publications

(5 citation statements)

References 21 publications

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“…However, the inclusion of Langevin forces in the nonlinear spin dynamics is not numerically efficient. Therefore we use Monte-Carlo (MC) simulations which allow to study phase transitions in composite multiferroics with strong long-range MD interaction and arbitrary thermal fluctuations [41,42,21,26,24,15,43,44,45,14].…”

Section: Fm Cmentioning

confidence: 99%

Competition of magneto-dipole, anisotropy and exchange interactions in composite multiferroics

Belemuk¹,

Udalov²,

Chtchelkatchev³

et al. 2016

J. Phys.: Condens. Matter

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Abstract. We study the competition of magneto-dipole, anisotropy and exchange interactions in composite three dimensional multiferroics.Using Monte Carlo simulations we show that magneto-dipole interaction does not suppress the ferromagnetic state caused by the interaction of the ferroelectric matrix and magnetic subsystem. However, the presence of magneto-dipole interaction influences the orderdisorder transition: depending on the strength of magneto-dipole interaction the transition from the ferromagnetic to the superparamagnetic state is accompanied either by creation of vortices or domains of opposite magnetization. Unusual temperature hysteresis loop occurs in composite multiferroics due to non-monotonic behavior of exchange interaction vs temperature. The origin of this hysteresis is related to the presence of stable magnetic domains which are robust against thermal fluctuations.

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Section: Fm Cmentioning

confidence: 99%

Competition of magneto-dipole, anisotropy and exchange interactions in composite multiferroics

Belemuk¹,

Udalov²,

Chtchelkatchev³

et al. 2016

J. Phys.: Condens. Matter

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“…The probabilistic approach in geotechnical design has not received much interest, with stimulus from two directions: The mathematical structure of probabilistic approaches is often not appealing to practicing engineers; and the general perception is that probabilistic analysis incurs more time and cost. Early models include the first order second moment (FOSM) from Taylor Series and based on Bayes rule [7,8]; the method did not receive much attention mainly due to its inconsistency with non-linear functions [9]. Monte Carlo simulation in geotechnics was introduced and discussed in a series of seminal works [10,11], with limitations revisited more recently in [12].…”

Section: Risk and Probabilistic Analysis In The Geotechnical Contextmentioning

confidence: 99%

A Probabilistic Approach to the Spatial Variability of Ground Properties in the Design of Urban Deep Excavation

Herridge

Tsiminis²,

Winzen³

et al. 2019

Infrastructures

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Uncertainty in ground datasets often stems from spatial variability of soil parameters and changing groundwater regimes. In urban settings and where engineering ground interventions need to have minimum and well-anticipated ground movements, uncertainty in ground data leads to uncertain analysis, with substantial unwelcomed economical and safety implications. A probabilistic random set finite element modelling (RSFEM) approach is used to revisit the stability and serviceability of a 27 m deep submerged soil nailed excavation built into a cemented soil profile, using a variable water level and soil shear strength. Variation of a suite of index parameters, including mobilized working loads and moments in facing and soil inclusion elements, as well as stability and serviceability of facing and the integrated support system, are derived and contrasted with field monitoring data and deterministic FE modelling outputs. The validated model is then deployed to test the viability of using independent hydraulic actions as stochastic variables as an alternative to dependent hydraulic actions and soil shear strength. The achieved results suggest that utilizing cohesion as a stochastic variable alongside the water level predicts system uncertainty reasonably well for both actions and material response; substituting the hydraulic gradient produces a conservative probability range for the action response only.

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“…The Kinetic Monte Carlo (KMC) method was used to carry out nonequilibrium simulations of dynamical processes for the metal (100) epitaxial growth [13]. Recently, molecular beam epitaxy of the irregular Fe islands grown on Si (111) substrate with Pb buffer layer was investigated by the Monte Carlo (MC) simulation based on the scanning tunneling microscopy image [14]. The MC method is good at simulating equilibrium properties of the model.…”

Section: Introductionmentioning

confidence: 99%

Heteroepitaxial structure of Zn atoms deposit on graphene, Si (001) and graphene/Si (001) substrates for ZnO nanostructure growth

Guo

Shi

et al. 2011

Journal of Crystal Growth

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Monte Carlo simulation of magnetic properties of irregular Fe islands on Pb/Si(111) substrate based on the scanning tunneling microscopy image

Cited by 7 publications

References 21 publications

Competition of magneto-dipole, anisotropy and exchange interactions in composite multiferroics

Competition of magneto-dipole, anisotropy and exchange interactions in composite multiferroics

A Probabilistic Approach to the Spatial Variability of Ground Properties in the Design of Urban Deep Excavation

Heteroepitaxial structure of Zn atoms deposit on graphene, Si (001) and graphene/Si (001) substrates for ZnO nanostructure growth

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