Lattice Monte Carlo model of Langmuir evaporation of ABsemiconductors

2019 ◽  
pp. 80-93
Author(s):  
Наталия Львовна Шварц ◽  
Станислав Валерьевич Усенков ◽  
Алла Георгиевна Настовьяк ◽  
Анна Александровна Спирина
Keyword(s):  
Monte Carlo ◽  
Molecular Form ◽  
Monte Carlo Model ◽  
Simulation Method ◽  
Model Parameters ◽  
Vicinal Surfaces ◽  
Equilibrium Pressure ◽  
Software Complex ◽  
Liquid Phases ◽  
Temperature Dependences

Целью работы являлось изучение процессов, протекающих при ленгмюровском испарении подложек полупроводников AB. Предложена и реализована решеточная Монте-Карло модель ленгмюровского испарения GaAs и InAs. Моделирование высокотемпературных отжигов проводилось на базе программного комплекса SilSim3D. В модели учтены процессы образования и диссоциации молекулярного мышьяка и формирования капель металла. Выделены области температур, при которых происходило конгруэнтное и неконгруэнтное испарение. Показано, что температура конгруэнтного испарения на поверхности (111)B ниже, чем на (111)A. На поверхностях (111)А образование капель начиналось вблизи ступеней вицинальных поверхностей, а на (111)B капли образовывались случайным образом на террасах. Purpose. The aim of the work is to study the processes occurring during the Langmuir evaporation of ABsemiconductor substrates. Methodology. The study of GaAs and InAs Langmuir evaporation was performed with the help of Monte Carlo simulation method. Simulation of high-temperature annealing was carried out on the basis of the SilSim3D software complex. The paper presents the abilities of the “Substrate Generator” software complex programs by which the model objects creation and the computing experiments results analysis were carried out. The four-component system, consisting of metal atoms (gallium or indium) in the solid and liquid phases and arsenic in the atomic and molecular form, was considered. The model takes into account the metal droplets formation and the processes of creation and dissociation of molecular arsenic. Each of the processes is characterized by its activation energy. The choice of the model parameters is based on the agreement between simulated and experimental temperature dependences of equilibrium pressure of semiconductor components and arsenic solubility in the liquid metal (gallium, indium) of GaAs and InAs systems over a wide temperature range. Findings. For two surfaces orientations of the model substrates ((111)A and (111)B), the temperatures regions of congruent and incongruent evaporation were determined. It was shown that the temperature of congruent evaporation on the (111)B surface is lower than on (111)A. On the (111)A surfaces, droplet formation starts near the steps of the vicinal surfaces and on (111)B droplets are formed uniformly on the terraces. Value. The obtained model results on the GaAs Langmuir evaporation agree with known experimental data. The results on InAs evaporation leads to the prediction for future experiments.

scholarly journals Designing angle-independent structural colors using Monte Carlo simulations of multiple scattering

2021 ◽  
Vol 118 (4) ◽  
pp. e2015551118
Author(s):  
Victoria Hwang ◽  
Anna B. Stephenson ◽  
Solomon Barkley ◽  
Soeren Brandt ◽  
Ming Xiao ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Multiple Scattering ◽  
Monte Carlo Model ◽  
Experimental System ◽  
Quantitative Agreement ◽  
Spherical Particles ◽  
Target Color ◽  
Model Parameters ◽  
Structural Colors ◽  
Visible Wavelengths

Disordered nanostructures with correlations on the scale of visible wavelengths can show angle-independent structural colors. These materials could replace dyes in some applications because the color is tunable and resists photobleaching. However, designing nanostructures with a prescribed color is difficult, especially when the application—cosmetics or displays, for example—requires specific component materials. A general approach to solving this constrained design problem is modeling and optimization: Using a model that predicts the color of a given system, one optimizes the model parameters under constraints to achieve a target color. For this approach to work, the model must make accurate predictions, which is challenging because disordered nanostructures have multiple scattering. To address this challenge, we develop a Monte Carlo model that simulates multiple scattering of light in disordered arrangements of spherical particles or voids. The model produces quantitative agreement with measurements when we account for roughness on the surface of the film, particle polydispersity, and wavelength-dependent absorption in the components. Unlike discrete numerical simulations, our model is parameterized in terms of experimental variables, simplifying the connection between simulation and fabrication. To demonstrate this approach, we reproduce the color of the male mountain bluebird (Sialia currucoides) in an experimental system, using prescribed components and a microstructure that is easy to fabricate. Finally, we use the model to find the limits of angle-independent structural colors for a given system. These results enable an engineering design approach to structural color for many different applications.

scholarly journals Uncertainty Cost Functions in Climate-Dependent Controllable Loads in Commercial Environments

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2885
Author(s):  
Daniel Losada ◽  
Ameena Al-Sumaiti ◽  
Sergio Rivera
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Method ◽  
Electricity Sector ◽  
Cost Functions ◽  
Density Estimator ◽  
Monte Carlo Simulation Method ◽  
Commercial Building ◽  
Complementary Method ◽  
The Cost

This article presents the development, simulation and validation of the uncertainty cost functions for a commercial building with climate-dependent controllable loads, located in Florida, USA. For its development, statistical data on the energy consumption of the building in 2016 were used, along with the deployment of kernel density estimator to characterize its probabilistic behavior. For validation of the uncertainty cost functions, the Monte-Carlo simulation method was used to make comparisons between the analytical results and the results obtained by the method. The cost functions found differential errors of less than 1%, compared to the Monte-Carlo simulation method. With this, there is an analytical approach to the uncertainty costs of the building that can be used in the development of optimal energy dispatches, as well as a complementary method for the probabilistic characterization of the stochastic behavior of agents in the electricity sector.

scholarly journals Study on Friction in Automotive Shock Absorbers Part 1: Friction Simulation Using a Dynamic Friction Model in the Contact Zone of an FEM Model

Vehicles ◽  
2021 ◽  
Vol 3 (2) ◽  
pp. 212-232
Author(s):  
Ludwig Herzog ◽  
Klaus Augsburg
Keyword(s):  
Ride Comfort ◽  
Viscous Friction ◽  
Simulation Method ◽  
Friction Model ◽  
Model Parameters ◽  
Dynamic Friction ◽  
Friction Modeling ◽  
Shock Absorbers ◽  
Operation Conditions ◽  
Wide Range

The important change in the transition from partial to high automation is that a vehicle can drive autonomously, without active human involvement. This fact increases the current requirements regarding ride comfort and dictates new challenges for automotive shock absorbers. There exist two common types of automotive shock absorber with two friction types: The intended viscous friction dissipates the chassis vibrations, while the unwanted solid body friction is generated by the rubbing of the damper’s seals and guides during actuation. The latter so-called static friction impairs ride comfort and demands appropriate friction modeling for the control of adaptive or active suspension systems. In this article, a simulation approach is introduced to model damper friction based on the most friction-relevant parameters. Since damper friction is highly dependent on geometry, which can vary widely, three-dimensional (3D) structural FEM is used to determine the deformations of the damper parts resulting from mounting and varying operation conditions. In the respective contact zones, a dynamic friction model is applied and parameterized based on the single friction point measurements. Subsequent to the parameterization of the overall friction model with geometry data, operation conditions, material properties and friction model parameters, single friction point simulations are performed, analyzed and validated against single friction point measurements. It is shown that this simulation method allows for friction prediction with high accuracy. Consequently, its application enables a wide range of parameters relevant to damper friction to be investigated with significantly increased development efficiency.

scholarly journals Statistical Analysis of Tritium Breeding Ratio Deviations in the DEMO Due to Nuclear Data Uncertainties

2021 ◽  
Vol 11 (11) ◽  
pp. 5234
Author(s):  
Jin Hun Park ◽  
Pavel Pereslavtsev ◽  
Alexandre Konobeev ◽  
Christian Wegmann
Keyword(s):  
Monte Carlo ◽  
Fusion Reactor ◽  
Nuclear Data ◽  
Data File ◽  
Nuclear Model ◽  
Model Parameters ◽  
Tritium Breeding ◽  
Tritium Breeding Ratio ◽  
Nuclear Data Library ◽  
Breeding Ratio

For the stable and self-sufficient functioning of the DEMO fusion reactor, one of the most important parameters that must be demonstrated is the Tritium Breeding Ratio (TBR). The reliable assessment of the TBR with safety margins is a matter of fusion reactor viability. The uncertainty of the TBR in the neutronic simulations includes many different aspects such as the uncertainty due to the simplification of the geometry models used, the uncertainty of the reactor layout and the uncertainty introduced due to neutronic calculations. The last one can be reduced by applying high fidelity Monte Carlo simulations for TBR estimations. Nevertheless, these calculations have inherent statistical errors controlled by the number of neutron histories, straightforward for a quantity such as that of TBR underlying errors due to nuclear data uncertainties. In fact, every evaluated nuclear data file involved in the MCNP calculations can be replaced with the set of the random data files representing the particular deviation of the nuclear model parameters, each of them being correct and valid for applications. To account for the uncertainty of the nuclear model parameters introduced in the evaluated data file, a total Monte Carlo (TMC) method can be used to analyze the uncertainty of TBR owing to the nuclear data used for calculations. To this end, two 3D fully heterogeneous geometry models of the helium cooled pebble bed (HCPB) and water cooled lithium lead (WCLL) European DEMOs were utilized for the calculations of the TBR. The TMC calculations were performed, making use of the TENDL-2017 nuclear data library random files with high enough statistics providing a well-resolved Gaussian distribution of the TBR value. The assessment was done for the estimation of the TBR uncertainty due to the nuclear data for entire material compositions and for separate materials: structural, breeder and neutron multipliers. The overall TBR uncertainty for the nuclear data was estimated to be 3~4% for the HCPB and WCLL DEMOs, respectively.

Monte Carlo model for describing charge transfer in irradiated CCDs

1998 ◽  
Author(s):  
Dennis J. Gallagher ◽  
Raymond Demara ◽  
Gary Emerson ◽  
Wayne W. Frame ◽  
Alan W. Delamere
Keyword(s):  
Monte Carlo ◽  
Charge Transfer ◽  
Monte Carlo Model

Monte Carlo model of multi-site adsorption

1985 ◽  
Vol 8 (7) ◽  
pp. 364-365 ◽  
Author(s):  
J. Sedláček ◽  
L. Nondek
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Model
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