Failure of the “Kick-Out” Model for the Diffusion of Au into Si when Tested by Monte Carlo Simulation

1989 ◽  
Vol 163 ◽  
Author(s):  
U. Schmid ◽  
J. A. Van Vechtent ◽  
N. C. Myers ◽  
U. Koch
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Computer Program ◽  
Computer Simulations ◽  
Large Scale ◽  
Controversial Issue ◽  
Monte Carlo Algorithm ◽  
Atom Level ◽  
Working Out

AbstractWe have performed large scale computer simulations on the controversial issue of Au diffusion into Si at T = 1095° C. Using a Monte Carlo algorithm and a conveniently parametrized set of parameters, our computer program is capable of working out the macroscopic consequences of a variety of models, i.e. atom level assumptions, in an unbiased way and without the approximations introduced in analytic calculations.When applied to the “kick-out” hypothesis, our results are dramatically at odds with the properties claimed by its proponents. Neither the profile of the Au substitutionals, nor the Au-interstitial profiles are in agreement with the analytically obtained results. The discrepancy becomes most pronounced when comparing the variation with time of the Au concentration in the center of the sample, which we find to be linear at all times, in contrast to the alleged t1/2 behavior. Moreover, the Au profile of a one-sided diffusion never becomes U-shaped, as experimentally observed.

scholarly journals Thomson linac-based X-ray generator: a primer for theory and design

2016 ◽  
Vol 34 (4) ◽  
pp. 637-644 ◽  
Author(s):  
I.A. Artyukov ◽  
E.G. Bessonov ◽  
M.V. Gorbunkov ◽  
Y.Y. Maslova ◽  
N.L. Popov ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Laser Radiation ◽  
Conceptual Design ◽  
Large Scale ◽  
State Of The Art ◽  
Thomson Scattering ◽  
Powerful Laser ◽  
X Ray ◽  
X Ray Imaging

AbstractThe paper presents a general theoretical framework and related Monte Carlo simulation of novel type of the X-ray sources based on relativistic Thomson scattering of powerful laser radiation. Special attention is paid to the linac X-ray generators by way of two examples: conceptual design for production of 12.4 keV photons and presently operating X-ray source of 29.4 keV photons. Our analysis shows that state-of-the-art laser and accelerator technologies enable to build up a compact linac-based Thomson source for the same X-ray imaging and diffraction experiments as in using of a large-scale X-ray radiation facility like a synchrotron or Thomson generator based on electron storage ring.

Assessing Curriculum Efficiency Through Monte Carlo Simulation

2018 ◽  
Vol 22 (4) ◽  
pp. 597-610
Author(s):  
David Torres ◽  
Jorge Crichigno ◽  
Carmella Sanchez
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Frequency Distribution ◽  
Relative Frequency ◽  
Monte Carlo Algorithm ◽  
Pass Rate ◽  
Random Numbers ◽  
Pass Rates ◽  
Low Pass ◽  
Relative Frequency Distribution

A Monte Carlo algorithm is designed to predict the average time to graduate by enrolling virtual students in a degree plan. The algorithm can be used to improve graduation rates by identifying bottlenecks in a degree plan (e.g., low pass rate courses and prerequisites). Random numbers are used to determine whether students pass or fail classes by comparing them to institutional pass rates. Courses cannot be taken unless prerequisites and corequisites are satisfied. The output of the algorithm generates a relative frequency distribution which plots the number of students who graduate by semester. Pass rates of courses can be changed to determine the courses that have the greatest impact on the time to graduate. Prerequisites can also be removed to determine whether certain prerequisites significantly affect the time to graduate.

scholarly journals H1 Grid production tool for large scale Monte Carlo simulation

2010 ◽  
Vol 219 (7) ◽  
pp. 072040 ◽  
Author(s):  
B Lobodzinski ◽  
E Bystritskaya ◽  
T M Karbach ◽  
S Mitsyn ◽  
M Mudrinic ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Large Scale

PHASE DIAGRAM OF DOUBLE EXCHANGE MODEL WITH ANTIFERROMAGNETIC COUPLING FOR LOCALIZED t2g SPINS IN ONE DIMENSION REVISITED

2005 ◽  
Vol 19 (24) ◽  
pp. 3731-3743 ◽  
Author(s):  
Q. L. ZHANG
Keyword(s):  
Phase Diagram ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Large Scale ◽  
Double Exchange ◽  
Exchange Model ◽  
One Dimension ◽  
Antiferromagnetic Coupling ◽  
Single Orbit ◽  
Superexchange Coupling

The phase diagram of the single-orbit double exchange model for manganites with ferromagnetic Hund coupling between mobile eg electrons and spins of localized t2g electrons as well as antiferromagnetic superexchange coupling between t2g electrons is investigated with a large scale Monte Carlo simulation in one dimension. The phase boundary is determined based on the internal energy, the electron density and the structure factor. In particular, low-temperature properties at quarter filling are studied in detail.

On the statistics of the linked stress release model

2001 ◽  
Vol 38 (A) ◽  
pp. 176-187 ◽  
Author(s):  
Mark Bebbington ◽  
David S. Harte
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Numerical Analysis ◽  
Large Scale ◽  
Point Processes ◽  
Information Criterion ◽  
Stress Release ◽  
Stress Release Model ◽  
Using Data ◽  
Release Model

The paper reviews the formulation of the linked stress release model for large scale seismicity together with aspects of its application. Using data from Taiwan for illustrative purposes, models can be selected and verified using tools that include Akaike's information criterion (AIC), numerical analysis, residual point processes and Monte Carlo simulation.

Conservative Surrogate Model Using Weighted Kriging Variance for Sampling-Based RBDO

2013 ◽  
Vol 135 (9) ◽  
Author(s):  
Liang Zhao ◽  
K. K. Choi ◽  
Ikjin Lee ◽  
David Gorsich
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Optimum Design ◽  
Surrogate Model ◽  
Large Scale ◽  
Prediction Interval ◽  
Safety Margin ◽  
Probabilistic Constraints ◽  
Kriging Variance ◽  
Better Than

In sampling-based reliability-based design optimization (RBDO) of large-scale engineering applications, the Monte Carlo simulation (MCS) is often used for the probability of failure calculation and probabilistic sensitivity analysis using the prediction from the surrogate model for the performance function evaluations. When the number of samples used to construct the surrogate model is not enough, the prediction from the surrogate model becomes inaccurate and thus the Monte Carlo simulation results as well. Therefore, to count in the prediction error from the surrogate model and assure the obtained optimum design from sampling-based RBDO satisfies the probabilistic constraints, a conservative surrogate model, which is not overly conservative, needs to be developed. In this paper, a conservative surrogate model is constructed using the weighted Kriging variance where the weight is determined by the relative change in the corrected Akaike Information Criterion (AICc) of the dynamic Kriging model. The proposed conservative surrogate model performs better than the traditional Kriging prediction interval approach because it reduces fluctuation in the Kriging prediction bound and it performs better than the constant safety margin approach because it adaptively accounts large uncertainty of the surrogate model in the region where samples are sparse. Numerical examples show that using the proposed conservative surrogate model for sampling-based RBDO is necessary to have confidence that the optimum design satisfies the probabilistic constraints when the number of samples is limited, while it does not lead to overly conservative designs like the constant safety margin approach.

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