Monte-Carlo Simulation of Generation- Recombination Noise in Amorphous Semiconductors

2002 ◽  
Vol 715 ◽  
Author(s):  
R.I. Badran ◽  
C. Main ◽  
S. Reynolds
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Noise Spectrum ◽  
Amorphous Semiconductors ◽  
Analytical Models ◽  
Release Time ◽  
Trapping Time ◽  
Extended States ◽  
Gap States ◽  
Analytical Approaches

AbstractWe compare the predictions of several analytical models for conductivity fluctuations in a homogeneous semiconductor containing discrete and distributed traps, using a Monte-Carlo simulation of the relevant multi – trapping (MT) transitions. The simulation directly embodies the statistical features associated with such processes, in a simple ‘model - independent’ approach, free of approximations and assumptions. We compare the results with those of several analytical approaches. In one, the noise spectrum is assumed to reflect separately, the characteristic individual release time constants of the various trapping centers in the material. In another, the trapping time into the ensemble of electron traps is taken to be the dominant time constant, and hence, in a material such as a-Si:H, where the trapping time into tail sates is of order 1ps, this is taken to imply that this component of the conductivity noise spectrum is unobservable in practice. Our own analytical approach, incorporates coupling (albeit weak) between traps, which necessarily communicate via the extended states. Preliminary results of the simulation support our thesis, and verify that the same information is contained in the real part of the modulated photoconductivity (MPC) spectrum. A ‘full Monte’ – Carlo simulation incorporating all gap states and spatial inhomogeneities is now a priority.

Computer Modelling of Non-Equilibrium Multiple-Trapping and Hopping Transport in Amorphous Semiconductors

2005 ◽  
Vol 862 ◽  
Author(s):  
C. Main ◽  
J. M. Marshall ◽  
S. Reynolds ◽  
M.J. Rose ◽  
R. Brüggemann
Keyword(s):  
Computer Modelling ◽  
Stochastic Matrix ◽  
Computational Procedure ◽  
Amorphous Semiconductors ◽  
Extended State ◽  
Hopping Transport ◽  
Multiple Trapping ◽  
Extended States ◽  
Localised States ◽  
Gap States

AbstractIn this paper we demonstrate a simple computational procedure for the simulation of transport in a disordered semiconductor in which both multi-trapping and hopping processes are occurring simultaneously. We base the simulation on earlier work on hopping transport, which used a Monte-Carlo method. Using the same model concepts, we now employ a stochastic matrix approach to speed computation, and include also multi-trapping transitions between localised and extended states. We use the simulation to study the relative contributions of extended state conduction (with multi-trapping) and hopping conduction (via localised states) to transient photocurrents, for various distributions of localised gap states, and as a function of temperature. The implications of our findings for the interpretation of transient photocurrents are examined.

Monte Carlo Simulation of Self-Absorption Effects in Elemental XRF Analysis of Atmospheric Particulates Collected on Filters

1975 ◽  
Vol 19 ◽  
pp. 323-337 ◽  
Author(s):  
A. R. Hawthorne ◽  
R. P. Gardner ◽  
T. G. Dzubay
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Size Range ◽  
Thick Layer ◽  
Thin Layers ◽  
Analytical Models ◽  
Enhancement Effect ◽  
X Rays ◽  
Atmospheric Particulates ◽  
Cylinders And Spheres

Monte Carlo simulation is used to determine the effects of selfabsorption for the low energy X-rays of light elements in the size range front 1 to 20 μm. Calculations are performed for a wide angle Fe-55 radioisotope-excited energy dispersive XRF system. Results are obtained for sulfur attenuation in thin layers, long cylinders, and spheres composed of various matrix materials. The enhancement effect is also treated for the transition region between thin and thick layer samples as well as in spheres of various sizes. Results are also comrpared to fixed angle analytical models.

Monte Carlo simulation of fluorescence correlation spectroscopy data

2011 ◽  
Vol 76 (3) ◽  
pp. 207-222 ◽  
Author(s):  
Peter Košovan ◽  
Filip Uhlík ◽  
Jitka Kuldová ◽  
Miroslav Štěpánek ◽  
Zuzana Limpouchová ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Diffusion Coefficients ◽  
Fluorescence Correlation Spectroscopy ◽  
Rotational Diffusion ◽  
Correlation Spectroscopy ◽  
Analytical Models ◽  
Spherical Particles ◽  
Fluorescence Signal ◽  
Fluorescence Correlation

We employed the Monte Carlo simulation methodology to emulate the diffusion of fluorescently labeled particles and understand the source of differences between values of diffusion coefficients (and consequently hydrodynamic radii) of fluorescently labeled nanoparticles measured by fluorescence correlation spectroscopy (FCS) and dynamic light scattering (DLS). We used the simulation program developed in our laboratory and studied the diffusion of spherical particles of different sizes, which are labeled on their surface. In this study, we focused on two complicating effects: (i) multiple labeling and (ii) rotational diffusion which affect the fluorescence signal from large particles and hinder the analysis of autocorrelation functions according to simple analytical models. We have shown that the fluorescence fluctuations can be well fitted using the analytical model for small point-like particles, but the obtained parameters deviate in some cases significantly from the real ones. It means that the current data treatment yields apparent values of diffusion coefficients and other parameters only and the interpretation of experimental results for systems of particles with sizes comparable to the size of the active illuminated volume requires great care and precaution.

Monte-Carlo Simulation of Energy Relaxation of Interacting Carriers in a-Si:H Under Arbitrary Electric Fields

1993 ◽  
Vol 297 ◽  
Author(s):  
B. Cleve ◽  
R. Hess ◽  
S.D. Baranovskii ◽  
P. Thomas
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Theoretical Prediction ◽  
Electric Fields ◽  
Effective Temperature ◽  
Applied Electric Field ◽  
Applied Field ◽  
Energy Relaxation ◽  
Amorphous Semiconductors ◽  
Simulation Algorithm

A new Monte-Carlo simulation algorithm has been applied to verify the concept of the effective temperature recently suggested as a description of energy relaxation of carriers in band tails of amorphous semiconductors under the presence of an applied electric field. The algorithm allows the simulation with arbitrary applied field and finite temperature. The results of the simulation agree favourably with the theoretical prediction.

Modeling, simulation and optimization of maintenance cost aspects on multi-unit systems by stochastic Petri nets with predicates

SIMULATION ◽  
2018 ◽  
Vol 95 (5) ◽  
pp. 461-478 ◽  
Author(s):  
Fernando P Santos ◽  
Ângelo P Teixeira ◽  
C. Guedes Soares
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Petri Nets ◽  
Stochastic Petri Nets ◽  
Maintenance Cost ◽  
Maintenance Strategies ◽  
Simulation And Optimization ◽  
System Components ◽  
Parallel Configuration ◽  
Analytical Approaches

The paper addresses repairable multi-unit systems with a series–parallel configuration for which maintenance strategies are modeled by generalized stochastic Petri nets (GSPN) with predicates coupled with Monte Carlo simulation. Four maintenance strategies consisting of basic periodic preventive and corrective maintenance, and both combined with opportunistic maintenance (OM) strategies, are considered. Failure and repair distributions of the system components are independent, and repairs are considered to be perfect. Times to failure of degraded components follow a Weibull distribution with increasing failure rate over time. The maintenance strategies are optimized so as to minimize the total maintenance costs of the system while maximizing availability. A comparison is drawn between OM and non-OM. The aim is to show that GSPN with predicates, in combination with Monte Carlo simulation, is a powerful, flexible, efficient, and intuitive approach for modeling and optimizing practical maintenance strategies on multi-unit complex systems, modeling the dynamic behavior resulting from the interaction between system components and economic dependencies. The merits and advantages of GSPN coupled with Monte Carlo simulation are enhanced relative to other, analytical, approaches.

scholarly journals Sensitivity Analysis for Monte Carlo Simulation of Option Pricing

1995 ◽  
Vol 9 (3) ◽  
pp. 417-446 ◽  
Author(s):  
Michael C. Fu ◽  
Jian-Qlang Hu
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Option Pricing ◽  
Computational Effort ◽  
Analytical Models ◽  
Gradient Estimates ◽  
Option Value ◽  
Options Markets ◽  
Early Exercise

Monte Carlo simulation is one alternative for analyzing options markets when the assumptions of simpler analytical models are violated. We introduce techniques for the sensitivity analysis of option pricing, which can be efficiently carried out in the simulation. In particular, using these techniques, a single run of the simulation would often provide not only an estimate of the option value but also estimates of the sensitivities of the option value to various parameters of the model. Both European and American options are considered, starting with simple analytically tractable models to present the idea and proceeding to more complicated examples. We then propose an approach for the pricing of options with early exercise features by incorporating the gradient estimates in an iterative stochastic approximation algorithm. The procedure is illustrated in a simple example estimating the option value of an American call. Numerical results indicate that the additional computational effort required over that required to estimate a European option is relatively small.

Electron Scattering in Solids

1990 ◽  
Vol 48 (2) ◽  
pp. 4-5
Author(s):  
Ryuichi Shimizu ◽  
Ze-Jun Ding
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Angular Distribution ◽  
Elastic Scattering ◽  
Electron Scattering ◽  
Cross Sections ◽  
Expansion Method ◽  
Electron Excitation ◽  
Partial Wave Expansion ◽  
Backscattered Electrons

Monte Carlo simulation has been becoming most powerful tool to describe the electron scattering in solids, leading to more comprehensive understanding of the complicated mechanism of generation of various types of signals for microbeam analysis.The present paper proposes a practical model for the Monte Carlo simulation of scattering processes of a penetrating electron and the generation of the slow secondaries in solids. The model is based on the combined use of Gryzinski’s inner-shell electron excitation function and the dielectric function for taking into account the valence electron contribution in inelastic scattering processes, while the cross-sections derived by partial wave expansion method are used for describing elastic scattering processes. An improvement of the use of this elastic scattering cross-section can be seen in the success to describe the anisotropy of angular distribution of elastically backscattered electrons from Au in low energy region, shown in Fig.l. Fig.l(a) shows the elastic cross-sections of 600 eV electron for single Au-atom, clearly indicating that the angular distribution is no more smooth as expected from Rutherford scattering formula, but has the socalled lobes appearing at the large scattering angle.

Determination of Stoichiometry of GaAs Component in (Gaas)Ge Epitaxially Grown Thin Films by Electron Microprobe X-Ray Analysis

1990 ◽  
Vol 48 (2) ◽  
pp. 264-265
Author(s):  
D. R. Liu ◽  
S. S. Shinozaki ◽  
R. J. Baird
Keyword(s):  
Thin Film ◽  
Thin Films ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Compound Semiconductors ◽  
Energy Dispersive Analysis ◽  
X Ray ◽  
Metastable Alloys ◽  
Lower Voltage

The epitaxially grown (GaAs)Ge thin film has been arousing much interest because it is one of metastable alloys of III-V compound semiconductors with germanium and a possible candidate in optoelectronic applications. It is important to be able to accurately determine the composition of the film, particularly whether or not the GaAs component is in stoichiometry, but x-ray energy dispersive analysis (EDS) cannot meet this need. The thickness of the film is usually about 0.5-1.5 μm. If Kα peaks are used for quantification, the accelerating voltage must be more than 10 kV in order for these peaks to be excited. Under this voltage, the generation depth of x-ray photons approaches 1 μm, as evidenced by a Monte Carlo simulation and actual x-ray intensity measurement as discussed below. If a lower voltage is used to reduce the generation depth, their L peaks have to be used. But these L peaks actually are merged as one big hump simply because the atomic numbers of these three elements are relatively small and close together, and the EDS energy resolution is limited.

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