Monte-Carlo simulation of intensity ratio Is/Ic from substrate and film to determine the film thickness

1988 ◽  
Vol 46 ◽  
pp. 972-973
Author(s):  
Jin Guangxiang ◽  
Li Jianlin ◽  
Xu Li ◽  
Wu Ziqin
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Film Thickness ◽  
Electron Scattering ◽  
Calibration Curve ◽  
Intensity Ratio ◽  
Electron Probe ◽  
Monte Carlo Calculation ◽  
X Ray

The methods of thickness of film on substrate by electron probe have been published in literatures. It may be carried out simply by constructing a calibration curve from x-ray intensity measurments made on a series of films with known thickness on substrate.Sweeney et al. obtained a calibration curve based on a calcula- tied x-ray Ø(p z). As the calculation of Ø(p z) is difficult, Cockett and Davis, proposed using the experimental Ø(p z) of Castaing and Descamps. Bishop and Poole utilised Ø(p z) established by Monte-Carlo calculation for calibration curve.Huchings' method took into account the different electron scattering and absorption in the film on substrate and the bulk standard.Reuter et al., constructing a curve of Ic/Ib (Ic, intensity of the film on substrate; Ib, intensity of bulk standard) versus electron accelerating voltage E, exterpolate the curve so that Ic/Ib equals to 1, the excited x-ray depth obtained is just equal to the thickness of the film. The thickness of the film can be obtained by the use of an appropiate equation of excited x-ray depth.

Parallel Monte Carlo Simulation Using Desktop Computers

1999 ◽  
Vol 5 (S2) ◽  
pp. 80-81
Author(s):  
John Henry J. Scott ◽  
Robert L. Myklebust ◽  
Dale E. Newbury
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Electron Scattering ◽  
Information Needs ◽  
Image Interpretation ◽  
Scattered Electron ◽  
Electron Trajectories ◽  
X Ray ◽  
Desktop Computers ◽  
Computationally Expensive

Monte Carlo simulation of electron scattering in solids has proven valuable to electron microscopists for many years. The electron trajectories, x-ray generation volumes, and scattered electron signals produced by these simulations are used in quantitative x-ray microanalysis, image interpretation, experimental design, and hypothesis testing. Unfortunately, these simulations are often computationally expensive, especially when used to simulate an image or survey a multidimensional region of parameter space.Here we present techniques for performing Monte Carlo simulations in parallel on a cluster of existing desktop computers. The simulation of multiple, independent electron trajectories in a sample and the collateral calculation of detected x-ray and electron signals falls into a class of computational problems termed “embarrassingly parallel”, since no information needs to be exchanged between parallel threads of execution during the calculation. Such problems are ideally suited to parallel multicomputers, where a manager process distributes the computational burden over a large number of nodes.

scholarly journals Parallel Monte Carlo Simulation Using Desktop Computers

2000 ◽  
Vol 8 (2) ◽  
pp. 34-35
Author(s):  
John Henry J. Scott ◽  
Robert L. Myklebust ◽  
Dale E. Newbury
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Electron Scattering ◽  
Information Needs ◽  
Image Interpretation ◽  
Scattered Electron ◽  
Electron Trajectories ◽  
X Ray ◽  
Desktop Computers ◽  
Computationally Expensive

Monte Carlo simulation of electron scattering in solids has proven valuable to electron microscopists for many years. The electron trajectories, x-ray generation volumes, and scattered electron signals produced by these simulations are used in quantitative x-ray microanalysis, image interpretation, experimental design, and hypothesis testing. Unfortunately, these simulations are often computationally expensive, especially when used to simulate an image or survey a multidimensional region of parameter space.Here we present techniques for performing Monte Carlo simulations in parallel on a cluster of existing desktop computers. The simulation of multiple, independent electron trajectories in a sample and the collateral calculation of detected xray and electron signals fall into a class of computational problems termed “embarrassingly parallel”, since no information needs to be exchanged between parallel threads of execution during the calculation.

Monte Carlo Simulation of Characteristic Secondary Fluorescence in Electron Probe Microanalysis of Homogeneous Samples Using the Splitting Technique

2015 ◽  
Vol 21 (3) ◽  
pp. 753-758 ◽  
Author(s):  
Mauricio Petaccia ◽  
Silvina Segui ◽  
Gustavo Castellano
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Electron Probe Microanalysis ◽  
Electron Probe ◽  
Variance Reduction ◽  
Fluorescence Enhancement ◽  
Radiation Transport ◽  
X Rays ◽  
X Ray ◽  
Secondary Fluorescence

AbstractElectron probe microanalysis (EPMA) is based on the comparison of characteristic intensities induced by monoenergetic electrons. When the electron beam ionizes inner atomic shells and these ionizations cause the emission of characteristic X-rays, secondary fluorescence can occur, originating from ionizations induced by X-ray photons produced by the primary electron interactions. As detectors are unable to distinguish the origin of these characteristic X-rays, Monte Carlo simulation of radiation transport becomes a determinant tool in the study of this fluorescence enhancement. In this work, characteristic secondary fluorescence enhancement in EPMA has been studied by using the splitting routines offered by PENELOPE 2008 as a variance reduction alternative. This approach is controlled by a single parameter NSPLIT, which represents the desired number of X-ray photon replicas. The dependence of the uncertainties associated with secondary intensities on NSPLIT was studied as a function of the accelerating voltage and the sample composition in a simple binary alloy in which this effect becomes relevant. The achieved efficiencies for the simulated secondary intensities bear a remarkable improvement when increasing the NSPLIT parameter; although in most cases an NSPLIT value of 100 is sufficient, some less likely enhancements may require stronger splitting in order to increase the efficiency associated with the simulation of secondary intensities.

A simple Monte Carlo model for electron-probe quantitation

1992 ◽  
Vol 50 (2) ◽  
pp. 1674-1675
Author(s):  
Peter Duncumb
Keyword(s):  
Monte Carlo ◽  
Cross Section ◽  
Electron Scattering ◽  
Electron Probe ◽  
Monte Carlo Model ◽  
Correction Procedure ◽  
Backscatter Coefficient ◽  
X Ray ◽  
Monte Carlo Techniques

Since the early work of Bishop in the 1960's, many have used Monte Carlo techniques for studying the role of electron scattering in the X-ray production process, but the simulation of individual trajectories has always proved too slow to be of use for online analysis. The paper describes a simple model for calculating the distribution curves of ionisation with depth ϕ(ρz) for a variety of target conditions, which are then characterised by a type of exponential expression capable of much faster computation. This expression is built into a practical correction procedure which can be applied to the analysis of all elements from boron upwards.The Monte Carlo model uses a simple multiple scattering cross-section with 50-step trajectories. This cross-section is adjusted to give the correct variation of backscatter coefficient with target atomic number, as shown in Figure 1, and this is the only physical parameter which it is necessary to fit empirically.

Applications of Monte Carlo Simulation of Electron Scattering to Quantitative X-Ray Microanalyses

2001 ◽  
Vol 7 (S2) ◽  
pp. 690-691
Author(s):  
Kenji Murata ◽  
Masaaki Yasuda ◽  
Syunji Yamauchi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Elastic Scattering ◽  
Energy Loss ◽  
Cross Section ◽  
Electron Scattering ◽  
List Type ◽  
Discrete Energy ◽  
X Ray ◽  
Loss Process

Monte Carlo simulation of electron scattering has been widely used in various fields such as microanalysis, microscopy and microlithography. Various simulation models have been reported so far. in applications to quantitative x-ray microanalysis the accuracy of the model has been significantly improved by introducing the Mott cross section. However, in the analyses at low energies of an electron beam or at energies near the x-ray excitation energy, the simulation accuracy becomes worse. This is probably because the discrete energy loss process is not incorporated into the simulation model. to improve this default, we developed the model which includes the discrete energy loss process[l]. The outline of the model is described in the following.1)Elastic scatteringWe used the Mott cross section. The Mott cross sections for Al, Cu, Ag and Au elements are calculated at various energies. From this data base we obtain the differential elastic scattering cross section and the total elastic cross section for arbitarary elements and energies by using the interporation or the extrapolation.

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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