SESAME (Simulation of Electron transport Supporting Analysis of MatErials) is a quasi-three-dimensional Monte Carlo program for the simulation of electron-matter interactions. It is written in FORTRAN and C and runs on Open VMS VAX, Open VMS AXP, and Digital Unix (former DEC OSF/1 AXP) platforms.
The simulation results obtained by SESAME are semi-quantitative. This means that comparisons with measured data will show very good qualitative agreement, and that interpretations based on such qualitative comparisons will lead to the correct conclusions with a high degree of confidence. Evaluations based solely on quantitative results could be distorted and should therefore be avoided unless they have been cross-checked using additional information or tools. Semi-quantitative estimations can be done if deviations up to approximately 50% are acceptable.
The simulation geometries must be two-dimensional, i.e. they expand infinitely in the direction of the third coordinate axis perpendicular to the defined geometry. This is the only restriction concerning the shape of the simulation structure. The direction of the electron beam and the directions to the detectors may be chosen freely in three-dimensional space. For detailed information on the geometry specifications see Chapter 6.6, for information on supplied detectors see Chapter 6.3 and 6.4.
In SESAME three different electron scattering models are implemented; a single scattering model (see Chapter A.3), a hybrid model (see Chapter A.4), and a direct simulation model using dielectric functions (see Chapter A.5). Elastic scattering is taken into consideration by tabulated Mott cross-sections (see Chapter A.1), and for inner-shell ionization the Gryzinski ionization cross-section is taken into account (see Chapter A.2). In case of the single scattering model also the ionization cross section from Pouchou (see Chapter A.2) may be applied.
Each of these models has specific advantages and disadvantages as compared with the other two. Therefore, it may be important to use the model which is most suited for the specific application. Information about what model to use for your application can be found in Chapter A.3, Chapter A.4, and Chapter A.5, respectively. It is also referred to Chapter 4 where different analysis methods and the appropriate models are described.
SESAME provides a great variety of output information. Principally, characteristic x-rays, Auger electrons, secondary electrons and backscattered and transmitted electrons may be simulated. Generated information like, distributions, spectra, scans, etc. can either be directed to the screen or stored in files using different file formats. For more information on different output options see Chapters 6.7 and 9.9.
SESAME is controlled by an input file containing input records using the namelist extension of FORTRAN. Each namelist record contains a set of input variables. To keep the input file- and the generation-time short, most of these variables have appropriate default values. For a complete listing of all namelist records and all input variables see Chapter 9.
There exists also the possibility to generate the simulation geometry and the input file by means of a graphical user interface (GUI). Information on how to invoke and use these GUI can be found in Chapter 5.
In Chapter , examples for different applications are described
in detail. It is recommended to copy input and geometry files referenced
in Chapter
to your own account. By modifying these files and
adapting them to your own specific needs you will save a lot of time.
Generation of data alone is not very useful in most cases. There are different postprocessing tools available. Four of them are described in Chapter 10.
For any feedback concerning the program SESAME or this manual, send a mail to /dev/null . Any feedback (suggestions, complaints, wishes, etc.) which helps to improve SESAME and/or the manual will be highly appreciated.
All of you who have read this far may be interested in the definition of Monte
Carlo simulation. It sounds complicated but try it, run SESAME, you will see
that it really works!
Definition:
The Monte Carlo method is defined as representing the solution
of a problem as a parameter of a hypothetical population, and using a random
sequence of numbers to construct a sample of the population, from which
statistical estimates of the parameter can be obtained.