USE OF A MONTE-CARLO TECHNIQUE FOR THE DETERMINATION OF RADIATION EXCHANGE AREAS IN 'LONG FURNACE' MODELS

1986 ◽  
Author(s):  
R. J. Tucker ◽  
J. Ward
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Technique ◽  
Radiation Exchange

Simulation of the Growth of Lattice Mismatched Semiconductors

1995 ◽  
Vol 379 ◽  
Author(s):  
M. Djafari Rouhani ◽  
R. Malek ◽  
A.M. Gue ◽  
D. Esteve
Keyword(s):  
Monte Carlo ◽  
Strain Relaxation ◽  
Local Strain ◽  
Monte Carlo Technique ◽  
Atomic Motion ◽  
Arrhenius Law ◽  
Activation Energy Barrier ◽  
Large Lattice ◽  
Layer Orientation

ABSTRACTWe have studied the growth of lattice mismatched semiconductors through the association of the Monte Carlo technique and the Valence Force Field (VFF) approximation. The Monte Carlo technique monitors the atomic motion in the deposited layer using the Arrhenius law and taking into account the impingment of atoms from the gas phase, intralayer and interlayer migrations of atoms and evaporation from the surface. The VFF approximation is used as an energy model to determine the local strain and stress inside the deposited layer by minimizing the total energy. This is performed after each single atomic motion. The strain is assumed to enhance the atomic motion by lowering the activation energy barrier related to the particular event. Results concerning the case of large lattice mismatches are presented. It is observed that the growing surface becomes rapidly rough, showing grooves with (111) facets. The strain relaxation occurs as a result of this roughening and allows the determination of the critical thickness. At higher lattice mismatches, it is seen that the layer orientation changes from(100) to (111) from the beginning.

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.

Application of the Monte Carlo Method for the Prediction of Behavior of Peptides

2019 ◽  
Vol 20 (12) ◽  
pp. 1151-1157 ◽  
Author(s):  
Alla P. Toropova ◽  
Andrey A. Toropov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Natural Sciences ◽  
Monte Carlo Technique ◽  
Quantitative Structure ◽  
Structure Property ◽  
The Monte Carlo Method ◽  
Modern Natural

Prediction of physicochemical and biochemical behavior of peptides is an important and attractive task of the modern natural sciences, since these substances have a key role in life processes. The Monte Carlo technique is a possible way to solve the above task. The Monte Carlo method is a tool with different applications relative to the study of peptides: (i) analysis of the 3D configurations (conformers); (ii) establishment of quantitative structure – property / activity relationships (QSPRs/QSARs); and (iii) development of databases on the biopolymers. Current ideas related to application of the Monte Carlo technique for studying peptides and biopolymers have been discussed in this review.

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