Amorphous Semiconductors by Kugler, Sándor; Shimakawa, Koichi

By Kugler, Sándor; Shimakawa, Koichi

Explains easy methods to use desktop modelling to appreciate amorphous semiconductors for researchers in reliable kingdom physics and semiconductor engineering.

summary: Explains tips on how to use machine modelling to appreciate amorphous semiconductors for researchers in stable country physics and semiconductor engineering

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In the uphill case, the new position is rejected conditionally. This decision is the essential part of MC simulations. A simple explanation for the selection rule is the following: if uphill motion is always rejected, than the procedure reaches the first shallow energy minimum and there is no chance of finding a deeper minimum, which probably belongs to a more realistic atomic configuration. A correct description of this MC philosophy can be found in any elementary textbook on statistical physics.

The instantaneous kinetic energies of the substrate atoms and the temperature of the substrate, however, may increase during an MD simulation owing to the particle impacts, depending on the energy of the incoming particles. In the rapid‐cooling technique, the characteristic rate of quenching in experiments is around 106 K/s or lower. A variety of thermostat methods to control the temperature in simulations can be found in the literature, but the simplest velocity rescaling methods are the most popular.

B, 52, 11059–11072. A. (2005) Parameterization of an anharmonic Kirkwood–Keating potential for AlxGa(1−x)As alloy. J. Chem. , 122, 174702‐1‐6. H. A. (1985) Computer simulation of local order in condensed phases of silicon. Phys. Rev. , 31, 5262–5271. , and Mousseau, N. (2001) 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 Fitting the Stillinger–Weber potential to amorphous silicon. J. Non‐Cryst. Solids, 282, 248–255. , and Albaret, T. (2013) A new parametrization of the Stillinger–Weber potential for an improved description of defects and plasticity of silicon.

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