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The Monte Carlo method for the solution of charge transport in semiconductors with applications to covalent materials

Jacoboni, Carlo, Reggiani, Lino·1983·Reviews of Modern Physics

Abstract

This review presents in a comprehensive and tutorial form the basic principles of the Monte Carlo method, as applied to the solution of transport problems in semiconductors. Sufficient details of a typical Monte Carlo simulation have been given to allow the interested reader to create his own Monte Carlo program, and the method has been briefly compared with alternative theoretical techniques. Applications have been limited to the case of covalent semiconductors. Particular attention has been paid to the evaluation of the integrated scattering probabilities, for which final expressions are given in a form suitable for their direct use. A collection of results obtained with Monte Carlo simulations is presented, with the aim of showing the power of the method in obtaining physical insights into the processes under investigation. Special technical aspects of the method and updated microscopic models have been treated in some appendixes.

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Metadata

Authors
Jacoboni, C., & Reggiani, L.
Venue
Reviews of Modern Physics
Published
1983-07-01
Volume
55
Issue
3
Pages
645-705
ISSN
0034-6861 (ISSN-L)
OpenAlex
W2109522465
Cited by
2,300
References
0
FWCI
28.90
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Monte Carlo method for the solution of charge transport in semiconductors with applications to covalent materials. https://app.cochat.ai/papers/10.1103/revmodphys.55.645
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Jacoboni, C., & Reggiani, L. (1983). The Monte Carlo method for the solution of charge transport in semiconductors with applications to covalent materials. Reviews of Modern Physics. https://doi.org/10.1103/revmodphys.55.645

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.