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Structures and Electric Properties of Semiconductor clusters

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Handbook of Computational Chemistry

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Abstract

Materials that exhibit an electrical resistivity between that of conductor and insulator are called semiconductors. Devices based on semiconductor materials, such as transistors, solar cells, light-emitting diodes, digital integrated circuits, solar photovoltaics, and much more, are the base of modern electronics. Silicon is used in most of the semiconductor devices while other materials such as germanium, gallium arsenide, and silicon carbide are used for specialized applications. The obvious theoretical and technological importance of semiconductor materials has led to phenomenal success in making semiconductors with near-atomic precision such as quantum wells, wires, and dots. As a result, there is a lot of undergoing research in semiconductor clusters of small and medium sizes both experimentally and by means of computational chemistry since the miniaturization of devices still continues. In the next pages, we are going to learn which the most studied semiconductor clusters are, we will explore their basic structural features and visit some of the most representative ab initio studies that are considered as works of reference in this research realm. Also, we are going to be introduced to the theory of the electric properties applied in the case of clusters by visiting some of the most illustrative studies into this research area. It is one of the purposes of this presentation to underscore the strong connection between the electric properties of clusters and their structure.

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  1. Groupe de Chimie Théorique et Réactivité, ECP, IPREM UMR 5254, Université de Pau et de Pays de l’Adour, Hélioparc Pau Pyrénées 2 avenue du Président Angot, 64053, PAU Cedex, France

    Panaghiotis Karamanis

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  1. Department of Chemistry and Biochemistry, Jackson State University, Jackson, MS, 39217, USA

    Jerzy Leszczynski

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Karamanis, P. (2012). Structures and Electric Properties of Semiconductor clusters. In: Leszczynski, J. (eds) Handbook of Computational Chemistry. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0711-5_20

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