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硅锗合金中的电负性与掺杂

Electronegativity and doping in SiGe alloys.

作者信息

Christopoulos Stavros-Richard G, Kuganathan Navaratnarajah, Chroneos Alexander

机构信息

Faculty of Engineering, Environment and Computing, Coventry University, Priory Street, Coventry, CV1 5FB, United Kingdom.

Department of Materials, Imperial College London, London, SW7 2AZ, United Kingdom.

出版信息

Sci Rep. 2020 May 4;10(1):7459. doi: 10.1038/s41598-020-64403-8.

DOI:10.1038/s41598-020-64403-8
PMID:32366971
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7198609/
Abstract

Silicon germanium alloys are technologically important in microelectronics but also they are an important paradigm and model system to study the intricacies of the defect processes on random alloys. The key in semiconductors is that dopants and defects can tune their electronic properties and although their impact is well established in elemental semiconductors such as silicon they are not well characterized in random semiconductor alloys such as silicon germanium. In particular the impact of electronegativity of the local environment on the electronic properties of the dopant atom needs to be clarified. Here we employ density functional theory in conjunction with special quasirandom structures model to show that the Bader charge of the dopant atoms is strongly dependent upon the nearest neighbor environment. This in turn implies that the dopants will behave differently is silicon-rich and germanium-rich regions of the silicon germanium alloy.

摘要

硅锗合金在微电子技术中具有重要的技术意义,同时也是研究随机合金中缺陷过程复杂性的重要范例和模型系统。在半导体中,关键在于掺杂剂和缺陷能够调节其电子特性,尽管它们在诸如硅等元素半导体中的影响已得到充分证实,但在诸如硅锗等随机半导体合金中,它们的特性尚未得到很好的表征。特别是,局部环境的电负性对掺杂原子电子特性的影响需要加以阐明。在此,我们采用密度泛函理论并结合特殊准随机结构模型,以表明掺杂原子的巴德电荷强烈依赖于最近邻环境。这反过来意味着,掺杂剂在硅锗合金的富硅区和富锗区的行为会有所不同。

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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/cc95efc36671/41598_2020_64403_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/6742f577b6cc/41598_2020_64403_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/8fa3fb777798/41598_2020_64403_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/b3a946c577a0/41598_2020_64403_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/7299ca3670ae/41598_2020_64403_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/07139973ce65/41598_2020_64403_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/15d0340524ef/41598_2020_64403_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/63fc89e7d66d/41598_2020_64403_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/10f9fc422773/41598_2020_64403_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/9088da2fd214/41598_2020_64403_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed65/7198609/cc95efc36671/41598_2020_64403_Fig10_HTML.jpg

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