Suppr超能文献

金属锗的自下而上组装。

Bottom-up assembly of metallic germanium.

作者信息

Scappucci Giordano, Klesse Wolfgang M, Yeoh LaReine A, Carter Damien J, Warschkow Oliver, Marks Nigel A, Jaeger David L, Capellini Giovanni, Simmons Michelle Y, Hamilton Alexander R

机构信息

School of Physics, University of New South Wales, Sydney, 2052, Australia.

1] Department of Chemistry, Curtin University, Perth WA 6845, Australia. [2] Nanochemistry Research Institute, Curtin University, Perth WA 6845, Australia.

出版信息

Sci Rep. 2015 Aug 10;5:12948. doi: 10.1038/srep12948.

Abstract

Extending chip performance beyond current limits of miniaturisation requires new materials and functionalities that integrate well with the silicon platform. Germanium fits these requirements and has been proposed as a high-mobility channel material, a light emitting medium in silicon-integrated lasers, and a plasmonic conductor for bio-sensing. Common to these diverse applications is the need for homogeneous, high electron densities in three-dimensions (3D). Here we use a bottom-up approach to demonstrate the 3D assembly of atomically sharp doping profiles in germanium by a repeated stacking of two-dimensional (2D) high-density phosphorus layers. This produces high-density (10(19) to 10(20) cm(-3)) low-resistivity (10(-4)Ω · cm) metallic germanium of precisely defined thickness, beyond the capabilities of diffusion-based doping technologies. We demonstrate that free electrons from distinct 2D dopant layers coalesce into a homogeneous 3D conductor using anisotropic quantum interference measurements, atom probe tomography, and density functional theory.

摘要

要将芯片性能提升至当前小型化极限之外,需要能与硅平台良好集成的新材料和新功能。锗符合这些要求,已被提议用作高迁移率沟道材料、硅基集成激光器中的发光介质以及用于生物传感的等离子体导体。这些不同应用的共同之处在于需要在三维空间(3D)中实现均匀的高电子密度。在此,我们采用自下而上的方法,通过重复堆叠二维(2D)高密度磷层来展示锗中原子级尖锐掺杂分布的三维组装。这产生了具有精确界定厚度的高密度(10¹⁹至10²⁰ cm⁻³)、低电阻率(10⁻⁴Ω·cm)的金属锗,这是基于扩散的掺杂技术所无法实现的。我们使用各向异性量子干涉测量、原子探针断层扫描和密度泛函理论证明,来自不同二维掺杂层的自由电子聚合成了均匀的三维导体。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a14a/4530340/3bf7615674ad/srep12948-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验