Suppr超能文献

像差校正的环形暗场扫描透射电子显微镜深度切片及在扫描/透射电子显微镜中进行可靠三维成像的前景。

Aberration-corrected ADF-STEM depth sectioning and prospects for reliable 3D imaging in S/TEM.

作者信息

Xin Huolin L, Muller David A

机构信息

Department of Physics, Cornell University, Ithaca, NY 14853, USA.

出版信息

J Electron Microsc (Tokyo). 2009 Jun;58(3):157-65. doi: 10.1093/jmicro/dfn029. Epub 2009 Jan 22.

Abstract

The short depth of focus of aberration-corrected scanning transmission electron microscopes (STEMs) could potentially enable 3D reconstruction of nanomaterials through acquisition of a through-focal series. However, the contrast transfer function of annular dark-field (ADF)-STEM depth sectioning has a missing-cone problem similar to that of tilt-series tomography. The elongation as a function of the probe-forming angle is found to be (square root of 3/2) x 1/alphamax. For existing aberration-corrected STEMs operated at optimal imaging conditions, the elongation factor for depth sectioning is larger than 30. This large elongation factor results in highly distorted shapes of 3D objects and unexpected artifacts due to the loss of information. Depth-sectioning experiments using a 33-mrad 100 keV C(5)-corrected aberration-corrected STEM demonstrate the elongation effect and the missing-cone problem in real and reciprocal space. The performance limits of different S/TEM-based imaging modes are compared. There is a missing cone of information for bright-field S/TEM, ADF-STEM, hollow-cone ADF-STEM and coherent scanning confocal electron microscopy (SCEM). Only incoherent SCEM fills the missing cone.

摘要

像差校正扫描透射电子显微镜(STEM)的短焦深有可能通过采集焦深系列实现纳米材料的三维重建。然而,环形暗场(ADF)-STEM深度切片的对比度传递函数存在类似于倾斜系列断层扫描的缺失锥问题。发现伸长率作为探针形成角的函数为(√3/2)×1/αmax。对于在最佳成像条件下运行的现有像差校正STEM,深度切片的伸长因子大于30。这种大的伸长因子会导致三维物体形状严重扭曲,并由于信息丢失而产生意外伪像。使用33毫弧度100 keV C(5)校正的像差校正STEM进行的深度切片实验在实空间和倒易空间中展示了伸长效应和缺失锥问题。比较了不同基于扫描透射电子显微镜(S/TEM)成像模式的性能极限。明场S/TEM、ADF-STEM、空心锥ADF-STEM和相干扫描共聚焦电子显微镜(SCEM)存在信息缺失锥。只有非相干SCEM填补了缺失锥。

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