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扫描透射电子显微镜中损伤减轻的扩散分布模型

Diffusion distribution model for damage mitigation in scanning transmission electron microscopy.

作者信息

Moshtaghpour Amirafshar, Velazco-Torrejon Abner, Nicholls Daniel, Robinson Alex W, Kirkland Angus I, Browning Nigel D

机构信息

Correlated Imaging Theme, Rosalind Franklin Institute, Harwell Science & Innovation Campus, Didcot, UK.

Department of Mechanical, Materials, & Aerospace Engineering, University of Liverpool, Liverpool, UK.

出版信息

J Microsc. 2025 Jan;297(1):57-77. doi: 10.1111/jmi.13351. Epub 2024 Aug 21.

DOI:10.1111/jmi.13351
PMID:39166469
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11629935/
Abstract

Despite the widespread use of Scanning Transmission Electron Microscopy (STEM) for observing the structure of materials at the atomic scale, a detailed understanding of some relevant electron beam damage mechanisms is limited. Recent reports suggest that certain types of damage can be modelled as a diffusion process and that the accumulation effects of this process must be kept low in order to reduce damage. We therefore develop an explicit mathematical formulation of spatiotemporal diffusion processes in STEM that take into account both instrument and sample parameters. Furthermore, our framework can aid the design of Diffusion Controlled Sampling (DCS) strategies using optimally selected probe positions in STEM, that constrain the cumulative diffusion distribution. Numerical simulations highlight the variability of the cumulative diffusion distribution for different experimental STEM configurations. These analytical and numerical frameworks can subsequently be used for careful design of 2- and 4-dimensional STEM experiments where beam damage is minimised.

摘要

尽管扫描透射电子显微镜（STEM）在原子尺度观察材料结构方面得到广泛应用，但对一些相关电子束损伤机制的详细理解仍然有限。最近的报告表明，某些类型的损伤可以建模为扩散过程，并且为了减少损伤，必须将此过程的累积效应保持在较低水平。因此，我们开发了一种明确的STEM时空扩散过程数学公式，该公式同时考虑了仪器和样品参数。此外，我们的框架可以帮助设计在STEM中使用最优选择的探针位置的扩散控制采样（DCS）策略，从而限制累积扩散分布。数值模拟突出了不同实验STEM配置下累积扩散分布的可变性。这些分析和数值框架随后可用于精心设计二维和四维STEM实验，以使束损伤最小化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/192a0f23566e/JMI-297-57-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/3ee989295e11/JMI-297-57-g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/6826af7d58cb/JMI-297-57-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/b0a0d7d2a232/JMI-297-57-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/70255edd00fd/JMI-297-57-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/1b3261d6ee33/JMI-297-57-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/cd4b177730d3/JMI-297-57-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/90589ec0bd94/JMI-297-57-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/86aef9f64f2a/JMI-297-57-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/192a0f23566e/JMI-297-57-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/3ee989295e11/JMI-297-57-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/aec583aa2d76/JMI-297-57-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/2a50395b9c67/JMI-297-57-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/6de221c4efc2/JMI-297-57-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/6826af7d58cb/JMI-297-57-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/b0a0d7d2a232/JMI-297-57-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/70255edd00fd/JMI-297-57-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/1b3261d6ee33/JMI-297-57-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/cd4b177730d3/JMI-297-57-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/90589ec0bd94/JMI-297-57-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/86aef9f64f2a/JMI-297-57-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c9c/11629935/192a0f23566e/JMI-297-57-g007.jpg

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