EMAT, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium.
Department of Materials, University of Oxford, 16 Parks Road, Oxford OX1 3PH, United Kingdom.
Phys Rev Lett. 2019 Feb 15;122(6):066101. doi: 10.1103/PhysRevLett.122.066101.
Understanding nanostructures down to the atomic level is the key to optimizing the design of advanced materials with revolutionary novel properties. This requires characterization methods capable of quantifying the three-dimensional (3D) atomic structure with the highest possible precision. A successful approach to reach this goal is to count the number of atoms in each atomic column from 2D annular dark field scanning transmission electron microscopy images. To count atoms with single atom sensitivity, a minimum electron dose has been shown to be necessary, while on the other hand beam damage, induced by the high energy electrons, puts a limit on the tolerable dose. An important challenge is therefore to develop experimental strategies to optimize the electron dose by balancing atom-counting fidelity vs the risk of knock-on damage. To achieve this goal, a statistical framework combined with physics-based modeling of the dose-dependent processes is here proposed and experimentally verified. This model enables an investigator to theoretically predict, in advance of an experimental measurement, the optimal electron dose resulting in an unambiguous quantification of nanostructures in their native state with the highest attainable precision.
深入了解纳米结构直至原子水平是优化具有革命性新型特性的先进材料设计的关键。这需要能够以尽可能高的精度量化三维(3D)原子结构的表征方法。实现这一目标的一种成功方法是从二维环形暗场扫描透射电子显微镜图像中计算每个原子列中的原子数量。为了实现单原子灵敏度的原子计数,已经证明需要最小的电子剂量,而另一方面,高能电子引起的束损伤对可耐受的剂量施加了限制。因此,一个重要的挑战是开发实验策略,通过平衡原子计数保真度与碰撞损伤风险来优化电子剂量。为了实现这一目标,本文提出并实验验证了一种结合基于物理的剂量相关过程建模的统计框架。该模型使研究人员能够在实验测量之前从理论上预测产生明确纳米结构定量的最佳电子剂量,从而以最高可达的精度实现其在本征状态下的定量。