De Wael Annelies, De Backer Annick, Jones Lewys, Nellist Peter D, Van Aert Sandra
Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium.
Electron Microscopy for Materials Science (EMAT), University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium.
Ultramicroscopy. 2017 Jun;177:69-77. doi: 10.1016/j.ultramic.2017.01.010. Epub 2017 Jan 25.
A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials.
提出了一种基于统计与模拟的混合方法，用于从单型晶体纳米结构的环形暗场扫描透射电子显微镜（ADF STEM）图像中进行原子计数。对于类似模型的系统，已经存在不同的原子计数方法。然而，在纳米结构研究中，辐射损伤的相关性日益增加，这就需要一种能够从低信噪比的低剂量图像中进行原子计数的方法。因此，该混合方法直接将图像模拟的先验知识纳入现有的基于统计的原子计数方法中，并以此方式考虑实际实验条件与模拟实验条件之间可能存在的差异。通过模拟和实验表明，这种混合方法优于基于统计的方法，特别是对于低电子剂量和小纳米颗粒的情况。对一个小纳米颗粒的模拟低剂量图像的分析表明，该方法能够对束敏感材料进行更可靠的定量分析。
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