从四维扫描传输电子显微镜通过散射矩阵优化结构因素
Kousuke Ooe1,2, Alireza Sadri1, Scott D Findlay1
1School of Physics and Astronomy, Monash University, Wellington Rd, Clayton, Victoria 3800, Australia.
概括
我们开发了一种新的算法,用于扫描传输电子显微镜 (STEM) 中的定量潜力检索. 这种方法可以准确地从更厚的样本中重建材料特性,克服多个散射挑战.
科学领域:
- 材料科学 材料科学 材料科学
- 凝聚物质物理学 凝聚物质物理学
- 电子显微镜电子显微镜
背景情况:
- 扫描传输电子显微镜 (STEM) 中的定量潜力检索对于材料表征至关重要.
- 较厚的样本由于显著的多重散射效应而存在挑战.
研究的目的:
- 开发一种基于梯度下降的新型优化算法,用于从4D STEM中的厚样本中检索定量潜力.
- 为了克服电子显微镜中多重散射所带来的局限性.
主要方法:
- 使用散射矩阵 (S-矩阵) 来建模多重散射效应.
- 在没有常见规范化术语的情况下使用梯度下降优化算法.
- 使用最佳亮场STEM数据作为初始潜在猜测和基于测量/估计的4DSTEM数据的损失函数.
主要成果:
- 在各种模拟条件 (厚度,剂量,不一致性) 中,成功地从厚样本中检索出定量潜力.
- 在实验4D STEM数据上证明了算法的有效性.
- 研究了对细分探测器算法的扩展.
结论:
- 提出的梯度下降优化算法有效地使得在STEM中对更厚的样本进行定量潜力检索.
- 这种方法通过减轻多个散射工件,提高了材料表征能力.
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