论文标题

综合受约束梯度下降(ICGD)方案,以高精度和精度纠正电子ptychography的扫描位置误差

An Integrated Constrained Gradient Descent (iCGD) Protocol to Correct Scan-Positional Errors for Electron Ptychography with High Accuracy and Precision

论文作者

Ning, Shoucong, Xu, Wenhui, Loh, Leyi, Lu, Zhen, Bosman, Michel, Zhang, Fucai, He, Qian

论文摘要

纠正扫描位置误差对于以高分辨率和高精度来实现电子ptychography至关重要。由于需要优化的大量参数,这是一项苛刻且具有挑战性的任务。对于原子分辨率的ptychographic重建,我们发现由于对象和扫描位置之间的固有纠缠而无法满足扫描位置的经典精炼方法,这可能会在结果中产生系统的错误。在这里,我们提出了一个新的协议,该方案包括一系列约束梯度下降(CGD)方法,以更好地恢复扫描位置。这些CGD方法的核心思想是利用有关STEM实验性质的先验知识,并在迭代重建过程中添加必要的约束以隔离不同类型的扫描位置错误。每个约束将在模拟的4D-STEM数据集的帮助下引入,并具有已知的位置错误。然后,将使用1H-MOS2单层的实验4D-STEM数据集来证明集成的约束梯度体面(ICGD)协议。我们将表明,ICGD协议可以有效地解决整个频谱扫描位置的误差,并有助于以高精度和精确度获得电子PTYChography。

Correcting scan-positional errors is critical in achieving electron ptychography with both high resolution and high precision. This is a demanding and challenging task due to the sheer number of parameters that need to be optimized. For atomic-resolution ptychographic reconstructions, we found classical refining methods for scan positions not satisfactory due to the inherent entanglement between the object and scan positions, which can produce systematic errors in the results. Here, we propose a new protocol consisting of a series of constrained gradient descent (CGD) methods to achieve better recovery of scan positions. The central idea of these CGD methods is to utilize a priori knowledge about the nature of STEM experiments and add necessary constraints to isolate different types of scan positional errors during the iterative reconstruction process. Each constraint will be introduced with the help of simulated 4D-STEM datasets with known positional errors. Then the integrated constrained gradient decent (iCGD) protocol will be demonstrated using an experimental 4D-STEM dataset of the 1H-MoS2 monolayer. We will show that the iCGD protocol can effectively address the errors of scan positions across the spectrum and help to achieve electron ptychography with high accuracy and precision.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源