High-resolution transmission electron microscopy(HRTEM)promises rapid atomic-scale dynamic structure imaging.Yet,the precision limitations of aberration parameters and the challenge of eliminating aberrations in Cs-co...High-resolution transmission electron microscopy(HRTEM)promises rapid atomic-scale dynamic structure imaging.Yet,the precision limitations of aberration parameters and the challenge of eliminating aberrations in Cs-corrected transmission electron microscopy constrain resolution.A machine learning algorithm is developed to determine the aberration parameters with higher precision from small,lattice-periodic crystal images.The proposed algorithm is then validated with simulated HRTEM images of graphene and applied to the experimental images of a molybdenum disulfide(MoS_(2))monolayer with 25 variables(14 aberrations)resolved in wide ranges.Using these measured parameters,the phases of the exit-wave functions are reconstructed for each image in a focal series of MoS_(2)monolayers.The images were acquired due to the unexpected movement of the specimen holder.Four-dimensional data extraction reveals time-varying atomic structures and ripple.In particular,the atomic evolution of the sulfur-vacancy point and line defects,as well as the edge structure near the amorphous,is visualized as the resolution has been improved from about 1.75?to 0.9 A.This method can help salvage important transmission electron microscope images and is beneficial for the images obtained from electron microscopes with average stability.展开更多
针对高分辨透射电子显微镜(high⁃resolution transmission electron microscope,HRTEM)所拍摄的图像存在像差造成的分辨率下降问题,本文提出一种自动测量像差参数的方案:以相对随机的方式,模仿实验像与模拟像的人工对比过程,可以求解电...针对高分辨透射电子显微镜(high⁃resolution transmission electron microscope,HRTEM)所拍摄的图像存在像差造成的分辨率下降问题,本文提出一种自动测量像差参数的方案:以相对随机的方式,模仿实验像与模拟像的人工对比过程,可以求解电镜像差。求得的像差结合改进单图重建波函数算法,可以去除图像的像差影响并获得单张图的波函数的相位像。本文运用模拟像验证后,方案与算法用于单层二硫化钼的实验HRTEM像,测得像差参数精度高,校正后的图像细节更优。本文算法计算精度好、效率高,有望应用于针对晶格像的像差测量问题。展开更多
基金financial support from the National Natural Science Foundation of China(Grant No.61971201)。
文摘High-resolution transmission electron microscopy(HRTEM)promises rapid atomic-scale dynamic structure imaging.Yet,the precision limitations of aberration parameters and the challenge of eliminating aberrations in Cs-corrected transmission electron microscopy constrain resolution.A machine learning algorithm is developed to determine the aberration parameters with higher precision from small,lattice-periodic crystal images.The proposed algorithm is then validated with simulated HRTEM images of graphene and applied to the experimental images of a molybdenum disulfide(MoS_(2))monolayer with 25 variables(14 aberrations)resolved in wide ranges.Using these measured parameters,the phases of the exit-wave functions are reconstructed for each image in a focal series of MoS_(2)monolayers.The images were acquired due to the unexpected movement of the specimen holder.Four-dimensional data extraction reveals time-varying atomic structures and ripple.In particular,the atomic evolution of the sulfur-vacancy point and line defects,as well as the edge structure near the amorphous,is visualized as the resolution has been improved from about 1.75?to 0.9 A.This method can help salvage important transmission electron microscope images and is beneficial for the images obtained from electron microscopes with average stability.
文摘针对高分辨透射电子显微镜(high⁃resolution transmission electron microscope,HRTEM)所拍摄的图像存在像差造成的分辨率下降问题,本文提出一种自动测量像差参数的方案:以相对随机的方式,模仿实验像与模拟像的人工对比过程,可以求解电镜像差。求得的像差结合改进单图重建波函数算法,可以去除图像的像差影响并获得单张图的波函数的相位像。本文运用模拟像验证后,方案与算法用于单层二硫化钼的实验HRTEM像,测得像差参数精度高,校正后的图像细节更优。本文算法计算精度好、效率高,有望应用于针对晶格像的像差测量问题。
