Towards STEM control: Modeling framework and development of a sensor for defocus control

Scanning transmission electron microscopes are indispensable tools for material science research, since they can reveal the internal structure of a wide range of specimens. Thus, it is of scientific and industrial interest to transform these microscopes into flexible, high-throughput, unsupervised, nanomeasuring tools. To do so, processes that are currently executed manually based on visual feedback (e.g., alignment or particle measurement) should be automated, taking into consideration their time dependencies. That is, these microscopes should be studied from the systems and control perspective. To the best of our knowledge, such perspective is lacking in the literature. Thus, it is provided here through a new modeling framework that facilitates the future development of control strategies based on image analysis. The progress made towards developing an image-based sensor for defocus control is also reported. Finally, the paper also aims to introduce scanning transmission electron microscopy as an important and untapped application area for control engineers.

[1]  J. Thong,et al.  Eddy current compensation for magnetic electron lenses , 1996 .

[2]  M. Graef.  Introduction to Conventional Transmission Electron Microscopy: List of symbols , 2003 .

[3]  Z. Wang.  Introduction to Conventional Transmission Electron Microscopy , 2003 .

[4]  W. O. Saxton,et al.  A new method for the determination of the wave aberration function for high-resolution TEM.; 2. Measurement of the antisymmetric aberrations. , 2004, Ultramicroscopy.

[5]  John M. Cowley,et al.  The simulation of high resolution images of amorphous thin films , 1987 .

[6]  Yu Zhou,et al.  Sensor-based microassembly of hybrid MEMS devices , 1998 .

[7]  David B. Williams,et al.  Transmission Electron Microscopy: A Textbook for Materials Science , 1996 .

[8]  J. M. Cowley,et al.  Scanning transmission electron microscopy of thin specimens. , 1976, Ultramicroscopy.

[9]  A. Koster,et al.  Practical autoalignment of transmission electron microscopes , 1992 .

[10]  Michel Gevers.  Identification for Control: From the Early Achievements to the Revival of Experiment Design , 2005, CDC 2005.

[11]  François Chaumette,et al.  Visual servo control. I. Basic approaches , 2006, IEEE Robotics & Automation Magazine.

[12]  Seth Hutchinson,et al.  Visual Servo Control Part I: Basic Approaches , 2006 .

[13]  Nan Yao,et al.  Handbook of microscopy for nanotechnology , 2005 .

[14]  P. Hawkes,et al.  Science of Microscopy , 2007 .

[15]  Santosh Devasia,et al.  Image-based compensation of dynamic effects in scanning tunnelling microscopes , 2005 .

[16]  N. Baba,et al.  An “on-line” correction method of defocus and astigmatism in HAADF-STEM , 1999 .

[17]  A fully computer-controlled scanning electron microscope (II) ― Table control , 1987 .

[18]  P D Nellist,et al.  Progress in aberration-corrected scanning transmission electron microscopy. , 2001, Journal of electron microscopy.

[19]  W. Coene,et al.  Improved methods for the determination of the spherical aberration coefficient in high-resolution electron microscopy from micrographs of an amorphous object , 1991 .

[20]  The Study of Heterogeneous Catalysts by High-Resolution Transmission Electron Microscopy , 1993 .