Modeling ion-solid interactions for imaging applications
- PDF / 2,685,313 Bytes
- 5 Pages / 585 x 783 pts Page_size
- 108 Downloads / 259 Views
Introduction There are many methods today that depend on scanning a primary beam of ions for imaging surfaces. These techniques include helium ion microscopy; secondary ion mass spectrometry (e.g., time of flight secondary ion mass spectrometry), wherein a variety of ions are used; and focused ion beam (FIB) microscopy, where ions such as those of Ga+ and Xe+ are commonly utilized for the imaging and sputtering of samples.1,2 All of these techniques rely on ion-induced secondary electrons (iSE) to form images of the sample surface. iSE images can show contrast arising from topography, materials contrast, and crystallographic contrast through channeling. In order to properly interpret images from these scanning ion microscopes, one must understand the generation of secondary electrons (SEs) by energetic ions. Research in this area is critical if ion imaging is to become a trusted technique for materials imaging. This article describes the use of a Monte Carlo-based model of SE generation to predict topographic contrast and materials contrast in scanning ion microscopy.
Ion-induced secondary electron yield modeling SEs are the most versatile and powerful tool for imaging in either electron or ion beam scanning microscopes because they uniquely cover the entire feature size range from millimeters to nanometers and produce images that are readily interpreted.3
To make optimum use of these capabilities, it is necessary to understand in detail how SE signals are generated, how they interact with materials, and how the user’s choice of beam parameters can be adjusted for the highest performance. This is most conveniently achieved by having a detailed, quantitative model of the interactions of the incident beam with the specimen. Monte Carlo methods are ideally suited for this purpose because they can readily be customized to answer any question of interest and because, even on typical desktop computers, useful data can be obtained in an acceptably short time. Procedures for developing a Monte Carlo model for electron beam interactions have been documented in detail elsewhere, but corresponding tools for studying ion-solid interactions are much less common.4 There are two possible approaches to developing a Monte Carlo model for ion transport. The first option models the energy straggling of the incoming ions as they travel through the specimen and accounts for the individual energy losses encountered by all the electrons in the SE cascade.5 The second method uses the continuous slowing down (CSD) approximation that models only the average energy loss suffered by incident ions.6 Although simpler and admittedly less rigorous than the first method, a detailed side by side analysis of the two approaches shows that the CSD methods offer an order of magnitude enhancement in computational speed, while suffering only a minimal loss in accuracy.5
D.C. Joy, Department of Biochemistry, Cellular and Molecular Biology Department of Materials Science and Engineering, University of Tennessee; [email protected] J.R. Michael, Sandia National L
Data Loading...
