This report describes the SummitView 1.0 computer code developed at Sandia National Laboratories. SummitView is designed to generate a 3D solid model, amenable to visualization and meshing, that represents the end state of a microsystem fabrication process such as the SUMMiT (Sandia Ultra-Planar Multilevel MEMS Technology) V process. Functionally, SummitView performs essentially the same computational task as an earlier code called the 3D Geometry modeler [1]. However, because SummitView is based on 2D instead of 3D data structures and operations, it has significant speed and robustness advantages. As input it requires a definition of both the process itself and the collection of individual 2D masks created by the designer and associated with each of the process steps. The definition of the process is contained in a special process definition file [2] and the 2D masks are contained in MEM format files [3]. The code is written in C++ and consists of a set of classes and routines. The classes represent the geometric data and the SUMMiT V process steps. Classes are provided for the following process steps: Planar Deposition, Planar Etch, Conformal Deposition, Dry Etch, Wet Etch and Release Etch.SummitView is built upon the 2D Boolean library GBL-2D [4], and thus contains all of that library's functionality.
This report describes version 1.0 of GBL-2D, a geometric Boolean library for 2D objects. The library is written in C++ and consists of a set of classes and routines. The classes primarily represent geometric data and relationships. Classes are provided for 2D points, lines, arcs, edgeuses, loops, surfaces and mask sets. The routines contain algorithms for geometric Boolean operations and utility functions. Routines are provided that incorporate the Boolean operations: Union(OR), XOR, Intersection and Difference. A variety of additional analytical geometry routines and routines for importing and exporting the data in various file formats are also provided.The GBL-2D library was originally developed as a geometric modeling engine for use with a separate software tool, called SummitView [1], that manipulates the 2D mask sets created by designers of Micro-Electro-Mechanical Systems (MEMS). However, many other practical applications for this type of software can be envisioned because the need to perform 2D Boolean operations can arise in many contexts.
Two methods for creating a hybrid level-set (LS) / particle method for modeling surface evolution during feature-scale etching and deposition processes are developed and tested. The first method supplements the LS method by introducing Lagrangian marker points in regions of high curvature. Once both the particle set and the LS function are advanced in time, minimization of certain objective functions adjusts the LS function so that its zero contour is in closer alignment with the particle locations. It was found that the objective-minimization problem was unexpectedly difficult to solve, and even when a solution could be found, the acquisition of it proved more costly than simply expanding the basis set of the LS function. The second method explored is a novel explicit marker-particle method that we have named the grid point 3 particle (GPP) approach. Although not a LS method, the GPP approach has strong procedural similarities to certain aspects of the LS approach. A key aspect of the method is a surface rediscretization procedure-applied at each time step and based on a global background mesh-that maintains a representation of the surface while naturally adding and subtracting surface discretization points as the surface evolves in time. This method was coded in 2-D, and tested on a variety of surface evolution problems by using it in the ChISELS computer code. Results shown for 2-D problems illustrate the effectiveness of the method and highlight some notable advantages in accuracy over the LS method. Generalizing the method to 3D is discussed but not implemented.4
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.