Level Set Modeling of Nickel Silicide Growth

2012 ◽  
Vol 1429 ◽  
Author(s):  
Ashish Kumar ◽  
Mark E. Law
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Reaction Rate ◽  
Solid Phase ◽  
Level Set Methods ◽  
Simulation Models ◽  
Nickel Silicide ◽  
Rate Equations ◽  
Transmission Electron Microscopy Data ◽  
Current Crowding

ABSTRACTLevel set methods have been used for Solid phase epitaxial regrowth, etching and deposition.This study is to model the growth of nickel silicide accurately using the level set method. NiSi growth has been observed to follow a linear-parabolic law which takes into account both diffusion and interfacial reaction. This linear-parabolic system is very similar to the Deal and Grove model of SiO2 growth. This model uses similar diffusion transport and reaction rate equations. This simulation models the growth of silicide coupling diffusion solutions to level-set techniques. Dual level sets have been used for top and bottom interface propagation of silicide; velocities were estimated based on nickel concentrations at both interfaces as well as diffusivity and reaction rate of nickel. This is important to predict precise shape of silicide that will allow current crowding and field focusing effects to be modeled in transport out of the intrinsic device into the contacting layers. These simulation models can be used for latest technology nodes at 45, 32, 22nm and special devices such as FinFET’s etc. The level set method is successfully implemented and verified in Florida Object Oriented Process Simulator and growth shapes matches well with the literature Transmission Electron Microscopy data.

scholarly journals A Hybrid Method for Pancreas Extraction from CT Image Based on Level Set Methods

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Huiyan Jiang ◽  
Hanqing Tan ◽  
Hiroshi Fujita
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Negative Impact ◽  
Level Set Methods ◽  
Region Growing ◽  
Ct Images ◽  
Medical Image Segmentation ◽  
Initial Contour ◽  
Ct Image ◽  
Fast Marching

This paper proposes a novel semiautomatic method to extract the pancreas from abdominal CT images. Traditional level set and region growing methods that request locating initial contour near the final boundary of object have problem of leakage to nearby tissues of pancreas region. The proposed method consists of a customized fast-marching level set method which generates an optimal initial pancreas region to solve the problem that the level set method is sensitive to the initial contour location and a modified distance regularized level set method which extracts accurate pancreas. The novelty in our method is the proper selection and combination of level set methods, furthermore an energy-decrement algorithm and an energy-tune algorithm are proposed to reduce the negative impact of bonding force caused by connected tissue whose intensity is similar with pancreas. As a result, our method overcomes the shortages of oversegmentation at weak boundary and can accurately extract pancreas from CT images. The proposed method is compared to other five state-of-the-art medical image segmentation methods based on a CT image dataset which contains abdominal images from 10 patients. The evaluated results demonstrate that our method outperforms other methods by achieving higher accuracy and making less false segmentation in pancreas extraction.

Parametric Shape and Topology Optimization: A New Level Set Approach Based on Cardinal Kernel Functions

2017 ◽  
Author(s):  
Long Jiang ◽  
Shikui Chen ◽  
Xiangmin Jiao
Keyword(s):  
Topology Optimization ◽  
Level Set Method ◽  
Level Set ◽  
Material Property ◽  
Kernel Function ◽  
Level Set Methods ◽  
Level Set Function ◽  
Set Function ◽  
Distance Regularization ◽  
Parametric Level Set Method

The parametric level set method is an extension of the conventional level set methods for topology optimization. By parameterizing the level set function, conventional levels let methods can be easily coupled with mathematical programming to achieve better numerical robustness and computational efficiency. Furthermore, the parametric level set scheme not only can inherit the original advantages of the conventional level set methods, such as clear boundary representation and high topological changes handling flexibility but also can alleviate some un-preferred features from the conventional level set methods, such as needing re-initialization. However, in the RBF-based parametric level set method, it was difficult to determine the range of the design variables. Moreover, with the mathematically driven optimization process, the level set function often results in significant fluctuations during the optimization process. This brings difficulties in both numerical stability control and material property interpolation. In this paper, an RBF partition of unity collocation method is implemented to create a new type of kernel function termed as the Cardinal Basis Function (CBF), which employed as the kernel function to parameterize the level set function. The advantage of using the CBF is that the range of the design variable, which was the weight factor in conventional RBF, can be explicitly specified. Additionally, a distance regularization energy functional is introduced to maintain a desired distance regularized level set function evolution. With this desired distance regularization feature, the level set evolution is stabilized against significant fluctuations. Besides, the material property interpolation from the level set function to the finite element model can be more accurate.

Island-Size Distributions for Submonolayer Epitaxy: Rate Equations and Beyond

1998 ◽  
Vol 528 ◽  
Author(s):  
D.D. Vvedensky ◽  
R.E. Caflisch ◽  
M.F. Gyure ◽  
B. Merriman ◽  
S. Osher ◽  
...  
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Atomic Scale ◽  
Rate Equations ◽  
Size Distributions ◽  
Scanning Tunnelling Microscope ◽  
Dynamics Model ◽  
Island Size ◽  
Boundary Velocity ◽  
Island Dynamics

AbstractThe scanning tunnelling microscope has revolutionized the quantitative analysis of epitaxial phenomena. This, in turn, has spawned a huge theoretical effort aimed at analyzing various aspects of the morphology of growing surfaces. One of the most important general approaches to have emerged from this effort is based on the application of scaling concepts to epitaxial island-size distributions in the regime of submonolayer coverage prior to coalescence. We first discuss the analytical basis for scaling solutions to rate equations. In the limit of irreversible aggregation, a solution is obtained in terms of the capture numbers which agrees with previous work. For reversible aggregation, we identify a new quantity that may be regarded as a continuous analogue of a critical island size. We then examine the influence of spatial correlations by introducing a method for modeling epitaxial phenomena in terms of the motion of island boundaries, which is implemented numerically using the level set method. This island dynamics model is continuous in the lateral directions, but retains atomic scale discreteness in the growth direction. Several choices for the island boundary velocity are discussed and computations of the island dynamics model using the level set method are presented.

A Meshless Level Set Method for Shape and Topology Optimization

2011 ◽  
Vol 308-310 ◽  
pp. 1046-1049 ◽  
Author(s):  
Yu Wang ◽  
Zhen Luo
Keyword(s):  
Topology Optimization ◽  
Free Boundary ◽  
Level Set Method ◽  
Level Set ◽  
Level Set Methods ◽  
Discrete Level ◽  
Shape And Topology Optimization ◽  
Level Set Function ◽  
And Topology ◽  
Set Function

This paper proposes a meshless Galerkin level set method for structural shape and topology optimization of continua. To taking advantage of the implicit free boundary representation scheme, structural design boundary is represented through the introduction of a scalar level set function as its zero level set, to flexibly handle complex shape fidelity and topology changes by maintaining concise and smooth interface. Compactly supported radial basis functions (CSRBFs) are used to parameterize the level set function and also to construct the shape functions for mesh free function approximation. The meshless Galerkin global weak formulation is employed to implement the discretization of the state equations. This provides a pathway to simplify two numerical procedures involved in most conventional level set methods in propagating the discrete level set functions and in approximating the discrete equations, by unifying the two different stages at two sets of grids just in terms of one set of scattered nodes. The proposed level set method has the capability of describing the implicit moving boundaries without remeshing for discontinuities. The motion of the free boundary is just a question of advancing the discrete level set function by finding the design variables of the size optimization in time. One benchmark example is used to demonstrate the effectiveness of the proposed method. The numerical results showcase that this method has the ability to simplify numerical procedures and to avoid numerical difficulties happened in most conventional level set methods. It is straightforward to apply the present method to more advanced shape and topology optimization problems.

Design of Multimaterial Compliant Mechanisms Using Level-Set Methods

2005 ◽  
Vol 127 (5) ◽  
pp. 941-956 ◽  
Author(s):  
Michael Yu Wang ◽  
Shikui Chen ◽  
Xiaoming Wang ◽  
Yulin Mei
Keyword(s):  
Level Set Method ◽  
Level Set ◽  
Compliant Mechanisms ◽  
Compliant Mechanism ◽  
Level Set Methods ◽  
Single Output ◽  
Geometric Boundary ◽  
Single Input ◽  
Applied Forces ◽  
Multiple Materials

A monolithic compliant mechanism transmits applied forces from specified input ports to output ports by elastic deformation of its comprising materials, fulfilling required functions analogous to a rigid-body mechanism. In this paper, we propose a level-set method for designing monolithic compliant mechanisms made of multiple materials as an optimization of continuum heterogeneous structures. Central to the method is a multiphase level-set model that precisely specifies the distinct material regions and their sharp interfaces as well as the geometric boundary of the structure. Combined with the classical shape derivatives, the level-set method yields an Eulerian computational system of geometric partial differential equations, capable of performing topological changes and capturing geometric evolutions at the interface and the boundary. The proposed method is demonstrated for single-input and single-output mechanisms and illustrated with several two-dimensional examples of synthesis of multimaterial mechanisms of force inverters and gripping and clamping devices. An analysis on the formation of de facto hinges is presented based on the shape gradient information. A scheme to ensure a well-connected topology of the mechanism during the process of optimization is also presented.

Total variation and level set methods in image science

Acta Numerica ◽  
2005 ◽  
Vol 14 ◽  
pp. 509-573 ◽  
Author(s):  
Yen-Hsi Richard Tsai ◽  
Stanley Osher
Keyword(s):  
Total Variation ◽  
Level Set Method ◽  
Level Set ◽  
Finite Difference Methods ◽  
Level Set Methods ◽  
Building Blocks ◽  
Continuous Functions ◽  
General Definition ◽  
Level Lines ◽  
Image Science

We review level set methods and the related techniques that are common in many PDE-based image models. Many of these techniques involve minimizing the total variation of the solution and admit regularizations on the curvature of its level sets. We examine the scope of these techniques in image science, in particular in image segmentation, interpolation, and decomposition, and introduce some relevant level set techniques that are useful for this class of applications. Many of the standard problems are formulated as variational models. We observe increasing synergistic progression of new tools and ideas between the inverse problem community and the ‘imagers’. We show that image science demands multi-disciplinary knowledge and flexible, but still robust methods. That is why the level set method and total variation methods have become thriving techniques in this field.Our goal is to survey recently developed techniques in various fields of research that are relevant to diverse objectives in image science. We begin by reviewing some typical PDE-based applications in image processing. In typical PDE methods, images are assumed to be continuous functions sampled on a grid. We will show that these methods all share a common feature, which is the emphasis on processing the level lines of the underlying image. The importance of level lines has been known for some time. See, e.g., Alvarez, Guichard, Morel and Lions (1993). This feature places our slightly general definition of the level set method for image science in context. In Section 2 we describe the building blocks of a typical level set method in the continuum setting. Each important task that we need to do is formulated as the solution to certain PDEs. Then, in Section 3, we briefly describe the finite difference methods developed to construct approximate solutions to these PDEs. Some approaches to interpolation into small subdomains of an image are reviewed in Section 4. In Section 5 we describe the Chan–Vese segmentation algorithm and two new fast implementation methods. Finally, in Section 6, we describe some new techniques developed in the level set community.

Multiple level-set joint inversion of traveltime and gravity data with application to ore delineation: A synthetic study

Geophysics ◽  
2018 ◽  
Vol 83 (1) ◽  
pp. R13-R30 ◽  
Author(s):  
Polina Zheglova ◽  
Peter G. Lelièvre ◽  
Colin G. Farquharson
Keyword(s):  
Physical Properties ◽  
Level Set Method ◽  
Level Set ◽  
Joint Inversion ◽  
Gravity Data ◽  
Level Set Methods ◽  
Physical Property ◽  
Magnetic Data ◽  
Inversion Method ◽  
Multiple Level

We have developed a multiple level-set method for simultaneous inversion of gravity and seismic traveltime data. The method recovers the boundaries between regions with distinct physical properties assumed constant and known, creating structurally consistent models of two subsurface properties: P-wave velocity and density. In single level-set methods, only two rock units can be considered: background and inclusion. Such methods have been applied to examples representing various geophysical scenarios, including in the context of joint inversion. In multiple level-set methods, several units can be considered, which make them far more applicable to real earth scenarios. Recently, a multiple level-set method has been proposed for inversion of magnetic data. We extend the multiple level-set formulation to joint inversion of gravity and traveltime data, improving upon previous work, and we investigate applicability of such an inversion method in ore delineation. In mineral exploration environments, traditional seismic imaging and inversion methods are challenging because of the small target size and the specific physical property contrasts involved. First-arrival seismic traveltime and gravity data complement each other, and we found that joint multiple level-set inversion is more beneficial than separate inversions, especially with limited data and slow targets. Our method is more robust than the joint inversion method based on clustering of physical properties in recovery of piecewise homogeneous models not well-constrained by the data. To justify the known property assumption, we found the degree of robustness of the multiple level-set joint inversion to uncertainties arising from incomplete knowledge of small-scale subsurface physical property variations and target composition.

Modeling two-dimensional solid-phase epitaxial regrowth using level set methods

2009 ◽  
Vol 105 (5) ◽  
pp. 053701 ◽  
Author(s):  
S. Morarka ◽  
N. G. Rudawski ◽  
M. E. Law ◽  
K. S. Jones ◽  
R. G. Elliman
Keyword(s):  
Level Set ◽  
Solid Phase ◽  
Level Set Methods ◽  
Two Dimensional ◽  
Epitaxial Regrowth

scholarly journals An enhanced variational level set method for MRI brain image segmentation using IFCM clustering and LBM

2018 ◽  
Vol 7 (2.31) ◽  
pp. 23 ◽  
Author(s):  
P Sudharshan Duth ◽  
Vinayak Ashok Kulkarni
Keyword(s):  
Image Segmentation ◽  
Level Set Method ◽  
Level Set ◽  
Time Complexity ◽  
Level Set Methods ◽  
Large Set ◽  
Brain Image ◽  
Mri Brain ◽  
Variational Level Set ◽  
Brain Image Segmentation

Today's technological advances in medical imaging have given rise to efficient diagnostic procedures. Segmentation identifies and defines individual objects with various attributes such as size, shape, texture, spatial location, contrast, brightness, noise, and context. Deformable segmentation methods are Active contours, which are used to match and track images of an atomic structure by determining constraints derived from the image data. Level set method is an integral part of active contour family, considerable work towards level set methods has identified two main disadvantages i.e., initialization of controlling parameters and time complexity. In this paper, the methodology employed proposes an enhanced Variational level set methodology for Magnetic Resonance (MR) brain image segmentation with heterogeneous intensity. Core concept of IFCM is based on Intuitionistic fuzzy set. Both the values of membership and non membership values for the purpose of labelling are utilized together. As the result of experimentation reveals the efficiency of the recommended IFCM algorithm and Lattice Boltzmann Method (LBM) to overcome the drawbacks of Level Set methods by using the energy function to reduce the processing time which addresses the time complexity issue. The proposed system combines of both IFCM and LBM to form a novel approach. The system is tested on a large set of MRI brain images, extensive research and experiments were carried over on the standard dataset and the results are found to be improved in identification of tumor size detection with respect to time complexity.

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