Collaborative Research: Detailed Chemical Kinetic Modeling of the Homogeneous Chemical Nucleation of Nanoparticles

摘要：马克·T. Swihart和琳达Broadbelt机构：纽约州立大学布法罗和西北大学提案编号：0500249和0500320标题：纳米颗粒均匀化学成核的详细化学动力学建模知识点：颗粒污染是半导体加工中产量损失的主要原因。随着集成电路变得更小，并且随着改进的洁净室技术消除了外部颗粒源，处理环境内的颗粒的均匀成核正迅速成为颗粒污染的最重要来源。在大多数情况下，这些颗粒是通过化学成核过程产生的，而不是通过纯材料的过饱和蒸汽的冷凝。如果要控制颗粒的形成，对化学成核过程的基本理解是重要的。同样的理解可以帮助设计纳米颗粒和纳米结构材料的气溶胶合成方法，这些材料是纳米级科学和工程的基石。最详细和翔实的方法来模拟化学成核被发现在机械水平。在这种方法中，粒子成核被描述为一个网络的基本化学反应，其速率可以相关的参与物种的属性。该项目延续了PI在这一主题上的合作，他们应用了两种互补的方法，自动反应机制生成和动力学Monte Carlo（KMC）模拟，以发展对硅纳米颗粒成核的机理理解。在最近的工作中，他们（1）开发了用于确定物种唯一性和识别复杂多环团簇中的环的改进算法，（2）对硅-氢团簇进行了广泛的量子化学计算，并将结果推广为基团加和方案，（3）开发了用于选择性生成反应途径的改进方法，并应用这些方法来确定颗粒成核的临界团簇尺寸和硅纳米颗粒成核的关键反应途径，（4）应用动力学Monte Carlo模拟来确定团簇生长概率和途径，和（5）构建了一个框架，用于将详细的化学反应机制与反应流和气溶胶动力学模拟联系起来，从而可以预测颗粒浓度和尺寸分布。从最近的工作中，他们已经确定了继续研究这个问题的最重要领域：（1）改进多环硅氢分子和具有多个官能团的硅氢分子的化学描述，（2）改进将这些分子纳入确定性和KMC模拟中，（3）将这些详细的成核模型与气溶胶动力学模型联系起来，从而为实验上可获得的量（如颗粒浓度和尺寸分布）提供结果。本科生，包括传统上代表性不足的群体的成员，将有机会通过布法罗的纳米结构超导体REU网站参与该项目和相关工作，Swihart是PI，并通过其他有针对性的计划，如麦克奈尔学者计划，路易斯·斯托克斯少数民族参与联盟（LS-AMP）计划和大学科学与技术入学（C-STEP）计划。该项目的实例将用于西北大学Broadbelt的应用分子模拟课程，该课程将增加一个关于动力学蒙特卡罗模拟的新课程模块，并将用于纽约州立大学布法罗Swihart的气溶胶科学与技术课程，这是一个新的课程，作为2003年春季的专题课程讲授，并将于2005年春季永久性地添加到课程中。这两门课程吸引了研究生和本科生，扩大了该项目对教育的影响。

ABSTRACTPI: Mark T. Swihart and Linda BroadbeltInstitution: SUNY Buffalo and Northwestern UniversityProposal Number: 0500249 and 0500320Title: Detailed Chemical Kinetic Modeling of the Homogeneous Chemical Nucleation of NanoparticlesIntellectual Merit: Particulate contamination is a leading cause of yield loss in semiconductor processing. As integrated circuits become smaller, and as improved cleanroom technology eliminates external sources of particles, homogeneous nucleation of particles within the processing environment is rapidly becoming the most important source of particulate contamination. In most cases, these particles are generated via the chemical nucleation processes that will be considered in this project, rather than by condensation of the supersaturated vapor of a pure material. Fundamental understanding of the chemical nucleation process is important if one is to control particle formation. This same understanding can help in design methods for aerosol synthesis of nanoparticles and nanostructured materials that are the building blocks of nanoscale science and engineering. The most detailed and informative approach to modeling chemical nucleation is found at the mechanistic level. In this approach, particle nucleation is described by a network of elementary chemical reactions whose rates can be related to properties of the participating species. This project continues the PIs' collaboration on this topic in which they have applied two complementary methodologies, automated reaction mechanism generation and kinetic Monte Carlo (KMC) simulation, to the development of mechanistic understanding of silicon nanoparticle nucleation. In recent work, they have (1) developed improved algorithms for determining species uniqueness and identifying rings in complex polycyclic clusters, (2) carried out extensive quantum chemical calculations on silicon-hydrogen clusters and generalized the results as a group additivity scheme, (3) developed improved methods for selective generation of reaction pathways, and applied these methods to identify the critical cluster size for particle nucleation and key reaction pathways for silicon nanoparticle nucleation, (4) applied kinetic Monte Carlo simulation to identify cluster growth probabilities and pathways, and (5) constructed a framework for linking detailed chemical reaction mechanisms to reacting flow and aerosol dynamics simulations that can predict particle concentrations and size distributions. From this recent work they have identified the most important areas for continued research on this problem as (1) improved descriptions of the chemistry of polycyclic silicon hydrogen molecules and silicon-hydrogen molecules with multiple functional groups, (2) improved incorporation of such molecules into both deterministic and KMC simulations, and (3) linking of these detailed models of nucleation to aerosol dynamics models that provide results for experimentally accessible quantities like particle concentration and size distribution.Broader Impacts: Undergraduates, including members of traditionally underrepresented groups, will have opportunities to participate in this project and related work through an REU site on nanostructured seminconductors in Buffalo, for which Swihart is the PI, and through additional targeted programs such as the McNair Scholars program, the Louis Stokes Alliance for Minority Participation (LS-AMP) program, and the Collegiate Science and Technology Entry (C-STEP) program. Examples from this project will be used in Broadbelt's Applied Molecular Modeling course at Northwestern, for which a new course module on kinetic Monte Carlo simulations will be added, and in Swihart's Aerosol Science and Technology course at SUNY Buffalo, which is a new offering, taught as a special topics course in spring 2003, and being permanently added to the curriculum in spring 2005. Both of these courses attract both graduate and undergraduate students, broadening the impact of this project on education.