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

合作研究：纳米粒子均质化学成核的详细化学动力学模型

• 批准号: 0500249
• 负责人: Mark Swihart
• 金额: --
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-01 至 2008-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0500249&HistoricalAwards=false
• 关键词: Collaborative; Research; Detailed; Chemical; Kinetic

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.

摘要PI：Mark T. Swihart 和 Linda Broadbelt 机构：纽约州立大学布法罗分校和西北大学 提案编号：0500249 和 0500320 标题：纳米粒子均质化学成核的详细化学动力学模型 智力优点：颗粒污染是半导体加工中产量损失的主要原因。随着集成电路变得越来越小，并且随着洁净室技术的改进消除了外部颗粒源，加工环境中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，这些颗粒是通过本项目中将考虑的化学成核过程产生的，而不是通过纯材料的过饱和蒸气的冷凝产生的。如果要控制颗粒形成，对化学成核过程的基本了解非常重要。这种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，这些材料是纳米科学和工程的基石。最详细、信息最丰富的化学成核建模方法是在机械层面上找到的。在这种方法中，粒子成核是通过基本化学反应网络来描述的，其速率可能与参与物种的性质相关。该项目延续了 PI 在此主题上的合作，其中他们应用了两种互补的方法，即自动反应机制生成和动力学蒙特卡罗 (KMC) 模拟，来发展对硅纳米粒子成核的机械理解。在最近的工作中，他们（1）开发了改进的算法，用于确定物种唯一性和识别复杂多环簇中的环，（2）对硅氢簇进行了广泛的量子化学计算，并将结果概括为群可加性方案，（3 ）开发了选择性生成反应路径的改进方法，并应用这些方法来确定颗粒成核的临界簇尺寸和硅纳米颗粒成核的关键反应路径，（4）应用动力学蒙特卡罗模拟来确定簇生长概率和路径，以及(5) 构建了一个框架，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，可以预测颗粒浓度和尺寸分布。从最近的工作中，他们确定了继续研究该问题的最重要领域：（1）改进对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）改进将此类分子纳入确定性模拟和 KMC 模拟，以及 (3) 将这些详细的成核模型与气溶胶动力学模型联系起来，这些模型提供了可通过实验获得的量（如颗粒浓度和尺寸分布）的结果。 更广泛的影响：本科生，包括传统的成员代表性不足的群体将有机会通过位于布法罗的 REU 纳米结构半导体站点（Swihart 是该站点的 PI）以及通过麦克奈尔学者计划、路易斯·斯托克斯少数民族参与联盟等其他有针对性的计划参与该项目和相关工作(LS-AMP) 计划和大学科学技术入门 (C-STEP) 计划。该项目的示例将用于西北大学 Broadbelt 的应用分子建模课程，其中将添加一个关于动力学蒙特卡罗模拟的新课程模块，以及纽约州立大学布法罗分校 Swihart 的气溶胶科学与技术课程，这是一个新课程，教授2003 年春季作为专题课程，并于 2005 年春季永久添加到课程中。这两门课程都吸引了研究生和本科生，扩大了该项目对 教育。