Detailed Chemical Kinetic Modeling of the Homogeneous Chemical Nucleation of Nanoparticles

摘要提案标题： 详细的化学动力学模型 纳米颗粒的均匀化学成核提案编号：CTS-0087315主要研究者：Mark Swihart机构： 该提案的目的是构建化学反应的机理模型，用于预测导致粒子核产生的簇形成。 构建机理模型的主要挑战是考虑所有可能的反应、产物和活性中间体所产生的极端复杂性。 反应机理的自动生成将用于处理复杂性。 将开发一个系统来将一组反应物和规则转换为具有速率参数的详细化学机理。 PI计划将重点放在硅沉积上，因为该系统在微电子工业中非常重要，并且该系统的一些实验数据可用于与模拟进行比较。 这种方法将用于预测硅纳米颗粒污染物的形成，这是半导体加工中产量损失的主要原因。 该项目将是PI和共同PI（琳达布罗德贝尔特）在西北大学的合作。 这项工作可能会导致一个更普遍的预测描述的粒子形成。 将使用文献中可用的有限数据进行模型验证。 这项工作可能是有用的，在预测的影响，改变操作条件对颗粒的形成和污染的潜力，以提高半导体材料的产量。

AbstractProposal Title: Detailed Chemical Kinetic Modeling of the Homogeneous Chemical Nucleation of nanoparticlesProposal Number: CTS-0087315Principal Investigator: Mark SwihartInstitution: SUNY BuffaloThe objective of this proposal is to construct mechanistic models of chemical reactions for use in the prediction of cluster formation leading to the production of particle nuclei. The major challenge is constructing mechanistic models is the extreme complexity created by accounting for all possible reactions, products, and reactive intermediates. Automatic generation of reaction mechanisms will be used to deal with the complexity. A system will be developed to convert a set of reactants and rules by which they react into a detailed chemical mechanisms with rate parameters. The PIs plan to focus on silicon deposition because this system is of importance in the microelectronics industry and because some experimental data on this system are available for comparison with simulations. This approach will be employed to predict silicon nanoparticle contaminant formation, which is a leading cause of yield loss, in semiconductor processing. This project will be a collaboration between the PI and co-PI (Linda Broadbelt) at Northwestern University. This work could lead to a more general predictive description of a particle formation. Model validation will be performed with limited data available in the literature. This work may be useful in predicting the effects for changing operating conditions on particle formation and contamination with the potential to increase yields of semiconductor materials.