Cluster formation processes are all encompassing and found in countless applications important to society medical research, creation of new and novel materials, and developing low cost space-based world wide telecommunications, to name a few. It has been shown recently that deposition of size-specific clusters opens up a new class of surface nanostructure fabrication of materials that have size-specific catalytic properties. Additionally, to reduce cluster formation in pulsed laser ablation deposition of thin films the size of clusters in the vicinity of a target surface must be controlled. These are just two of many examples that demonstrate the importance of developing a theory and simulation tool capable of modeling nonequilibrium spatial distributions of cluster formation and evolution to advance new fabrication technologies. Predicting cluster size distributions and velocities in supersonic reaction control jets will reduce the cost of space-based telecommunications by allowing intelligent placement of sensitive surfaces such as solar cell arrays. Novel materials for medical surgical procedures are being developed by cluster formation processes to create pure microscopic implants of pharmaceuticals in strategic locations. Clearly the above applications have many important global, societal implications.
The predictive modeling of cluster condensation in the gas phase in these engineering applications currently presents a formidable task due to the uncertainties in some of the fundamental rates for nonequilibrium physical chemical processes involving the evolution of clusters and the large variability of flow length scales. Therefore, a logical step in the development of simulation tools is to consider the simpler phenomenon of supersonic jet expansion in which the process of cluster formation and growth is coupled only with non-equilibrium gas dynamics. Successful modeling of cluster behavior in supersonic jets will serve as a prototype for future modeling of more complex technologies involving the evolution of clusters. Successful modeling of a non-homogenous two-phase flow system will also allow us to establish the relative importance of individual fundamental cross sections.
The subject of this proposed research is the quantitative characterization of clusters formed by homogeneous nucleation in a supersonic jet, in terms of non-equilibrium spatial distributions of cluster size and internal and kinetic energies. We propose to model the process of cluster formation and evolution in supersonic jets by a multiscale computational model. The proposed model is based on a kinetic particle simulation method, the direct simulation Monte Carlo (DSMC), which is applicable in the transitional to rarefied flow regime. The proposed model is multiscale because, in addition to DSMC, continuum fluid dynamics (CFD)/Navier-Stokes (NS) and molecular dynamics (MD) formulations will also be used. The CFD Navier-Stokes approach will be used to simulate the initial expansion stage of the dense gas, during which the condensation can be neglected. Molecular dynamics will be used primarily to develop a cluster reaction cross section data base for DSMC and to extend the DSMC simulation capabilities further to address issues related to condensation due to non-binary collisions. A statistically efficient approach will be developed for estimation of both the reaction cross sections and post-collisional outcomes. The primary emphasis of this work involves systems described by a pair-wise potential, since multi-scale modeling and simulation credibility must first be established for well known, simple gases. Rayleigh scattering data sets providing not only average cluster quantities, but cluster distributions as well, will be used for simulation validation. These data have been under-utilized and represent an important resource for the modeling community.
The project will advance discovery and understanding while promoting teaching and learning. A new graduate course on computational modeling of rarefied flows with applications to materials processing will be developed. The course will involve the learning and usage of the MD-DSMC methodology to be developed in the proposed research. More specifically, after taking this course Aerospace and Mechanical Engineering and Engineering Science students will be able to simulate coupled rarefied-condensation flows for chemical systems with known interaction potentials. This course is one of the very few in the nation where students perform a class project requiring the use of DSMC for modeling the effects of rarefied gas flows on spacecraft. Undergraduate and graduate students will participate in the proposed schololarly activities with outreach to minority students through various programs at Penn State and direct solicitation of colleagues. The proposed research combines elements of rarefied gas dynamics, physical chemistry, massively parallel computing, materials science, and statistics and is, therefore, multidisciplinary.
