学术活动发布与订制系统

Transport phenomena play an important role in a wide range of applications including film growth for energy-efficient electronic devices, novel material processing for photovoltaic applications, and nanomaterials for treatment of cancer. Numerical simulation of transport phenomena, including heat and mass transfer, fluid dynamics, phase change, and chemical reactions, provides an important means to acquire critical information unavailable with experimental measurement, obtain advanced understanding of the underlying physics, and achieve improved process design and control. In this talk, two examples of numerical study will be given in the respect of chemical vapor deposition for electronic manufacturing and magnetic nanoparticle hyperthermia for cancer treatment.

In the study of chemical vapor deposition, complicated chemical reaction kinetics has been developed and incorporated into a comprehensive model for fluid flow, heat and mass transfer, and electromagnetic dynamics. This model was used to study the growth of silicon carbide film from vapor phase in a real reactor. Advanced understanding of chemical reaction paths, film etching mechanism, and the effects of major operational parameters has been achieved. Information obtained through the parametric study allows material scientists to link growth conditions to growth rate, defect formation, and material properties, and ultimately, lead to improved system design and optimized processing conditions.

The numerical study magnetic nanoparticle hyperthermia is focused on the behavior of nanofluid transport in porous tissue using a multi-scale approach. A multi-physics model has been developed to consider particle-surface interaction as well as macroscale particle transport in fluid and tissue deformation using finite volume and particle tracking methods. We have used this model to study the flow and deposition of nanofluid in tissue during an intratumoral infusion process that involves complex physicochemical processes with large disparity in length and time scales. The study shows that tissue deformation and particle deposition are important in determining the particle distribution after injection. The appropriate combinations of injection parameters have been identified. The multi-scale approach can be applied to target drug delivery using nanocarriers and nanofabrication with colloidal fluids.

Dr. Ronghui Ma currently holds a position of Associate Professor of Mechanical Engineering, University of Maryland, Baltimore County. Prior to joining University of Maryland in 2004, she worked as a Postdoc fellow at University of Pennsylvania. Dr. Ma earned her Bachelor degree from Zhejiang University, 1991, master degree from Southeast University, 1994, and PhD degree from State University of New York Stony Brook University, 2003, all in mechanical engineering. Dr. Ma’s research lies in computational thermal fluid. She is interested in solving problems that involve transport of heat, mass, and momentum, phase change, chemical reactions, colloidal fluid flow, etc, using various computational methods such as finite volume/finite element, meshless method, particle tracking, and molecular dynamic simulation. She has experience of developing multi-physics and multi-scale models for solidification, film/bulk crystal growth from both liquid and vapor phases, and interactions of nanofluid/nanoparticles with biological tissue for biomedical applications. Her recent research effort is to use statistic approaches (such as Monte Carlo method and Bayesian inference) to address the random nature of biological tissues and its influence on the delivery of drugs and nanomedicines to tumors. Her research has been supported by National Science Foundation and industries.