This Small Business Innovation Research (SBIR) Phase I research project will develop software for emerging combinatorial technologies. The feasibility of the proposed approach will be investigated for plasma-assisted growth of carbon nanotubes. Combinatorial technologies have been developed to grow nanocrystal compounds whose properties are unmatched by other materials. These compounds are used for many applications in molecular-scale electronics and sensors, catalysis, and biomaterials. Progress in the virtual design of combinatorial methods lags behind experimental advances since existing atomistic models are too slow, while mesoscopic (continuum) codes are not capable of capturing nanoscale effects. This problem will be addressed by developing Multi-Scale Computational Environment (MSCE) that consists of a reactor-scale module for gas/plasma-phase and surface processes, a Kinetic Monte Carlo (KMC) module for the growth of molecular structures, a Molecular Dynamic (MD) module for the self-assembly of atoms into molecular structures, a "Gap-tooth" module for bridging reactor-scale and atomistic KMC simulations, and a "Coarse timestepper" module for coupling KMC and MD modeling. This tool will work on length and time scales that are a million times disparate. It is proposed to use continuum CFD-ACE and atomistic KMC-FILM tools both developed by CFDRC as well as publicly available MD-NAMD software. The focus of proposed work will be on the development of the Coarse timestepper and the Gap-tooth modules as well as integrating all modules into a single unit.
The proposed work will create a virtual laboratory for combinatorial technologies such as advanced sputtering, thermal and plasma-assisted chemical vapor deposition, and surface templating. This computational laboratory will be used for understanding and optimizing critical processes in carbon nanotube nucleation and growth, fabrication of nanophase biomaterials and semiconductor nanocrystals, nanoscale magnetism, and ultra-selective catalysis.
