Silicon Based Nanostructures Experiment Modeling PDF Download

In today's nanotechnology, a critical issue is to gain the ability to control the structure and function of matter with a deeper understanding of the quantitative and qualitative relationship among their synthesis conditions, structures, and properties. Experiments may provide information regarding the behavior of nanomaterials, but their interpretations are often controversial due largely to the difficulty of direct measurement. Hereupon, with the amazing advance in computer technology since the late 20th century, computational modeling in science and engineering is increasingly important particularly in the fields of nanoscience and nanotechnology while it can provide researchers with significant insights into atomic-level interactions in various materials systems and underlying fundamental theories. The ability of engineering thermal conductivity of materials on the nanoscale has become extremely important in various applications including electronics and energy storage/conversion technologies. Due to technical difficulties in experimentally measuring the thermal conductivity of disordered and complex nanostructures, there has been much interest in use of theoretical and computational methods to investigate thermal transport properties nanostructured materials. One computational method that can perform an accurate analysis for the thermal conductivity of new or complex systems is molecular dynamics (MD), due to its capability of predicting the behaviors of atoms in large systems. In this work, we have developed a comprehensive MD-based computational platform capable of predicting and explaining thermal transport in disordered and complex nanostructured materials. The unique features include construction of realistic nanostructures, determination of reliable force fields, and direct simulation of large systems, which are allowed by coupling various state-of-the-art computational methods including quantum mechanics, molecular mechanics, statistical theories, and massively parallel computing. The computational scheme was applied to describe thermal transport in various silicon and carbon-based disordered and nanostructures. First, the effects of defects including vacancy clusters, substitutional dopants, and dopant-defect complexes on the thermal conductivity of bulk crystalline silicon were investigated. Next, we analyzed the factors affecting heat transport in silicon-germanium and ternary silicon-germanium-tin alloys. Lastly, we performed the analysis of heat transport in silicon-based nanostructures such as nanowires and polycrystalline structures.