Collaborative Research: Large-Scale Patterning of Germanium Quantum Dots by Stress Transfer

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The goal of this collaborative research project is aimed at studying and developing a high-throughput, template-based method for the growth of highly ordered arrays of semiconductor quantum dots in the silicon-germanium system. An integrated approach based on theory, multiscale computer simulation, and experiments will be utilized to perform the study. Atomic-scale computer simulation techniques such as the Monte Carlo method will be employed to identify optimal conditions for generating micro-patterned compositional distributions in a silicon-germanium substrate using stress applied via a patterned, reusable template. The suitability of the compositional variations induced within the substrate, and the resultant surface strain patterns, will then be investigated in the context of growing ordered germanium nanostructures on the substrate using molecular beam epitaxy. A dedicated experimental apparatus will be fabricated for performing the template-based compositional patterning of a substrate silicon-germanium wafer. High-resolution electron microscopy will be performed and used throughout this study in order to establish direct connections with atomic-scale and multiscale simulation predictions.This research will establish materials and operating-condition criteria required for successfully realizing a conceptually simple, cost-effective, template-based method for growing a highly ordered two-dimensional array of germanium nanostructures on silicon-germanium substrates. The primary goals of this work are to understand quantitatively the basic atomistic mechanisms that govern compositional patterning under applied stress and the coupling of this stress to nanostructure ordering, and then the use of this understanding to demonstrate experimentally the germanium quantum dot array formation. If successful, this work could lead to a practical route for fabrication of high-density nanostructure arrays with a variety of potentially important applications, ranging from sensors, to data storage, to quantum computing. Moreover, many of the basic atomistic sub-processes that will be studied, along with the associated computational and experimental techniques that will be developed, may be relevant to a wide range of materials processing applications.