As integrated circuit technologies are approaching their physical limitations with current lithographic patterning methods, new approaches with improved spatial resolution are required to keep this $200 billion market stable. A bottom up or self-assembly approach driven by the elastic interactions is widely viewed as a promising technique for the fabrication of structures such as nanowires, quantum dots and nanoscale surface patterns. However, to follow this approach and create structures in a desired manner, a reliable means to engineer the size and shapes that the patterns adopt during self-assembly is essential. In the proposed work, alloying will be explored as a means to achieve control over the shape, size and spatial pattering of strained self-assembled structures on surfaces. The investigator will develop computational models that accounts for features unique to alloyed systems such as differences in transport properties and segregation induced by morphology dependent elastic fields. The composition and strain dependence of the material parameters will be obtained from atomic scale simulations. The investigator has close ties with an experimental group based in the semiconductor industry, which will allow for direct assessment of the proposed modeling effort.
The multiscale methods that will be developed in the project will be broadly applicable to analyze nanoscale patterning in a variety of material systems, but the immediate focus will be on alloying of Si surfaces with Ge. The Ge/Si system has the advantage that in addition to potential applications in renewable energy devices and biological sensors, it is also naturally compatible with the well developed Si integrated circuit fabrication technology. The project will provide an opportunity for students to both collaborate with experimentalists in the semiconductor industry and to develop advanced computational skills. The students trained on this project will be well positioned to pursue careers in academia and in the semiconductor and energy industries. The progress made in the computational methods will be included in the course that the PI has created to promote hands-on simulation experience.
