ECCS-CDS&E: Predictive modeling of atomically thin multifunctional semiconductors

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Atomically thin two-dimensional materials are promising for novel electronic and optoelectronic device applications. Most work on two-dimensional materials focuses on graphene and transition metal dichalcogenides. This work focuses on materials that contain elements with lone-pair electrons such as tin selenide, which crystallize in layered structures and simultaneously display many interesting functional properties. The project will use state-of-the-art predictive materials simulation algorithms to uncover the fundamental materials physics and functional properties of these novel two-dimensional materials and identify promising candidates for electronic and optoelectronic device applications. The proposed work also involves the development and application of innovative simulation algorithms and high-performance computing tools for the high-fidelity predictive modeling of novel materials and devices in order to advance the current frontiers in electronics. This project will also advance the education, training, and mentoring of graduate and undergraduate students in materials physics, electronic and optoelectronic devices, computational techniques, and high-performance computing. The proposed work also will produce open-source computer codes that will be shared with the educational and research communities. The research findings will be incorporated in the undergraduate curriculum and communicated to the general public through outreach presentations.The goal of the proposed research is to understand and predict the structural and functional properties (structure, thermodynamics, band structure, vibrational properties, electronic and thermal transport, optical response, strain effects, band alignments) of freestanding and substrate-deposited atomically thin layered semiconducting materials with predictive calculations based on density functional theory and related methods. Materials to explore include SnSe and GeSe, which contain cations with lone-pair electrons. These materials crystallize in layered structures and display an array of unique functional properties, such as anisotropic spin transport and unusually strong optical absorbance in the visible range. A genetic algorithm will be applied to identify promising new materials that simultaneously exhibit multiple functionalities for novel electronic, spintronic, and optoelectronic device applications. The findings of the research project are expected to advance the development and manufacturing of novel electronic and optoelectronic devices with functionalities that are limited by current materials availability.