Predictive Computational Modeling of Two-Dimensional Materials: Defects and Morphologies

The recent discovery of two-dimensional (2D) semiconducting materials such as MoS2 and MoSe2 has intensified the research efforts in these materials. These materials exhibit unique properties due to the 2D confinement, but they, unlike graphene, also possess the ability to switch between conducting and insulating state, offering a potential to yield revolutionary new technologies. The research efforts have been primarily based on experimental exploration based on various synthetic routes, and significant gaps exist in the fundamental understanding of what determine their bulk and defect structures and morphologies, as well as how they influence their properties. Due to the small length scale involved, computational modeling is essential for developing such understanding. Phase field crystal (PFC) modeling is uniquely suited for this problem because of its ability to resolve atomic-scale structure and its extended time-scale comparable to those associated with synthesis. Intellectual Merit: Our multidisciplinary project addresses the challenge of understanding multiscale phenomena associated with the formation of nanostructures by exploiting recent developments in PFC models, which follow the dynamics of individual atoms over diffusive time scales. Originating from classical density functional theory, the PFC method naturally incorporates elastic/plastic deformations and crystalline defects, and has already been used to simulate interfacial evolution during solid-liquid phase transitions. We will develop a new PFC-based computational methodology for modeling the structure and the synthesis of two-dimensional, multicomponent materials. The models will be parameterized and validated with the aid of atomistic simulations and experimental results. Defects such as grain boundaries, which are important in nanodevice development, will be examined. Amplitude/phase equations similar to traditional phase field models will be derived to simulate larger, three-dimensional structures built from the 2D blocks. This will reveal how the 2D building blocks interacts with each other, and how defects such as grain boundaries are distributed over a larger scale. We will build on our efficient numerical algorithms developed under previous funding and tailor it to the new models. These tools will advance the field of materials science by providing a framework for the computational discovery of the fundamental mechanisms underlying synthesis of 2D materials and their assembly. Broader Impacts: 2D semiconductors and their heterostructures offer broad applications, ranging from nanosized transistors and efficient light emitting diodes to highly sensitive chemical sensors. The development of efficient, predictive computational methodologies that are tailored to examine 2D materials over the length and time scales associated with their synthesis will accelerate the realization of such technologies. The framework can be extended to examine other 2D materials including topological insulators and topological superconductors with 2D structures. Graduate students will receive interdisciplinary training and will present their findings at conferences, which would enhance their educational experience. Furthermore, a symposium on PFC models will be organized. The proposed work will broaden the participation of underrepresented populations, as the PI is female, and she and co-PIs will continue to make every effort to recruit students with diverse backgrounds. The PFC codes will be disseminated through Materials Commons at University of Michigan. Educational outcome in