This award supports theoretical research and educational activities in computational materials science, with a focus on the controlled growth of nanostructured materials.
Nanostructured materials, including semiconductor quantum dots and nanowires, hold the promise to yield revolutionary new technologies. The realization of this promise has been hindered to date by the challenges inherent in reproducibly synthesizing and assembling arrays of such nanostructures with controlled morphologies and compositions. Computational modeling is essential for understanding the complex fundamental processes underlying nanostructure growth and self-assembly. However, current state-of-the-art computational methods are not well suited to such studies because of the difficulty in accounting for the atomistic processes that control growth, while simulating over the larger length and time scales associated with self-assembly. The PIs, three materials scientists and a mathematician, propose to develop a new computational methodology that addresses these issues, in order to investigate quantum-dot formation in thin-film heteroepitaxy and nanowire growth mediated by liquid catalysts.
This multidisciplinary project addresses the challenge of understanding multiscale phenomena associated with the formation of nanostructures by exploiting recent developments in phase field crystal (PFC) models, which resolve atomic spatial scales on diffusive time scales. 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. The team will develop a new PFC-based computational methodology for modeling solid-vapor, liquid-vapor and faceted solid-liquid interfaces, which are commonly present during the growth of crystalline nanostructures. The models will be parameterized and validated with the aid of atomistic simulations and experimental results. Amplitude/phase equations similar to traditional phase field models will be derived to allow larger domains to be simulated. This will reveal how atomistic features and processes affect morphological evolution at larger scales. We will develop new efficient numerical algorithms that will enable simulations of large 3D systems, as well as novel tools for data extraction and visualization. These tools will advance the field of computational materials science by providing a framework for the computational discovery of the fundamental mechanisms underlying synthesis and assembly of nanostructures.
Courses on crystal growth for high school students are planned as part of the California State Summer School for Mathematics and Science at UC Irvine, along with additional outreach activities at the Ann Arbor Hands-On Museum. These activities will help develop the future generation of mathematicians, scientists and engineers. Graduate students will receive interdisciplinary training and will present their findings at conferences, enhancing their educational experiences. Furthermore, a symposium on the PFC approach will be organized. In collaboration with the National Institute of Standards and Technology, a FiPy version of the PFC codes will be developed and will be disseminated through their website for use in education and research.
NON-TECHNICAL SUMMARY:
This award supports theoretical research and educational activities in computational materials science, with a focus on the controlled growth of nanostructured materials.
Artificial materials composed of building blocks on the scale of some ten thousand times smaller than the width of a human hair but still larger than an atom can have unique properties and capabilities that differ dramatically from bulk crystalline materials. The properties of these nanostructured materials and their lean tiny cousins, nanostructures, can be controlled through the way the building blocks are arranged; they may even arrange themselves through a process of self-assembly. Nanostructured materials including semiconductor quantum dots and nanowires, hold the promise to yield revolutionary new technologies. Realizing this promise has been hindered by difficulties in controlling their structures and compositions. The use of computers to model nanostructures and nanostructured materials is essential for understanding the complex fundamental processes underlying nanostructure growth and self-assembly. However, current state-of-the-art computational methods are not well suited to such studies because of the difficulty in accounting for the atomic scale processes that control growth, while simulating over the larger length and time scales associated with self-assembly, involving the organization of the building blocks. This grant will support the development of a new computational methodology that addresses these issues, in order to investigate quantum-dot formation and nanowire growth. The team will also develop new efficient numerical algorithms that will enable simulations of large three-dimensional systems, as well as novel tools for data extraction and visualization. These tools will advance the field of computational materials science by providing a framework for computational discovery of the fundamental mechanisms underlying synthesis and assembly of nanostructures.
Courses on crystal growth for high school students are proposed as part of the California State Summer School for Mathematics and Science at UC Irvine, and additional outreach activities are planned at the Ann Arbor Hands-On Museum. These activities will help develop the future generation of mathematicians, scientists and engineers. Graduate students will receive interdisciplinary training and will present their findings at conferences, enhancing their educational experiences. Furthermore, a symposium on aforementioned computational techniques will be organized. In collaboration with the National Institute of Standards and Technology, a Python-script version of the simulation software will be developed and will be disseminated through their website for use in education and research.
