Modeling Long-Time and Macroscopic Behavior of Complex Atomistic Systems with Application to Silicon-based Lithium Batteries

California Institute Of Technology, Pasadena CA

Investigators

Abstract

In a number of areas of application, the behavior of systems depends sensitively on properties that pertain to the atomistic scale, i.e., the angstrom and femtosecond scales. However, often the properties and behaviors of interest are macroscopic and take place on the scale of centimeters to meters, and are characterized by slow evolution on the scale of minutes to years. No computationally-tractable atomistically-based models appear to be as yet available to study such slow phenomena over time scales of the order of minutes to years and in macroscopic samples while maintaining a strictly atomistic description of the material. This project addresses this chronic gap in predictive science. This approach offers unprecedented capability for the study of device-level properties mediated by slow, coupled, thermal-mechanical-chemical processes at the atomistic scale. Thus, beyond this application to Li-ion batteries, this methodology may be expected to have far-reaching impact as an enabling tool in applications requiring the careful accounting of atomic-level processes simultaneously with the elucidation of macroscopic properties over long time scales, e.g., stability of alloys and irradiated materials, electromigration in interconnects, corrosion and environmentally-assisted cracking, among others. The empirical atomic-level kinetic models, variational meanfield approximation schemes, variational time-discretization algorithms and spatial coarse-graining schemes developed under the project will be implemented into a verified and validated high-performance computing solver, the Extended Quasicontinuum (XQC) solver, for broad dissemination in the community. This work is concerned with the further development and implementation of a novel multiscale analysis methodology. It combines elements of non-equilibrium statistical mechanics and kinetic and approximation theory. This approach offers unprecedented capability for the study of the long-term macroscopic behavior of complex multi-species atomistic systems mediated by slow, coupled, thermal-mechanical-chemical processes at atomistic scales. Application of the novel methodology to the investigation of silicon lithiation, both in bulk and in nanowires (SiNW) is considered. The potential use of silicon as a high energy-density anode material in Li-ion based batteries is hampered by the extensive mechanical degradation that occurs during lithiation. The current global market size for such storage, just for vehicle applications, is estimated at $1.5 billion, and is expected to grow to by more than 3,000% by the end of the decade. The ability to simulate silicon lithiation predictively at the device level and over large numbers of charge/discharge cycles is expected to enable the identification and assessment of novel nano-engineered materials for Li battery applications.