Our research focuses on modeling materials at the mesoscale level, which bridges between atomistic building blocks and macroscopic properties. We are interested in microstructures, their kinetic evolution and implications for performance in a wide range of systems from energy storage materials, structural materials, 2D materials to soft matters. We develop and apply a suite of modeling techniques including the phase-field method, front-tracking method and kinetic Monte-Carlo to perform numerical experiments, utilize parallel computing to accelerate simulations, and develop theory to interpret and generalize simulation results. The ultimate goal is to use modeling to inform and guide the design, fabrication and manipulation of mesoscale structures in both structural and functional materials.
Electrochemically driven phase transformations in energy storage compounds
Many battery electrode materials exhibit first-order phase transformations during operation. The transformation process is coupled with ion diffusion, surface reaction, stress development and other physical processes within the materials, often exerting considerable influence on device performance and degradation. While governed by similar thermodynamic and kinetic principles as in other systems that are more traditional subjects of materials science, phase transformations in electrochemical energy storage compounds also have their unique features. First, the large electrochemical driving force inherent in practical use often drives the systems far from equilibrium, which causes metastable transformation pathways to be more easily observed. Secondly, battery electrodes consist of a large number of micro- or nano-particles that weakly interact with each other and the surrounding electrolyte. The nucleation and growth kinetics in such highly partitioned open systems are distinct from bulk materials and the classical theories may no longer be applicable. We are employing mesoscale simulations to discover and understand novel phase transition behavior that results from these features, with particular interest in a number of important electrode materials for lithium and sodium batteries. Our aim is to establish a general theoretical framework for predicting phase transformation phenomena in electrochemical energy storage systems, to guide materials selection and microstructure design.
2D crystal growth
Single layer 2D materials such as graphene and transition metal dichalgenides have attracted considerable research interest because of their many novel properties compared to their bulk counterparts. Chemical vapor deposition (CVD) is one of the most promising techniques towards scalable synthesis of large-area, high quality 2D materials. However, CVD synthesis often results in a rich variety of crystal shapes that are challenging to control, and the formation mechanisms of such diverse morphologies are poorly understood despite their important implications for the functionality of 2D materials. We are using mesoscale modeling of 2D crystal growth process to explain experimentally observed crystal shape evolution and elucidate the dependence of crystal morphologies on growth process parameters. Our goal is to apply predictive modeling to guide the control and optimization of the interface morphologies of 2D single and poly-crystals.