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.
Dendrite growth mechanisms of metal anodes for rechargeable batteries
We are studying how a group of metals with relevance to batteries develop unstable growth morphology during the electrodeposition or electroplating process, a process important for the function of batteries. These metals include alkali metals (e.g. lithium, sodium and potassium) and zinc that have large atomic mobility and high reactivity with the electrolytes used during the battery process. They are very attractive electrode candidates for the next-generation rechargeable batteries that promise several times higher energy density at lower cost. However, the prevalent formation of highly non-uniform morphologies, represented by the growth of filament-like and moss-like structures, presents a major barrier to their successful application since it causes rapid capacity fading and even internal shorting of the batteries. We aim to elucidate the diverse nucleation and growth mechanisms of such unstable plating structures through a combination of mesoscale modeling, scaling analysis and experiments in collaboration with multiple groups. Significant questions to answer include:
1) What is the role of electroplating-induced stress in triggering the formation of unstable electrodeposition morphology?
2) How does the competition between the surface deposition and diffusion, long-range transport and SEI formation kinetics determine the feature size and shape of the electroplated structure?
3) What is the internal microstructure of mossy electrodeposits commonly form on lithium and zinc surface?
Electrochemically driven phase transformations in battery 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 and theory to discover and understand novel phase transition behavior that results from these features, with particular interest in the coupling between stress, defects and phase transition modes. 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.
Efficient prediction and optimization of battery electrode structures
Recently, novel battery electrode architecture such as low-tortuosity and graded electrode structures have demonstrated significant promise in boosting the rate performance of battery cells without compromising their energy density. However, the rational design and optimization of these emerging battery cell structures face tremendous challenge because they involve a much larger design space than traditional electrodes. Currently, the de facto standard method for battery modeling at the cell level is based on the pseudo-2D (P2D) porous electrode simulation, which is computationally expensive for such tasks. We are developing very efficient analytical and semi-analytical methods to accurately predict the battery performance with dramatic computational speedup, which makes the modeling-guided design of novel heterogeneous and 3D battery cell architecture a reality.
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.
Big thanks to our research sponsors!