Building Bridges between Computational Chemistry and Experiment at the Nanoscale: Impacts on Energy Storage, Agriculture, and the Environment

BIOSKETCH: My group uses theory and modeling to link the macroscopic properties of environmental interfaces to molecular-level understanding. We study the structure, reactivity, and transformations of metal (hydr)oxide (nano)materials under a wide range of environmental and operational conditions, which allows for scientific connections to be made with engineers, geoscientists, biologists, and a wide range of chemists. The primary methodology used in my group is ab initio thermodynamics, which are models that employ total energy information from electronic structure calculations (such as density functional theory) along with expressions from statistical mechanics, electrochemical principles, and thermochemical data. Projects in my group are expanding to incorporate machine learning architectures to assist, for example, in identifying reactivity descriptors (in terms of geometry/electronic structure) in systems of increasing complexity.

One focus in my research group centers on complex metal oxide materials that are ubiquitous in catalysis and used in many forms in Li-ion batteries, such as LiCoO2 (LCO) and its compositionally tuned variant, Li(NixMnyCo1-x-y)O2 (NMC). Experimental studies from my collaborators have identified cation release (dissolution) as a key pathway of NMC toxicity towards model organisms. We used a combined DFT and thermodynamics approach to model cation release, which successfully recovers the trend of incongruent cation release from NMC and which goes on to provide molecular-level guidance on the design principles that govern how complex oxides release cations in aqueous settings [Bennett et al., Environmental Science and Technology, 52, 5792 (2018)]. In ongoing work, my group is applying the lessons learned to suggest new compositions of complex metal oxides that do not release toxic cations. Recently, we extended out DFT + thermodynamics modeling of metal release to understand how different Cu-bearing nanomaterials perform in plant micronutrient delivery and disease suppression [Ma et al., Nature Nanotechnology, 15, 1033 (2020)]. We continue to build on our modeling to include a wider range of materials and to further aqueous chemistry of released ions.