Insights into material structures and properties from novel computational approaches have the potential to advance technologies and address critical challenges in a wide variety of fields ranging from photonics to healthcare to environmental sustainability. In materials discovery and development, two critical knowledge gaps remain: elucidating the relationship between the chemical building blocks and the structures they form, and the connection between structures and the corresponding properties they exhibit. In this talk, I will present examples from my prior research which have addressed these gaps. First, I will discuss the use of chemistry-agnostic models to examine the self-assembly of nanoparticles into colloidal crystals in both two and three dimensions, in systems mimicking both metallic alloys and salts. I will examine the influence of increasingly disparate particle size on the stability of mixed, bcc-type crystals using a tunable particle–particle interaction model. Second, I will elucidate the failures of equilibrium molecular dynamics to capture the viscous behavior of some complex solutions and discuss the implementation of a novel pathway for estimating the shear viscosity of structured liquids via non-equilibrium all-atom molecular dynamics and demonstrate its efficacy using lauramidopropyl betaine/sodium dodecyl sulfate micellar fluid as a case study.
Jasmin Kennard is an incoming instructor in the School of Chemical, Biological and Environmental Engineering at Oregon State University. She received a BS in Chemical Engineering from Oregon State University in 2018 and received a PhD in Chemical Engineering from Cornell University in 2024. During her PhD, she worked as an associate at RAND Corporation in the Homeland Security Operational Analysis Center examining how current policy impacts the security of microelectronic supply chains. She also worked on the Polymers team at Schrödinger, Inc. developing improved analysis and solvation pathways for Material Science Maestro software. Her doctoral research focused on high-throughput computational studies of mesoscale self-assembly using chemistry-agnostic models. Specific interests relate to multicomponent systems, and both ordered and solid solution assemblies.