Biography:
The Gartner group is developing advanced computational approaches to understand and predict the properties of polymers and soft materials for energy, sustainability, and technology applications. The group uses machine learning-enabled computational tools to uncover the chemical and physical driving forces underlying thermodynamics, transport, and assembly in fluids and functional soft matter.
Current research interests include:
- Polymer sustainability, polymer degradation, polymer recycling & upcycling
- Polymer physics, solution processing of polymers, polymer architecture effects
- Polymer- and nanoparticle-based electrical & optical nanomaterials
- Liquid state theory, molecular simulations, and statistical mechanics
- Developing machine learning interaction potentials to predict the properties and phase behavior of fluids and materials
Disciplines:
- Materials and Nanotechnology
- Energy and Sustainability
Education
Postdoc, Princeton University (2019-2021)
Ph.D., University of Delaware (2014-2019)
Process Engineer, Applied Materials, Inc. (2011-2014)
B.S. (with Honors), University of California, Berkeley (2007-2011)