We develop mathematical theories, AI-based algorithms, and computational simulations across the atomistic, particle, and continuum levels to model chemical engineering processes, with the aims of gaining fundamental scientific knowledge and devising next-generation applications in in-space manufacturing, renewable energy, drug delivery, geological formation, electrochemical impedance spectroscopy, and membrane-based separation.
Faculty
Ph.D., 2017, Cornell University
Research Interests: Complex Fluid Dynamics, Colloid and Interface Science, Electrokinetics, and Rheology
Ph.D., 1992, University of Minnesota
Research Interests: Cellular Engineering, Cell Adhesion, Cell Migration, Molecular Motors, Mathematical Biology
https://hibbitts.rc.ufl.edu/group.html
Research Interests: Heterogeneous Catalysis, Kinetic Studies, Density Functional Theory, Catalyst Synthesis and Characterization
Ph.D., 2002, University of Notre Dame
Research Interests: Molecular and Multi-scale Modeling, Nanoscale Transport Phenomena, Non-equilibrium Statistical Mechanics
Research Interests: Numerical Simulations of Complex Fluids: Reactive Flows in Porous Media, Hydrodynamic Interactions, Dynamics of Filament Networks
https://sites.google.com/view/ranganarayananuflab/home
Ph.D., 1978, Illinois Institute of Technology (1981)
Research Interests: Interfacial instabilities, Transport phenomena with life support, materials science and biomedical applications
https://www.che.ufl.edu/orazem/
Research Interests: Electrochemical Engineering: Electrochemical Impedance Spectroscopy, Corrosion (including cathodic protection), Current Distribution in Electrochemical Systems, Fuel Cells, Mathematical Modeling.
Research Interests: Sustainability, Process Synthesis, Optimization, Energy Efficient Separations (membranes and adsorption)
Ph.D. 2018, The Ohio State University
Research Interests: Polymer Membranes, Polymer-Protein Conjugates, Self-Assembly, Computational Materials Design
Ph.D., 1981, University of Minnesota (1982)
Research Interests: Bioprocess Engineering, Process Modeling, Optimization, and Control, Machine Learning