Welcome to the home page of the Grover Group at Georgia Tech.
Our group's research activities in process systems engineering focus on understanding macromolecular organization and the emergence of biological function.
Discrete atoms and molecules interact to form macromolecules and even larger mesoscale assemblies,
ultimately yielding macroscopic structures and properties.
A quantitative relationship between the nanoscale discrete interactions and the macroscale properties is
required to design, optimize, and control such systems; yet in many applications, predictive models do not
exist or are computationally intractable.
The Grover group is dedicated to the development of tractable and practical approaches for the engineering
of macroscale behavior via explicit consideration of molecular and atomic scale interactions.
We focus on applications involving the kinetics of self-assembly, specific those in which methods from
non-equilibrium statistical mechanics do not provide closed form solutions.
General approaches employed include stochastic modeling, model reduction, machine learning, experimental design,
robust parameter design, and estimation.
a AFM image of conjugated polymers (Persson);
b microscope image of darapskite crystals (Griffin);
c kinetic Monte Carlo simulation of self-organization in replicating polymers (Walker);
d Combining esperimental data with models to predict the composition of nuclear waste simulants (Maggioni and Kocevska)