Motivation and General Overview
Understanding
phenomena from science and processes from engineering is no longer an
exclusive realm of theory and experiment; computation is now regarded as an
equal and indispensable partner for the advance of scientific knowledge and
for engineering practice. In an important number of cases, computer
simulations supplement experiment, but in many others, they are the enabling
tool for the study and understanding of complex systems and natural
phenomena that would otherwise be too expensive or dangerous, or even
impossible, to study by direct experimentation. These factors and the
inescapable quest for ever-higher levels of detail and realism in such
simulations, contribute to the inexorable demand for new theory, methods,
and computational tools.
In
principle, all properties of all
materials and phenomena are describable by quantum mechanics (QM),
unfortunately direct use of computational QM is impractical for solving
applications that involve a large number of particles (> ~1K). On the
other side of the length spectrum, phenomenological-based continuum-level
methods are incapable of capturing fundamental nanoscale intrinsic and
extensive properties that define the behavior of matter.
Our research
involves developing first
principles-based theory, methods and efficient multiparadigm computational
algorithms and tools capable of seamlessly bridging length and time scales
to enable de novo design, characterization and prediction of material
properties and processes and their application into solving currently
"impossible" problems. This research leverages on other legacy
achievements at the MCS, including, ReaxFF reactive force fields, eFF
electron force fields, among others.
