First-Principles-Based Multiscale, Multiparadigm Molecular Mechanics and Dynamics Methods for Describing Complex Chemical Processes - Multiscale Molecular Methods in Applied Chemistry - page 3

Fig. 1 Hierarchical multiscale, multiparadigm approach to materials modeling, from QM to the
mesoscale, incorporating breakthrough methods to handle complex chemical processes (eFF,
ReaxFF). Adapted from our multiscale group site http://www.wag.caltech.edu/multiscale

Nonetheless, QM methods are essential for accurately describing atomic-level
composition, structure and energy states of materials, considering the influence of
electronic degrees of freedom. By incorporating time-dependent information, the
dynamics of a system under varying conditions may be explored from QM-derived
forces, albeit within a limited timescale ( 1 ps). The prominent challenge for theory

and computation involves efficiently bridging, from QM first-principles, into larger
length scales with predominantly heterogeneous spatial and density distributions,
and longer timescales of simulation - enough to connect into engineering-level
design variables - while retaining physicochemical accuracy and certainty. Equally
challenging remains the inverse top-down engineering design problem, by which
macroscopic material/process properties would be tunable from optimizing its
atomic-level composition and structure. Our approach to this challenge has been
to develop breakthrough methods to staple and extend hierarchically over existing
ones, as well as to develop the necessary tools to enable continuous lateral (multi-
paradigm) and hierarchical (multiscale) couplings, between the different theories
and models as a function of their length- and timescale range - a strategy referred to
here as First-Principles-Based Multiscale-Multiparadigm Simulation .
The ultimate goal is a reversible bottom-up, top-down approach, based on first
principles QM, to characterize properties of materials and processes at a hierarchy
of length and timescales. This will improve our ability to design, analyze, and
interpret experimental results, perform model-based prediction of phenomena, and
to control precisely the multi-scale nature of material systems for multiple applica-
tions. Such an approach is now enabling us to study problems once thought to
be intractable, including reactive turbulent flows, composite material instabilities,

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