## David A. Kofke## SUNY Distinguished Professor510 Furnas Hall |

Short bio | Research | Publications | Teaching |

Starting from a model for how molecules interact, it is not a simple matter to predict how
a material formed from those molecules will behave. A molecular model might be something
simple, such as the hard-sphere model which postulates that molecules interact like nanoscopic billiard
balls, or somthing quite sophisticated, such as a detailed *ab initio* quantum mechanical
treatment. In either case it is not easy to predict what will happend when 10^{23} of these
particles are put in a box of given volume that is contacted with a constant-temperature bath.
Behavior of interest is quite varied, and could include things such as the
normal boiling point of the material, its viscosity, or its tendency to dissolve in oil or water.

Our research aims to improve the ability of molecular simulation to do this, while also applying molecular simulation to understand the behavior of systems that are interesting and of practical importance. Specific research areas targeted by our group are as follows.

The free-energy perturbation (FEP) method is a core technique in computational chemistry. Despite its importance and wide use, it is frequently applied in ways that are inefficient at best, and incorrect at worst. FEP calculations can be performed in either of two directions, depending on which system is taken as the reference. It is well known that these two calculations lead to results that differ systematically. One mistake commonly made is to assume that both calculations are equally wrong, and the best result is obtained by splitting the difference. By applying modeling concepts to the simulation process itself, we have shown that this heuristic is incorrect, and we are formulating a perspective on these calculations that enables them to be applied much more reliably and efficiently. Because free energy is the key to understanding any thermophysical behavior, this work can impact a very broad range of applications. Examples include pharmaceutical formulation and manufacturing, catalysis design, nanotechnology, biochemistry, and many more such fields in which applications of molecular modeling are at the leading edge of research and development.

An interesting and exciting extension of our work on free energy
methods considers application of molecular simulation to evaluation
of so-called “cluster integrals”. These quantities capture the elementary
contributions of interactions between two molecules taken alone,
three molecules, four, *etc*. and through a well established
theoretical formalism permits them to be combined to yield properties
of the bulk phase of 10^{23} molecules! A limiting element of this
formalism has lied in the inability to evaluate the basic integrals
arising in the development. Using ideas from our free-energy work,
we have made large advances toward the resolution of this problem.
Our larger aim in this work is to permit simulation to yield useful
results while focusing on the behaviors of just a few molecules
at once. This could be viewed as a powerful way to parallelize the
calculations involved in evaluating bulk properties from molecular
models.

The above describe our activities to improve the methodology of simulation. In addition we have activities applying molecular simulation to understand complex phenomena.

Prediction of stable crystalline polymorphs should be completed by examining the relative free energies of candidate structures. In practice this is almost always done by examining the lattice energy alone, ignoring entropic contributions to the free energy. The error incurred with this procedure is generally considered to be of the order of the difference between candidate structures, but nevertheless the practice persists because it is inconvenient to consider the entropy rigorously, and approximate methods that introduce entropy tend not to lead to greater success in predicting the observed polymorphs. We are performing rigorous calculations of the free energies of crystalline polymorphs of a variety of molecules. We use these results to ascertain the true importance of entropy in polymorph stability, determine if widely used approximations are justified, and examine if new methods can be applied instead.

This is less a research than a development project driven by an interest in applying molecular simulation as a teaching tool. We are investigating the feasibility of using molecular simulation teaching tools as a basis for constructing extensible, object-oriented research-quality molecular simulation codes. Etomica is the name of the API and development environment that we are constructing. We now have a page devoted to describing and disseminating it: http://www.etomica.org/ In our latest work we are attempting to extend the design developed in Etomica to formulate a general-purpose API for molecular simulation, which can facilitate interfacing with a variety of simulation code bases.

One particularly useful application of the Etomica library has been in the development of user-friendly, interactive molecular simulations that are appropriate for instructional purposes. The suite of modules developed for this purpose can be found at http://modules.etomica.org/. These were developed as part of a community-based project funded by NSF, and the work has been recognized by the Himmelblau Award, given in 2012.

Last Updated: June 2012