Over the last decades, computational sciences have extended the range of phe-nomena that can be investigated within the frameworks of chemistry and biology. Complex systems such as proteins or nanocomposites, are hampered by common problems and can be studied with similar techniques. My research interests and experience span a wide range of topics from protein simulations to surface catalysis and computational spectroscopy. such work advances understanding in each of them.

More specifically there are four focus areas of my work: (1) structure and dynamics of biopolymers, (2) explicit/implicit solvent effects, dynamics of water molecules, (3) first principles calculations, chemical accuracy and (4) high performance computing and visualization. I have been fortunate to be part of several interdisciplinary projects and gained valuable research experience working with colleagues from materials science, physics, chemistry, statistics, and biology.

ACCURACY & FIRST-PRINCIPLES SIMULATIONS

For the last few years focus of my work brings together a hierarchy of state-of-the-art computational methods to address both applications and requisite theoretical methodology development in relation to the properties of nanoparticles and bio-nano interfaces, thus facilitating the pipeline from fundamental understanding to perspective practical solutions. In particular, we have carried out theoretical simulations of tensile tests on Si<001> nanowires adapting constrained Car–Parrinello molecular dynamics.

I have a long-standing research interest in trying to push ab initio methods to their limit of accuracy. This involves such issues as: basis set convergence and extrapolation to the complete basis set limit, accounting for higher-order correlation effects, and the rotational-vibrational anharmonicity. For small and medium polyatomic molecules we are presently able, to predict binding free energies and enthalpies to an accuracy of 1 kcal/mol or better, very accurate geometries and vibrational modes.

Our research efforts have manifested into two “black box” composite com-putational thermochemistry protocols. First provides the procedure for calculations of interaction Gibbs free energies for intermolecular complexes of biological interests. The second one offers very robust vey to predict redox potential for organic aromatic compounds. Aside from applications of extremely demanding correlated methods composite protocols usually include less CPU-intensive methods (like DFT) that provide reasonable trade-off between desired accuracy and time to solution.

The correct description of solvation free energies and detailed solution structures of (bio-)molecules is crucial to our understanding of molecular processes in chemical and biological systems. Efficient theoretical approaches to such descriptions are typically given by implicit (or continuum) or explicit solvent models of the aqueous environment.

Of particular interest to me are hydration properties of DNA and nucleobases. Comprehensive study on interactions between nucleic acid bases and bulk water environment has been performed with use of classical and first principles Car–Parrinello molecular dynamics. Detailed analysis of average number, lifetimes and mobility of water molecules, orientation and 3D organization of hydrogen bond network in the first hydration shell of adenine, guanine, cytosine and thymine has been carried out.

Because MD simulations explicitly include of temperature, such simulations are uniquely suited to study the effects of temperature on chemical properties. I have been using first principles MD simulations to examine the temperature and dynamic effects of environment on DNA bases tautomerization. Obtained rate constants challenge the accepted results obtained using static methods and implicit solvation models. Although successful in many cases, the general applicability of many empirical implicit models with many system-dependent, adjustable parameters is often questionable, when compared to more accurate but computationally expensive explicit molecular dynamics (MD) simulations.

The trend toward massively parallel computer systems is leading to an increased demand for scalable software. However, HPC systems are also becoming more complex making the development and use of scalable software increasingly difficult. As a result, very few applications run effectively at extreme scales. Furthermore, many application problems are manifested only at large scales. With the availability of hundred thousand processor systems and the advent of million processor systems, the lack of scalable software systems is increasingly problematic. This problem is particularly concerning for capability computing where the most powerful computational resources are used to solve large, demanding problems.

My collaborative efforts with the leading national supercomputing centers address performance and scalability issues in large distributed systems, scalable communication, runtime data analysis. Working together with the Maui High Performance Computing Center (MHPCC) and the Engineer Research and De-velopment Center (ERDC, both DoD DSRC centers) few scientific application were ported and especially optimized for several TOP500 system, including 100Tflop Dell PowerEdge M610 cluster, and 75Tflop Cray XT4.

As a part of collaboration with the Army High Performance Computing Research Center (AHPCRC) my efforts were devoted to benchmarking and per-formance/functionality enhancements computational chemistry codes (e.g. CPMD) on the new Cray X1E supercomputer and Opteron cluster systems.

As part of collaboration with the Mississippi Center for Supercomputing Research (MCSR) I have been involved into testing, benchmarking and tuning many scientific applications for the SGI Altix global shared-memory system.