Research: Interfaces and Quantum Simulation Methods
Interfaces: My research group studies liquid and solid interfacial regions with large scale computer simulation methods. The general focus of the research is to understand complex interfacial phenomena via computer simulation. We have carried out the first molecular dynamics simulations of the Reversed Phase Liquid Chromatographic interface. The simulations involve thousands of particles and include tethered alkane chains, water/cosolvent (methanol or acetonitrile), the silica surface, and solute motions. We have examined the structure and dynamics near the surface and have computed a free energy profile for solute transfer from the mobile phase into the stationary phase. The simulations lend clear molecular level insights into the microscopic origins and driving forces for solute retention in liquid chromatography. The simulations can be compared directly to experimental data to test the validity of the model and can also provide guidelines for the applicability of previous theoretical models of solute retention in chromatography. Our research benefits from active collaborations with experimental chromatographers.
A second system of interest concerns molecular orientations of organic species near metal surfaces. We have carried out Monte Carlo simulations of rigid rod monolayers near solid surfaces to explore the origins of collective tilt behavior in the chains. We have also performed more realistic molecular dynamics simulations of oligoimide chains self assembled on gold surfaces. These systems are of interest for a range of microelectronic and adhesion applications. We obtained good agreement with Raman scattering experiments for the observed tilt and orientation behavior. Our long term goal is to carry out more realistic quantum calculations to probe the local energetics of the chemical bonds of the thiols to the metal surface, and their influence on the chain structure and dynamics.
Quantum Simulation Methods: We are developing a general method for simulation of quantum systems including many electrons. The underlying theoretical framework is Density Functional Theory. We express the Kohn-Sham equations in real space and solve the equations iteratively via a multigrid method. The Poisson equation is also solved with the multigrid method. These computational methods allow one to simulate finite or periodic systems in a way that scales linearly in computer time with the number of electrons. In addition, accurate solutions can be obtained with only a few to several iterations on the fine scale, so the method is fast. An advantage of multigrid as a computational approach is that one can focus a more detailed description of the problem in a region of interest via adaptive grids. We have performed a series of calculations that show that accurate physical results can be obtained for atoms and molecules with these methods and are now developing the algorithm for larger scale simulations. Special areas of interest for future studies include motions of the proton in water and the chemical bonding near metal surfaces discussed above. A very long term goal is to couple the all electron calculations with path integral methods for the nuclear motions when quantum effects are important.
Our calculations are carried out on several local workstations in my group and on the vector Cray-YMP and parallel Cray-T3D at the Ohio Supercomputer Center in Columbus.
Large Scale Electrostatics: As part of the multigrid quantum chemical methods discussed above, we have developed large scale solvers for electrostatics problems. We have extended the multigrid Poisson solver to a linear scaling solver for the fully nonlinear Poisson-Boltzmann equation. We are applying these computational methods to study free energies of solute transfer in size exclusion chromatography. We have also implemented the PB solver in a new Monte Carlo method for simulating the properties of polyelectrolyte chains on a lattice. This allows us to test the underlying Debye-Huckel level theory which has been used extensively in previous studies of charged chains. The method combines the configurational bias Monte Carlo technique with the linear scaling PB solver. We plan to study many-chain systems with this new method.
Modeling of Biological Ion Channels: Membrane protein channels control the flow of ions into and out of the cell. We are developing new methods to study ion transport through biological channels. This involves several levels of theory, from molecular dynamics to Brownian dynamics to continuum descriptions. In particular, we are studying the acid secretion mechanism in the human stomach. The mechanism includes a proton pump, a potassium channel, and a chloride channel. We are investigating the driving forces for ion permeation in the chloride channel. New multiscale methods are being developed to efficiently model ion transport at the continuum level. Also, we are developing a new algorithm to search for ion transport pathways once a structure is known. Using the bacterial structure as a template, we have constructed a homology model of the human ClC-2 channel and have located a pH sensor domain in a 31 residue extracellular loop. We are studying how this domain may be involved in channel gating. Our project involves a close collaboration with researchers in the medical school who study the physiology of ion channels and perform NMR structure determination.
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