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  • David M. Rogers, Dian Jiao, Lawrence Pratt, and Susan B. Rempe. "Local Structural Methods for Molecular Solvation?" Annu. Rep. Comp. Chem. 8, 2012.
  • David M. Rogers and Susan B. Rempe. "Irreversible Thermodynamics." J. Phys., Conf. Series, 2012.

We show how the interpretation of thermodynamic states as representing system information leads naturally to thermodynamic cycles and the first and second laws of thermodynamics as well as similar formulations for nontrivial nonequilibrium problems. The logical development of the theory also leads naturally to correct indistinguishability factors in the partition function.

  • Sameer Varma, David M. Rogers, Lawrence R. Pratt, and Susan B. Rempe. "Perspectives on Ion Selectivity: Design Principles for K+ Selectivity in Membrane Transport." Gen. Physiol., 137(6):479-488, 2011.

We review the development of models for understanding the physical basis of selectivity for K+ ions over Na+, its sibling only one row behind, in membrane channels and transporters. Although the problem is subtle because of the morass of competing effects, we emphasize work analyzing the systematic influence of the environment on tipping local binding site structure toward selective configurations.

  • David M. Rogers and Susan B. Rempe. “Probing the Thermodynamics of Competitive Ion Binding Using Minimum Energy Structures.” J. Phys. Chem. B, in press 2011.

We presented an extension of the Quasi-Chemical theory for quantifying the impact of local structure on ion complexation thermodynamics. The theory can be simply represented using a set of thermodynamic cycles involving binding site structural and compositional states as reaction intermediates.

  • Susan B. Rempe and David M. Rogers; et. al. “Computational and experimental platform for understanding and optimizing water flux and salt rejection in nanoporous membranes.” Technical Report, SAND2010-6735, 2010.

We summarize work on designing polymer coatings for salt exclusion in water transporting nanopores. In this work, I collected available molecular dynamics results for these systems and performed a novel energy efficiency analysis able to relate atomistic and experimental scales as well as identify important design goals and chemical principles for material performance.

We investigated the central quantity of free energies in a Bayesian context and provide estimators for solvation free energies as well as optimal potential of mean force approximations to model polymer coarse-grained dynamics from atomistic simulations.

Dr. Zhao's ab-initio analysis of the charge distribution in water-ion clusters highlighted the importance of many-body water-water interactions and charge transfer effects in determining cluster structural and energetic properties. These are still challenging to represent in modern polarizable forcefields and have implications for anion properties at interfaces.

The role of polarizability in forcefield-based models of ions and water was examined. Utilizing some of our recent developments on quasi-chemical theory, we have been able to quantify the tightened, asymmetric nature of the ion's local solvation waters induced by increased polarizability as well as the exact effects of polarization on the solvation free energy. The results suggest some potential problems and diagnostics for such models.

  • David M. Rogers and Thomas L. Beck. Solve (Sourceforge, Chicago IL, 2008).

This force matching software implements and tests coarse-graining for general molecular systems in a mere 4000 lines of code. It is able to parametrize coarse Hamiltonians from atomic trajectory data given arbitrary definitions of coarse united-atom type models as well as carry out short Langevin Dynamics simulations on the coarse scale. The program's main drawbacks are its slow speed and high memory usage due to its simplistic design, attributable to the interpreted nature of python.

  • David M. Rogers and Thomas L. Beck. "Resolution and Scale Independent Nonparametric Function Matching Using a String Energy Penalized Spline Prior." 2008. [1] (stat.ML).

Fresh insight is provided into long-standing mathematical issues surrounding computational modeling of continuous functions from a few sampled data points. The present research lays the groundwork for predicting the behavior of complicated many-body systems using advanced regression techniques.