Susan Rempe Ph.D.

Rempe, Susan
Position Department / Business Unit
Senior Researcher Computational Bioscience Department
Institution Disciplines
National Center for Design of Biomimetic Nanoconductors Nanobiology Nanomaterials
City State / Provence
Urbana Illinois
Country Website
United States link

Susan Rempe is a Senior member of the technical staff in the Computational Bioscience Department at Sandia National Laboratories. Her research includes work on computational chemical physics, dynamical descriptions of proton motion, and polarizable force fields.


Transport across membranes and nanopores can be characterized by static equilibrium properties as well as by nonequilibrium dynamic properties. For example, equilibrium selectivity properties of a nanopore can be characterized by the difference in interaction free energy for transferring one ion from bulk liquid water into a pore compared to another ion.  Furthermore, transport rates can be characterized by the free energy barriers encountered when an ion traverses a pore, a property also calculated by equilibrium methods.  In alignment with the focus of the Center, much of our current and recent activity has been aimed at determining static equilibrium properties of ions in complex environments, such as liquid water and inside aqueous nanopores. Characterization of proton hydration and free energy profiles for dynamic protonation reactions has been an important component of this work  Our aim has been to predict thermodynamic driving forces for selective ion permeation and exclusion, and to relate those properties to structural characteristics of nanopores. 

Guided by a new statistical mechanical theory (Pratt et al., 1999), which emphasizes the importance of the local environment in calculating interaction free energies, we have predicted structural and thermodynamic properties of ions (Rempe et al., 2000; Rempe et al., 2001; Rempe et al., 2004; Asthagiri et al., 2004; Leung et al., 2004) and small hydrophobic particles (Ashbaugh et al., 2003) in water, the reference solution for ion conduction through nanopores.  We also characterized the structural and thermodynamic properties of an ionizable amino acid molecule (and its mobile proton) during the course of an intramolecular proton transfer reaction (Leung et al., 2005).  To achieve an accurate description of the local environment, we applied ab initio methods to molecular model systems, consisting of both microscopic fragments of the aqueous system and molecular clusters coupled to coarse electrostatic descriptions of the distant liquid environment.  In one study using a microscopic fragment of liquid, we examined the consequences of reducing the full ab initio molecular model of water to a cheaper rigid water approximation (Leung et al., 2005).  The validity of the models was established by comparing coupled models to pure ab initio studies, and by comparing structural and thermodynamic predictions to experimental data.  As a consequence of this work, carried out by us as well as others (Asthagiri et al., 2004; Asthagiri et al., 2005), new structures and chemical mechanisms have been revealed, and a solid foundation has been laid for future modeling studies based on coarser treatment of molecular details.

New efforts are being pursued to model ion behavior in more complex environments than pure liquid water.  Since nanoporous silica membranes show promise as ion conductors, we have initiated studies that aim to relate ion permeation and exclusion characteristics to silica pore structure and chemical composition (Leung et al., 2005).  Part of this undertaking includes studies that characterize interactions between the silica surface and water (Tsige et al., 2003).  In related work, we are characterizing mechanisms that lead to conformational changes large enough to cause “gating” (opening/closing) events in nanoporous conductors.  The current model system under study consists of transition metal ions trapped by porphine molecules on a solid surface (Leung et al., 2005).

The Rempe lab’s current and recent activities support the Center goals directly.  They provide much of the preliminary work needed to develop a multi-scale approach for studying the properties of ion conductors.  By using ab initio approaches as a foundation, we can apply our expertise in modeling techniques that span multiple time and length scales, coupled with our expertise in statistical methods for computing thermodynamic driving forces, to achieve accurate predictions of structure-function relationships in biological and synthetic ion transporters.


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