Thomas Wüst, PhD

Contact Information:

The Center for Simulational Physics
Department of Physics and Astronomy
The University of Georgia
Athens, GA 30602-2451, USA

Email: email-address

Research Interests:

General	Physical modeling and study of complex systems Connection between physics, computational methods and the Human / Nature
Physics / Mathematics	Statistical condensed matter physics (e.g. crystals, polymers, magnets, soft matter) Phase transitions and critical phenomena Stochastic and growth processes (Markov chains) Pattern formation, fractals
Computational	Monte Carlo methods in scientific computing Other computational techniques (e.g. cellular automata, molecular dynamics, quantum chemistry methods) Scientific visualization Artificial intelligence (e.g. neural networks, machine learning) High performance computing
Interdisciplinary	Materials science Biophysics (e.g. protein folding) Nature and the environment

Coarse-grained lattice models play an important role for the understanding of the complexity of biological phenomena such as protein folding and Monte Carlo simulation methods are an indispensable tool for the study of such models. In particular, the hydrophobic-polar (HP) lattice protein model (Lau & Dill, Macromolecules 22, 1989) has gained much attention as a standard in assessing the efficiency of computational methods for protein structure prediction as well as for exploring the statistical physics of protein folding in general. Within a minimalistic framework, it features some of the biggest challenges for the computational study of proteins and many other complex systems: namely, the efficient sampling of a large conformational space characterized by a rough energy landscape with many local minima and high energy and/or conformational barriers.

This project includes:

Developing Monte Carlo simulation methods (Wang-Landau, Metropolis or multicanonical sampling) to explore HP-like polymer and protein models (ground state search, determination of the density of states) and to investigate their statistical physical properties (low temperature thermodynamics).

Applying a procedure (derived from the findings from the HP model) to analyze the thermodynamic properties of real proteins (in collaboration with biochemists/bioinformaticians).


HP 20mer in 2D (H: white beads; P: blue beads) Click on image for an animation	Ground state of a HP 103mer in 3D

Growth-Induced Polarity Formation in Molecular Crystals

Symmetry breaking at the surface during growth of molecular crystals can induce macroscopic physical properties (e.g. polarity) which may not be allowed by the symmetry group of the bulk. This phenomenon has been observed experimentally in single-component crystals, inclusion compounds and solid solutions of organic dipolar molecules. Theoretically, evolution of growth-induced polarity can be described by a stochastic growth process, in its simplest form by a layer-by-layer growth model, where subsequent ad-layers of dipolar molecules thermalize on a frozen substrate (see Hulliger et al., Chem. Mater. 14, 2002; Bebie et al., Phys. Rev. E 66, 2002).

This project includes:

Developing a model of growth-induced polarity formation in two-component crystals (solid solutions) H_1-XG_X of dipolar host (H) and non-polar/dipolar guest (G) molecules (X, molar fraction of G molecules in the solid). Studying the driving forces governing polarity formation by means of an analytical description (mean-field approximation) and Monte Carlo simulations.

Investigating the effect of reduced cooperativity on growth-induced polarity by different growth models (layer-by-layer growth, growth along edges, kink growth).

Monte Carlo simulation of polarity formation in solid solutions H_1-XG_X (blue/red squares: dipolar H molecules with dipole orientation down/up, resp.; yellow squares: non-polar G molecules) Click on images for an animation

Ad-layer (top view of crystal surface)	Cross-section (view along growth direction)	Solid lines: mean-field approximation; dots: Monte Carlo simulations

Formation:

2006 - 2008

Postdoctoral research position at the Center for Simulational Physics, University of Georgia, USA.
Advisor: Prof. David P. Landau

Subjects:

Development of Monte Carlo simulation methods (e.g. Wang-Landau sampling)
Statistical physics of polymer and protein models (phase transitions)
Protein folding and protein structure prediction

2005 - 2006

Postdoctoral research position at the Department of Chemistry and Biochemistry, University of Berne, Switzerland.
Advisor: Prof. Jürg Hulliger

Subjects:

Physical modeling of crystal properties (polarity)
Analytical/numerical study of growth processes (Markov chains, Monte Carlo simulations)
Study of packing problems (simulated annealing)

Educational Background:

2002 - 2005	PhD in Physics. Department of Chemistry and Biochemistry, University of Berne, Switzerland. Supervisor: Prof. Jürg Hulliger PhD thesis: Growth-induced polarity formation in molecular crystals: Analytical theory and Monte Carlo simulations.
2000 - 2002	PhD student at the Department of Chemistry, Swiss Federal Institute of Technology (ETH) Zurich, Switzerland. Subject: Computational (ab initio) quantum chemistry.
1993 - 1999	Master of Science in Physics. Swiss Federal Institute of Technology (ETH) Zurich, Switzerland. Master thesis: Simulation of a stellar convection zone. Institute for Astronomy, ETH Zurich.

Award:

Faculty prize 2005 for the PhD thesis from the Faculty of Science (Chemistry and Biochemistry), University of Berne, Switzerland.

Publications:

Submitted/in preparation:

C. Gervais, T. Wüst, D. P. Landau, and Y. Xu. Application of the Wang-Landau algorithm to the dimerization of Glycophorin A. Submitted to J. Chem. Phys.

Refereed journal articles:

T. Wüst and D. P. Landau. Versatile approach to access the low temperature thermodynamics of lattice polymers and proteins. Accepted for publication in Phys. Rev. Lett.

T. Wüst, D. P. Landau, C. Gervais, and Y. Xu. Monte Carlo simulations of systems with complex energy landscapes. Comput. Phys. Commun. 180, 475 (2009).

D. T. Seaton, T. Wüst, and D. P. Landau. A Wang-Landau study of the phase transitions in a flexible homopolymer. Comput. Phys. Commun. 180, 587 (2009).

A. Batagiannis, T. Wüst, and J. Hulliger. Universality behaviour for polarity formation in channel-type inclusion compounds. J. Math. Chem. published online (2008).

T. Wüst and D. P. Landau. The HP model of protein folding: A challenging testing ground for Wang-Landau sampling. Comput. Phys. Commun. 179, 124 (2008).

Y. W. Li, T. Wüst, D. P. Landau, and H. Q. Lin. Numerical integration using Wang-Landau sampling. Comput. Phys. Commun. 117, 524 (2007).

T. Wüst and J. Hulliger. Effect of reduced cooperativity on growth-induced polarity formation: A comparison between different growth models. Phil. Mag. 87, 1683 (2007).

T. Wüst and J. Hulliger. Growth-induced polarity formation in two-component crystals of organic molecules: A statistical analysis. J. Phys. Chem. Solids 67, 2517 (2006).

T. Wüst and J. Hulliger. Growth-induced polarity formation in solid solutions of organic molecules: Markov mean-field model and Monte Carlo simulations. J. Chem. Phys. 122, 084715 (2005).

T. Wüst, C. Gervais, and J. Hulliger. How symmetrical molecules can induce polarity: On the paradox of dilution. Cryst. Growth Des. 5, 93 (2005).

C. Gervais, T. Wüst, and J. Hulliger. Influence of solid solution formation on polarity: Molecular modeling investigation of the system 4-chloro-4'-nitrostilbene/4,4'-dinitrostilbene. J. Phys. Chem. B 109, 12582 (2005).

C. Gervais, T. Wüst, N. R. Behrnd, M. Wübbenhorst, and J. Hulliger. Prediction of growth-induced polarity in centrosymmetric molecular crystals using force field methods. Chem. Mater. 17, 85 (2005).

J. Hulliger, M. Losada, C. Gervais, T. Wüst, and F. Budde. Effects of an external electrical field on the polarization of growing organic crystals: A theoretical study. Chem. Phys. Lett. 377, 340 (2003).

H. I. Süss, T. Wüst, A. Sieber, R. Althaus, F. Budde, H. P. Lüthi, G. D. McManus, J. Rawson, and J. Hulliger. Alignment of radicals into chains by a Markov mechanism for polarity formation. CrystEngComm 4, 432 (2002).

Conference proceedings:

T. Wüst and J. Hulliger. Vector property generation by a stochastic growth process. In Lecture Series on Computer and Computational Sciences, Volume 4A (Brill Academic Publishers, 2005).

Last update: April 22, 2009