Research
The general field of research in the AG Netz is the dynamics and structure of biological and liquid matter with wide applications to medical, biological and nano sciences. We use a wide arsenal of theoretical methods, ranging from ab initio and classical force-field based molecular dynamics simulations over coarse-grained simulations to analytic calculus employing scaling arguments, field-theoretic and stochastic methods. We are particularly interested in problems that can only be tackled by a combination of simulations and analytic approaches. For such problems we develop various methods to connect simulations to continuous theory. For example, we define and extract viscosity profiles1 and dielectric profiles2 of confined water from simulations and thereby apply hydrodynamics and electrostatics to nano-scale interfacial problems. We use efficient simulation techniques for water at prescribed chemical potential and extract the hydration interaction between phospholipid membranes in perfect agreement with experiments, showing that this biologically ubiquitous force is due to water polarization3,4. We are also interested in reaction kinetics and protein folding. We use general methods for the extraction of inhomogeneous friction profiles from experimental drug concentration profiles in human skin and thereby derive micrometer-resolved human skin properties5. In a series of papers we explore the connection between stochastic motion and infrared spectroscopic features6,7. We have introduced general methods to extract memory kernels from time series data and use the generalized Langevin equation to model non-Markovian kinetics of infrared spectra7, of conformational transitions8 and of protein folding9. Using analytical methods, we explore the Hamilton-based investigation of non-equilibrium processes and apply it to experimental data from biological active systems and living cells10,11.
Example publications
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Hydration Friction in Nanoconfinement: From Bulk via Interfacial to Dry Friction, A. Schlaich, J. Kappler and R. R. Netz, Nano Letters 17, 5969- 5976 (2017).
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Water Dielectric Effects in Planar Confinement, A. Schlaich, E. W. Knapp and R. R. Netz, Physical Review Letters 117, 048001 (2016).
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Hydration repulsion between biomembranes results from an interplay of dehydration and depolarization, E. Schneck, F. Sedlmeier, R. R. Netz Proc. Natl. Acad. Sci. USA 109, 14405–14409 (2012).
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From hydration repulsion to dry adhesion between asymmetric hydrophilic and hydrophobic surfaces, M. Kanduc, R. R. Netz Proc. Natl. Acad. Sci. USA 112, 12338–12343 (2015).
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Data-based modeling of drug penetration relates human skin barrier function to the interplay of diffusivity and free-energy profiles, R. Schulz, K. Yamamoto, A. Klossek, R. Flesch, S. Hönzke, F. Rancan, A. Vogt, U. Blume-Peytavi, S. Hedtrich, M. Schäfer-Korting, E. Rühl, R. R. Netz Proc. Natl. Acad. Sci. USA 114, 3631–3636 (2017).
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Orientation of non-spherical protonated water clusters revealed by infrared absorption dichroism, J. O. Daldrop, M. Saita, M. Heyden, V. A. Lorenz-Fonfria, J. Heberle and R. R. Netz, Nature Communications 9, 311 (2018).
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Time-Dependent Friction Effects on Vibrational Infrared Frequencies and Line Shapes of Liquid Water, F. Brünig, O. Geburtig, A. von Canal, J. Kappler, R.R. Netz, J. Phys. Chem. B 126, 1579-1589 (2022).
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Butane dihedral angle dynamics in water is dominated by internal friction, J. O. Daldrop, J. Kappler, F. N. Brünig and R. R. Netz, Proc. Natl. Acad. Sci. USA 115, 5169-5174 (2018).
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Non-Markovian modeling of protein folding, C. Ayaz, L. Tepper, F. N. Brünig, J. Kappler, J. O. Daldrop and R. R. Netz, Proc. Natl. Acad. Sci. USA 118, e2023856118 (2021).
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Fluctuation-dissipation relation and stationary distribution of an exactly solvable many-particle model for active biomatter far from equilibrium, R. R. Netz, Journal of Chemical Physics 148, 185101 (2018).
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Non-Markovian data-driven modeling of single-cell motility, B. G. Mitterwallner , C. Schreiber, O. Daldrop, J. O. Rädler and R. R. Netz, Physical Review E 101, 032408 (2020).
Keywords
- AG Roland Netz, Bio Soft Matter Theory