Alexander Schlaich

About Me

I've just started setting up a research group on 'Multiscale Materials Modeling' (M3) at the Institute for Computational Physics (ICP), University of Stuttgart.
In general, my research is largely curiosity driven and concerns the interface between chemical physics, physical chemistry, statistical physics but also questions from biology and material science. I use computer simulations and statistical mechanics as principal tool, but I also stay in close touch with experiments.
I will iregularly post some insights I feel worth sharing in my blog.
Feel free to check my CV (last updated 2020/08/04) or to contact me!


MAICoS is public!

2019-10-31 08:00:00 +0100

We have just published MAICoS - Molecular Analysis for Interfacial and Confined Systems.

MAICos is a Python library to analyse molecular dynamics simulations of interfacial and confined systems based on MDAnalysis. For now the most important features cover the analysis of dielectric profiles in different geometries and various tools to invertigate the interfacial structure and velocity profiles. Check it out for here and provide us feedback using the bugtracker if you have any suggestions or problems!



    From water cavitation to hydration repulsion

    Liquids at interfaces show many properties different from their bulk due to the different forces that are experienced. The force balance between the different phases is typically described in terms of the wetting coefficient . The free energy difference between a confined liquid and in bulk then determines if the cavity is filled at given values of temperature and pressure, and, more importantly, if the surface interaction is attractive or repulsive. Using molecular simulations of water at controlled chemical potential between surfaces with tunable , we were able to obtain the interaction phase diagram [1].

    The precise knowledge and understanding of the water-mediated interactions is not only of crucial importance for industrial applications, but also in biology where the hydration repulsion ultimately stabilizes biological membranes at nanometer separations [2]. Although known since many years, its physical origin is still under debate. In my work I use simulations of atomistically represented water between membranes to obtain further insights into possible mechanisms for this overwhelming repulsion.

    1. M. Kanduč, A. Schlaich, E. Schneck, and R. R. Netz, “Water-Mediated Interactions between Hydrophilic and Hydrophobic Surfaces,” Langmuir, vol. 32, no. 35, pp. 8767–8782, Sep. 2016. [WEB][DOI]
    2. A. Schlaich, B. Kowalik, M. Kanduč, E. Schneck, and R. R. Netz, “Physical mechanisms of the interaction between lipid membranes in the aqueous environment,” Physica A, vol. 418, pp. 105–125, Jan. 2015. [WEB][DOI]
    Electrostatic and dielectric effects at interfaces and in confinement


    Many biologically and industrially relevant surfaces are charged in water, classical examples are lipid membranes, ionic surfactant layers and solid surfaces such as glass, silica or mica. The resulting interactions are profoundly influenced by water polarization, which in a macroscopic approach is quantified by means of the static dielectric tensor. Whereas the latter is constant and diagonal in bulk, close to an interface, the effect of the water structure is more intricate [1]. Using atomistic molecular dynamics simulations, we calculate the space-dependent dielectric response function of water in confinement and find that the effective dielectric permitivitty is strongly influenced for a confined planar water slab [2]. Finally, by performing simulations of charged surfaces at controlled water chemical potential both the ion distribution and the interaction pressure are accessible [3]. Importantly, already for moderate surface charge densities the additivity of the hydration pressure and mean-field electrostatic repulsion breaks down, due to a combination of different effects, namely, counterion correlations as well as the surface charge-induced reorientation of hydration water, which modifies the effective water dielectric constant as well as the hydration repulsion.

    1. P. Loche, C. Ayaz, A. Schlaich, D. J. Bonthuis, and R. R. Netz, “Breakdown of Linear Dielectric Theory for the Interaction between Hydrated Ions and Graphene,” J. Phys. Chem. Lett., vol. 9, no. 22, pp. 6463–6468, Nov. 2018. [WEB][DOI]
    2. A. Schlaich, E. W. Knapp, and R. R. Netz, “Water Dielectric Effects in Planar Confinement,” Phys. Rev. Lett., vol. 117, no. 4, p. 048001, Jul. 2016. [WEB][DOI]
    3. A. Schlaich, A. P. dos Santos, and R. R. Netz, “Simulations of Nanoseparated Charged Surfaces Reveal Charge-Induced Water Reorientation and Nonadditivity of Hydration and Mean-Field Electrostatic Repulsion,” Langmuir, vol. 35, no. 2, pp. 551–560, Jan. 2019. [WEB][DOI]
    Adsorption and transport in hierarchical porous materials

    Porous materials combining several porosity scales, such as hierarchical zeolites, are widely used in industry for adsorption, separation or catalysis to overcome slow diffusion in strongest confinement (< 2 nm) and enhance access to the materials large surface area. Available modeling approaches for adsorption and transport in such multiscale porous media are limited to empirical parameters which cannot be derived from molecular coefficients. In particular, existing approaches do not offer the ground for a bottom up model of adsorption/transport in multiscale materials as (1) they describe empirically the adsorption/transport interplay and (2) they do not account for the molecular details of hydrodynamics at the nm scale. We use atom-scale molecular simulations to obtain explicit relations between adsorption and the transport coefficients, which capture different regimes upon varying the temperature, pore size, pressure, etc. This research is conducted within the ANR project TAMTAM that aims at developing a bottom up model of adsorption/transport in multiscale porous materials using experiment, molecular simulation and theory. We employ a rigorous statistical mechanics upscaling strategy to connect parameters from molecular to engineering scales without losing information at the lower scale. Owing to the use of data that capture the many adsorption/transport regimes upon varying pressure, pore size, etc., this approach does not rely on hydrodynamics and, hence, does not require assuming a given adsorption/flow type.


    Alexander Schlaich
    Office 1.036
    Institute for Computational Physics
    Universität Stuttgart
    Allmandring 3
    70569 Stuttgart
    Phone +49 711 685-63607
    Fax +49 711 685-63658