Research group "Simulation of mesostructured materials"

Group leader:


Thomas Gruhn, PhD. 0921-55 7873
  thomas.gruhn(.at.)bm.uni-bayreuth.de
   

Research overview

Understanding the formation process and the properties of mesoscopic structures in materials is a fascinating field of research, which is of great importance for the development of new materials. Especially, the self-assembly of structures on the nanoscale and its dependence on external conditions are of high relevance for the production and adaptation of nanomaterials. The group uses computer simulations and numerical methods for studying microdomains, nanostructures and other ordering phenomena in soft matter and solid state systems. Investigated systems include polymer and filament networks, colloid-polymer suspensions and colloidal quasicrystals, but also solid state materials for alternative energy materials like thermoelectrics and thin film solar cells.

Reversibly crosslinked polymer networks

Intelligent polymer networks are polymers interconnected by crosslinks that can break and re-establish. The process may occur spontaneously or triggered by external stimuli. Depending on the type of crosslinks, a drastic transformation of structure and morphology can be induced by changing temperature, irradiance or chemical environment. The effect may be used, for example, for controlled drug application. We have developed a new method that allows us to simulate reversibly crosslinked polymer networks with the self-consistent mean field theory (SCFT). We have used this method to study phase transitions of nanostructures in copolymer networks

 

Reversibly crosslinked copolymer network simulated with SCFT (a) Crosslinks between AB copolymers (A red, B blue) can form and break, the strength of the link depends on the involved monomer types (AA, AB or BB). (b) Sketch of a lamellar and a hexagonal mesophase in a reversible AB copolymer network. (c) Local B monomer concentrations xB obtained from SCFT.

Fig. b) reproduced with permission from J. Mater. Res., Cambridge University Press: T. Gruhn and H. Emmerich, “Phase behavior of polymer blends with reversible crosslinks—A self-consistent field theory study”, J. Mater. Res. 28, 3079-3085 (2013). Fig. c) reproduced with permission from Chemosensors, MDPI: T. Gruhn and H. Emmerich, "Simulation of Stimuli-Responsive Polymer Networks", Chemosensors 1, 43-67 (2013).

 
Colloid-polymer suspensions

Mixtures of polymers and rod-like or platelet-like colloids may be used to create materials with anisotropic material properties (for example, directional mechanical strength). In our simulations we investigate the time development of concentration and orientation fields of the colloids. With our novel method, we have investigated anisotropic spinodal decomposition and developed a method that allows to extract more material properties from structure factors measured in scattering experiments.

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a) Spinodal decomposition of anisotropic colloids in a polymer matrix. The picture shows the spatial distribution of the colloid concentration c(x,y). The inset shows a schematic of the partially aligned colloids). The direction of the domain boundaries is coupled to the orientation of the colloids. b) Anisotropic structure factor obtained from the simulation. The inset shows the analytic result for small oscillations.

Fig. b) reproduced with permission from J. Phys.: Condens. Matter, IOPscience : T. Gruhn, E. Pogorelov, F. Seiferling, and H. Emmerich, “Analyzing spinodal decomposition of an anisotropic fluid mixture”, J. Phys. Condens. Matter 29, 055103 (2017).

 
Colloidal quasicrystals

Suspensions of spherical core-shell colloids, in which the soft shell is built of polymer brushes, can form various phases including colloidal quasicrystals. Colloidal quasicrystals are of interest because they may be used for plasmonic or photonic applications. Using a model potential, which represents the effective interaction of the colloids, we perform molecular dynamic (MD) simulations of quasicrystalline systems. Studying phase diagrams we have already found four previously unknown quasicrystalline phases. A focus of the current work is on advanced 3D structures and dynamics.

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a) Spherical colloids with impenetrable cores and soft shells. b) Tiling of a quasicrystal with 12-fold symmetry. Black dots are colloid centers of mass, red lines connect proximate colloids. c) Static structure factor of this quasicrystal.

Figs. b) and c) from H.G. Schoberth, H. Emmerich, M. Holzinger, M. Dulle, S. Förster, and T. Gruhn, "Molecular dynamics study of colloidal quasicrystals", Soft Matter 12, 7644 (2016) -Reproduced by permission of The Royal Society of Chemistry.

 
Structure formation in half-Heusler thermoelectric materials

Thermoelectric materials can transform heat differences into electrical currents and can be used to supply electrical devices with waste heat (for example, from the exhaust of cars). It was found that nano- and microstructures within a thermoelectric material can help to decrease the thermal conductivity and to increase the efficiency of the thermoelectric device. Using multiscale simulations, we investigate the spontaneous formation of nano- and microstructures within thermoelectric half-Heusler compounds. Simulations start with ab initio density functional theory calculations, which provide parameters of the effective atomic interactions. With these parameters, Monte Carlo simulations and numeric calculations are performed on the nanoscale and a phase diagram of the system is calculated. On a higher length scale, the dynamics of microdomains can be investigated. Furthermore, we study the dependence of the thermal conductivity on the domain structures.

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a) Scheme of a thermoelectric device. b) Snapshot from ab-initio based Monte Carlo simulations of CoTixSc1−xSb, a thermoelectric half-Heusler material. c) Phase diagram of CoTixSc1−xSb obtained from Monte Carlo simulations and mean field calculations.

Fig. c) adapted with permission from J. Electron. Mater., Springer: J. Miranda Mena et al., “Miscibility Gap in the Phase Diagrams of Thermoelectric Half-Heusler Materials CoTi1-x YxSb (Y = Sc, V, Mn, Fe)”, J. Electron. Mater. 45, 1382 (2016).

 
Selected publications:

Miranda Mena J. and Gruhn T. (2017). Demixing and ordering in Ni(Ti,Zr)(Sb,Sn) half-Heusler materials. Phys. Chem. Chem. Phys., 19, 30695 .

Gruhn T., Pogorelov E., Seiferling F. and Emmerich H. (2017). Analyzing spinodal decomposition of an anisotropic fluid mixture. J. Phys.: Condens. Matter, 29, 055103.

Miranda Mena J., Schoberth H.G., Gruhn T. and Emmerich H (2016). Ab initio-based Monte Carlo and mean field studies of phase separated NiSn(Ti1−xHfx, Ti1−xZrx, Hf1−xZrx) compounds with C1b structure. Acta Materialia, 111, 157.

Schoberth H.G., Emmerich H., Holzinger M., Dulle M., Förster S. and Gruhn T. (2016). Molecular dynamics study of colloidal quasicrystals. Soft Matter 12, 7644.

Gruhn T. and Emmerich H. (2013). Phase behavior of polymer blends with reversible crosslinks—A self-consistent field theory study. J. Mater. Res., 28, 3079.

Emmerich H., Löwen H., Wittkowski R., Gruhn T., Toth G.I., Tegze G. and Granasy L. (2012). Phase-field-crystal models for condensed matter dynamics on atomic length and diffusive time scales: an overview. Adv. Phys., 61, 665.

Li D., Gruhn T. and Emmerich H. (2012). Mean field theory for a reversibly crosslinked polymer network. J. Chem. Phys., 137, 024906.

Chelakkot R. and Gruhn T. (2012). Length dependence of crosslinker induced network formation of rods: a Monte Carlo study. Soft Matter 8, 11746.

Ludwig C.D.R., Felser C., Windeln J. and Gruhn T. (2011). Defect structures in CuInSe2: A combination of Monte Carlo simulations and density functional theory. Phys. Rev. B, 83, 174112, (2011).

Gruhn T. (2010). Comparative ab initio study of half-Heusler compounds for optoelectronic applications. Phys. Rev. B, 82, 125210.

Chelakkot R., Lipowsky R. and Gruhn T. (2009). Self-assembling network and bundle structures in systems of rods and crosslinkers - A Monte Carlo study. Soft Matter, 5, 1504.

Ludwig C.D.R., Gruhn T., Felser C., Schilling T., Windeln J. and Kratzer P. (2010). Indium-Gallium Segregation in CuInxGa1-xSe2: An Ab Initio-Based Monte Carlo Study. Phys. Rev. Lett. 105, 025702.

Gruhn T., Franke T., Dimova R. and Lipowsky R. (2007). Novel Method for Measuring the Adhesion Energy of Vesicles. Langmuir, 23, 5423.

Gruhn T. and Schoen M. (1998). Substrate-induced order in confined nematic liquid-crystal films. J. Chem. Phys., 108, 9124.

Gruhn T. and Hess S. (1996). Monte Carlo simulation of the director field of a nematic liquid crystal with three elastic coefficients. Z. Naturforsch., 51a, 1 (1996).