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). 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. The multiscale simulations include ab initio calculations, Monte Carlo and molecular dynamic simulations as well as continuum theoretical methods on higher length scales.

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Fig. 4: a) Scheme of a thermoelectric device. b) Snapshot from ab-initio based Monte Carlo simulations of CoTi_xSc_1−xSb, a thermoelectric half-Heusler material. c) Phase diagram of CoTi_xSc_1−xSb obtained from Monte Carlo simulations and mean field calculations. 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 CoTI _1-xY_xSb  (Y = Sc, V, Mn, Fe)”, J. Electron. Mater. 45, 1382 (2016). https://doi.org/10.1007/s11664-015-4041-9

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.

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Fig. 3: 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. 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. http://dx.doi.org/10.1039/C6SM01454B

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.

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Fig. 2: 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. 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). https://doi.org/10.1088/1361-648X/aa4de0.

Hydrogels and other polymer networks are central elements for the creation biomaterials due to their elastic properties, permeability, and large inner surface. If polymer networks are deformed mechanically, physical crosslinks can break and form again at other parts of the networks. The resulting rheological properties make physically crosslinked hydrogels excellently suited as a soft matrix for 3D-printing of biomaterials. With the help of molecular dynamic simulations we study dynamic properties of such 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. Changes of temperature or chemical environment can switch the nanostructure of the system. We have developed a new method that allows us to simulate reversibly crosslinked polymer networks with the self-consistent mean field theory (SCFT).

Fig. 1: 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 x_B 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) https://doi.org/10.1557/jmr.2013.315. Fig. c) reproduced with permission from Chemosensors, MDPI: T. Gruhn and H. Emmerich, „Simulation of Stimuli-Responsive Polymer Networks“, Chemosensors 1, 43-67 (2013) https://doi.org/10.3390/chemosensors1030043.