Prof. Dr. rer. nat. Karsten Reuter

Lehrveranstaltungen und Termine

Ausgeschriebene Angebote für Abschlussarbeiten

Development of a simulation protocol for ab initio molecular dynamics simulations of solid-water interfaces

Solid-water interfaces are of outstanding importance for electrochemistry and catalysis. With modern algorithms based on density functional theory the electronic structure of water and solids can be analyzed in great detail. A fundamental challenge is the description of the electrochemical double layer which effectively forms a capacitor subject to competing chemical and physical processes. Electrode water interfaces, for example, are often subject to faradaic and non-faradaic charge transfer processes which are difficult to separate in experiments. The goal of the MSc project is to develop a simulation protocol using ab initio molecular dynamics (MD) to model the behaviour of liquid water at transition metal interfaces, to identify structural and electronic properties at the interface and associated with the electric double layer. In the MSc project problems such as the construction of atomistic models of the liquid phase will be addressed along with a statistical description of the fluctuating behaviour of the fluid.  Electronic properties including work functions, electronic band structure, dipole effects, charge accumulation and capacitance effects due to interactions at the solid-liquid interface will be analyzed and compared to more  approximate models. Simulations will be carried out with ab initio MD simulation software such as CP2K and FHI-AIMS.

geeignet als

• Masterarbeit Physik der kondensierten Materie
• Masterarbeit Applied and Engineering Physics

Themensteller(in): Karsten Reuter

Machine learning for computational design of nanostructured catalysts

The computational design of new materials for heterogeneous catalysis relies on methods that can accurately predict adsorption energies of reactants and intermediates at low computational cost. Quantum-mechanical calculations based on the Density Functional Theory (DFT) are typically used for surface reactivity studies, but their cost significantly limits the number of compounds that can be evaluated as candidates for catalysing each targeted reaction. Scaling relations between adsorption energies of similar adsorbates and machine-learning approaches have been recently developed to circumvent this computational burden, but their application is currently limited to extended close-packed metal surfaces. Real catalysts are typically formed by supported metal nanoparticles exposing sites at different facets, edges, and corners. Dealing only with extended surfaces thus limits the predictive potential of computational catalyst design.

 

The goal of this M.Sc. project is to extend existing approaches for predicting adsorption energies to the description of undercoordinated sites typically found on metal nanoparticles. The candidate should be interested in electronic structure and machine learning methods, as well as in surface chemistry and catalysis. The student will learn how to perform DFT-based calculations and to use and asses the results of different machine learning methods. Basic knowledge of UNIX based operating systems and some experience with programming (and/or scripting) languages (preferably Python) is desirable, but not required.

 

Questions about the project can be directed to mie.andersen@ch.tum.de and albert.bruix@ch.tum.de. 

 

geeignet als

• Masterarbeit Physik der kondensierten Materie
• Masterarbeit Applied and Engineering Physics

Themensteller(in): Karsten Reuter

Origin of the open circuit voltage in ternary organic solar cells, a study based on a semi-empirical Monte Carlo simulation approach

Organic photovoltaic (OPV) technology has seen a rapid evolution over the last decade. The unique selling points of OPVs, such as excellent light harvesting capability, freedom of form, color and transparency, environmental friendliness, easy scalability and lower manufacturing costs based on roll-to-roll printing methods, position this technology for the mobile power market, and this most properly reflects the state of the art in commercialization. An important milestone towards OPV commercialization has been surpassed by reaching a power conversion efficiency (PCE) of up to 17%. The main limitation in OPVs is due to the intrinsic narrow absorption window (~100-200 nm) of polymers compared to inorganic semiconductors such as Si, which makes it challenging to fully cover the solar spectrum with a single junction device. To overcome the absorption limitation, ternary blend organic solar cells represent one of the dominant strategies that has been explored in the last decade. The outstanding advantage of ternary blends consists of maintaining the simplicity of the processing conditions used for single active layer devices. Interestingly, the open circuit voltage (Voc) is tunable depending on the loading concentration of the ternary compound in both ternary systems compromised of i) two donors and one accepter as well as ii) one donor – two accepters blends.

The origin of the composition-tunability of Voc and the optimal electronic correlations between the components remains as an open question in OPV field. Obviously, it is very challenging to develop a complete model for Voc in ternary systems mainly due to the fact that this model should take all the electronic interactions between the components into account and consider their role in the photogeneration. Moreover, the model should be compositional dependent and accounts for the different microstructures and transport mechanisms operating simultaneously in the system. To this end, a semi-empirical method is required to link the electrical characteristics of ternaries to their morphological properties and draw a comprehensive picture from the morphology models reported in literature as the origin of Voc changes in ternary systems.

This project will focus on solving the aforementioned key challenge by employing a semi-emprical method based on kinetic Monte Carlo (kMC). An existing lattice kinetic Monte Carlo model, previously applied to the modeling of binary polymer:fullerrene solar cells, will be extended to treat ternary blends. This will allow us to correlate nano-morphological features with measured optical properties and obtained Voc, a crucial capability for the design of optimized, high performance ternary solar cells. 

geeignet als

• Masterarbeit Physik der kondensierten Materie
• Masterarbeit Applied and Engineering Physics

Themensteller(in): Karsten Reuter

Tight-binding beyond the two-center LCAO approximation

Semiempirical electronic structure approaches like the density functional tight-binding (DFTB) method are popular due to their unrivaled computational efficiency. This often makes them the only option, e.g. for describing the electronic structure of nanoparticles, which may consist of tens of thousands of atoms. Their efficiency comes at the cost of limited accuracy and transferability, however. Currently, these shortcomings are compensated on a case-by-case basis by the introduction of empirical parameters. Unfortunately, even here the limitations of the underlying theory sometimes become evident.
The goal of this M.Sc. project is the development of a novel framework for a tight-binding-like theory that goes beyond the typical two-center approximation for the Hamiltonian. The candidate should be interested learning the fundamentals of electronic structure theory, implementing methods and performing numerical test of different approximations. The main focus of the work will be on programming. Experience with a scripting language (e.g. Python) is advantageous but not mandatory. Questions about the project can be directed to johannes.margraf@ch.tum.de.
     

geeignet als

• Masterarbeit Physik der kondensierten Materie
• Masterarbeit Applied and Engineering Physics

Themensteller(in): Karsten Reuter