Theoretical models have the tendency to quickly become too complex to be treated in an exact fashion, or simply require too many operations for manually solving the equation(s) in a reasonable timescale. In such cases the models are evaluated numerically when studying the behavior of specific systems. The complexity and the many different approximations used in modern computational solid state physics programs (but also in many other branches of computational science) makes their usage often more akin to experimental work (with the physical risk to their users limited to paper cuts). However, there are important differences; in contrast to actual experiments, computational “experiments” allow the researchers to set the initial conditions exactly, and give a lot of additional control. On the other hand, the computational work in general can only take into account a limited set of effects, resulting in a simpler version of a real environment. This simplicity often has the advantage of making it easier to indicate which causes result in which effects.
As such, all models are wrong, in the sense of representing nature in absolute detail and truth, however, they do show us underlying laws and behaviour.
My main research interests are build around modeling experimental systems by comparison to results obtained from computational work. This, preferably, through direct comparison using robust approaches (e.g. Scanning Tunneling Microscopy), as I did during my PhD project: “Ab initio study of Pt induced nanowires“.
Also the use of frameworks extending the ab initio DFT zero pressure and zero temperature regime I find very interesting. Although, one always needs to be careful, and bear in mind the limitations and approximations used, these techniques are very well suited for comparison of closely related systems. Such an approach is also more directed at predictive results, aimed at specific properties of a material rather than its specific geometry. This made them well suited for my research on the effects of metal doping of CeO2 buffer layers.
In contrast to the above, systems at the limit of what is possible with a given method, are ideal to learn and understand the limitations of current state of the art methods. They also provide insights into how such methods can and should be improved. Metal-Organic Frameworks (MOFs) are such systems. Furthermore these materials live at the conceptual interface between fields: chemistry due to their molecular components and large pores, and physics due to their periodic crystalline nature, inorganic clusters, and low dimensional substructure providing access to exotic physics.
- Mechanical and Electronic Properties of flexible Metal-Organic Frameworks (current focus)
- The Hirshfeld-I method for solids and large molecular systems.
- Metal doping of CeO2 buffer layers.
- The formation and structure of lanthanum cerates.
- Pt induced Ge Nanowires.