Oxidative Fluorination of Cu/ZnO Methanol Catalysts

The influence of a mild difluorine treatment on Cu/ZnO precatalysts for methanol synthesis was investigated. It led to the incorporation of 1.2…1.3±0.1 wt % fluoride into the material. Fluorination considerably increased the amount of ZnO_x related defect sites on the catalysts and significantly increased the space‐time yields. Although the apparent activation energy E_A,app for methanol formation from CO₂ and H₂ was almost unchanged, the E_A,app for the reverse water‐gas shift (rWGS) reaction increased considerably. Overall, fluorination led to a significant gain in methanol selectivity and productivity. Apparently, also the quantity of active sites increased.     

Strongly consistent multivariate conditional risk measures

We consider families of strongly consistent multivariate conditional risk measures. We show that under strong consistency these families admit a decomposition into a conditional aggregation function and a univariate conditional risk measure as introduced Hoffmann et al. (Stoch Process Appl 126(7):2014–2037, 2016). Further, in analogy to the univariate case in Föllmer (Stat Risk Model 31(1):79–103, 2014), we prove that under law-invariance strong consistency implies that multivariate conditional risk measures are necessarily multivariate conditional certainty equivalents.     

Supporting mathematical literacy: examples from a cross-curricular project

Mathematical literacy implies the capacity to apply mathematical knowledge to various and context-related problems in a functional, flexible and practical way. Improving mathematical literacy requires a learning environment that stimulates students cognitively as well as allowing them to collect practical experiences through connections with the real world. In order to achieve this, students should be confronted with many different facets of reality. They should be given the opportunity to participate in carrying out experiments, to be exposed to verbal argumentative discussions and to be involved in model-building activities. This leads to the idea of integrating science into maths education. Two sequences of lessons were developed and tried out at the University of Education Schwäbisch Gmünd integrating scientific topics and methods into maths lessons at German secondary schools. The results show that the scientific activities and their connection with reality led to well-based discussions. The connection between the phenomenon and the model remained remarkably close during the entire series of lessons. At present the sequences of lessons are integrated in the European ScienceMath project, a joint project between universities and schools in Denmark, Finland, Slovenia and Germany (see www.sciencemath.ph-gmuend.de).     

Molecules of fermionic atoms in an optical lattice

We create molecules from fermionic atoms in a three-dimensional optical lattice using a Feshbach resonance. In the limit of low tunneling, the individual wells can be regarded as independent three-dimensional harmonic oscillators. The measured binding energies for varying scattering length agree excellently with the theoretical prediction for two interacting atoms in a harmonic oscillator. We demonstrate that the formation of molecules can be used to measure the occupancy of the lattice and perform thermometry.     

Interface controlled electronic charge inhomogeneities in correlated heterostructures

For heterostructures of ultrathin, strongly correlated copper-oxide films and dielectric perovskite layers, we predict inhomogeneous electronic interface states. Our study is based on an extended Hubbard model for the cuprate film. The interface is implemented by a coupling to the electron and phonon degrees of freedom of the dielectric oxide layer. We find that electronic ordering in the film is associated with a strongly inhomogeneous polaron effect. We propose to consider the interfacial tuning as a powerful mechanism to control the charge ordering in correlated electronic systems.     

Explicit Representation of Strong Solutions of SDEs Driven by Infinite-Dimensional Lévy Processes

We develop a white noise framework for Lévy processes on Hilbert spaces. As the main result of this paper, we then employ these white noise techniques to explicitly represent strong solutions of stochastic differential equations driven by a Hilbert-space-valued Lévy process.     

Discounted Bayesian search problems with unknown detection probabilities

In this paper we consider three discrete-time discounted Bayesian search problems with an unknown number of objects and uncertainty about the distribution of the objects among the boxes. Moreover, we admit uncertainty about the detection probabilities. The goal is to determine a policy which finds (dependent on the search problem) at least one object or all objects with minimal expected total cost. We give sufficient conditions for the optimality of the greedy policy which has been introduced in Liebig/Rieder (1996). For some examples in which the greedy policy is not optimal we derive a bound for the error.