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The mammalian senses of taste and smell utilize a series of cross-reactive receptors, rather than highly selective receptors. Our group mimics this principle with a series of synthetic and designed receptors for the analysis of complex analytes in real-life settings. The receptors derive from a combination of rational chemical design and modeling, with combinatorial synthesis techniques. Optical signaling often derives either from indicator-displacement assays, or direct modulation of the spectroscopy of the receptor. It will be shown that a union of designed receptors targeted to a class of analytes, with combinatorial methods, gives fingerprints that differentiate between the individual members of the analyte class. The strategy is to use a core-binding element that imparts a bias to each and every member of the library, ensuring affinity of the library members for the class of analytes being targeted. The design of this core derives from standard molecular recognition principles: preorganization, complementary, pair-wise interactions between receptor and analyte, and desolvation. Imparting a bias to the affinity of the library members dramatically reduces the diversity space needed in the library. The fingerprints of the solutions are created using artificial neural networks, principle component analysis, and/or discriminate analysis. The technique represents a marriage of supramolecular chemistry and pattern recognition protocols, and has become known as differential sensing. A variety of examples will be presented, ranging from applications in the biological sciences to commercial beverage analysis.

Nature has created mechanisms to detect salient objects like food, prey or mates. Visual search is the process of shifting gaze from one salient object to another. It has both a stimulus driven bottom-up component as well as a task-driven top-down component. This is well studied in human and primates but not so much in other animals. It is, therefore, a challenge to increase our understanding of visual search in non-primate animals. The barn owl is a predator having frontally oriented eyes, but lacking eye movements. Because of such specializations, this bird offers itself for the study of visual search. We study mechanisms of visual search in this animal on both the behavioural and neurophysiological levels. In this talk I will present our main findings on these matters.

A quantum computer holds the promise of solving some problems that are beyond the reach of the most powerful supercomputers. Due to theoretical and experimental breakthroughs in the last few years, we are now at a point where the feeling grows that a large-scale quantum computer can actually be built. Increasingly, this requires bridging the disciplines, from physics to engineering, materials science and computer science. In this talk, I will present the start-of-the-art in quantum computing and outline the challenges ahead, with a focus on electron spin qubits in semiconductors.