Stars are the basic building blocks of the visible Universe. Understanding how they transformed the pristine Universe into the one we live in today is at the heart of astrophysical research and vital for many areas in astrophysics. Massive stars, in particular, are cosmic powerhouses because of their radiative, mechanical and chemical feedback from stellar winds and supernova explosions. Thanks to new telescopes and observatories, massive star research is entering a golden era, as exemplified by transient surveys and the dawn of gravitational-wave astronomy. Yet, our understanding of the lives and final fates of massive stars is incomplete. Binary stars are of particular importance because the vast majority of all massive stars will exchange mass with a companion during their life, thereby completely changing their evolution and final fates. About 25% of massive stars are even thought to merge. The merger phase is largely unexplored and the consequences of binary mass exchange for supernovae are poorly understood. To remedy this situation, I propose to build the essential theoretical framework to help understand massive stars. My group will conduct the first 3D magnetohydrodynamical simulations of stellar mergers, develop merger prescriptions for stellar evolution codes, compute grids of massive single and binary stars that cover all relevant phases, and build the required statistical methods to compare models with observations. We will unravel whether merging can explain the origin of strong magnetic fields in 10% of massive stars and thereby also that of the strongest magnetic fields in the Universe, namely those of magnetars. Moreover, we will study the asteroseismic properties of mergers and will understand how binary mass exchange affects pre-SN structures and hence the explosions of massive stars. In this way, we will push the frontiers of massive star research and help to approach a truly comprehensive picture of the lives and final fates of massive stars.

What would a star look like below its opaque surface? What are the physical conditions in a star? What physical processes play an important role in stars? How do these physical conditions and processes interact? How do they change with time, when a star evolves? Answering these kinds of questions is of fundamental importance for astronomy and beyond. Stars are a dominant source of light in the universe as well as main building blocks of planetary systems and galaxies. Thus, understanding of stars has a major impact in these fields. Closer to home, understanding the past and future of the Sun has a potentially wide-ranging impact on other scientific fields. To pierce inside stars, we need observable features that are sensitive to the hidden layers in stars. Intrinsic global oscillations are observable, and are sensitive to the internal structures of stars. The application of these global modes to study internal stellar structures is the field of asteroseismology. Particularly interesting and opportune stars to apply asteroseismology to are red-giant stars. These evolved stars are abundant, relatively bright, exhibit different stellar structures, allow to trace back a long history, and possess probes that are sensitive to both their deep and their more shallow layers; the so-called mixed dipole oscillation modes. The observed characteristics of mixed dipole modes differ significantly between different red-giant stars, leading to the following questions: • ‘What are the physical differences in the structures of / conditions in red-giant stars which lead to different mixed dipole mode oscillation spectra?’ • ‘What is the cause of the different structures / conditions in these stars?’ The aim of the DipolarSound proposal is to unravel the physical conditions and physical processes at play in red-giant stars using mixed dipole oscillation modes and to understand the underlying physical origin of the different oscillation spectra observed in red-giant stars.

Functional, topologically complex organic molecules are rising stars in modern materials science due to their biocompatibility, structural variability, and wealth of physico-chemical properties. Their practical applications often involve interactions with small molecular targets (e.g., gases, environmental pollutants, and drugs) via relatively weak non-covalent forces. Key to these interactions are the topological features of host materials: arrangement of functional groups, pore size, and cavity volume. Atom types and the forces connecting them in space determine molecular and material structures, defining their fundamental physical and chemical properties. These patterns comprise a universal chemical language. Numerous molecular representations exist, from strings in chemoinformatics to matrices in chemical machine learning. While these big data-oriented fingerprints generally reduce the dimensionality of atomic composition and connectivity, they do not capture the intricacies of shape and topology. In PATTERNCHEM, several families of functional organic materials – graphenes, covalent-organic frameworks, and hyperbranched polymers – will provide a unique foundation for developing application-oriented fingerprints of their topological and non-covalent interaction features. After elucidating diverse structural descriptors of atomistic arrangement, substitution patterns, and two- and three-dimensional shapes of these materials, we will establish a scheme for quantifying the propensity for non-covalent interactions and assessing host-guest complementarity. Using this scheme, chemical and physical performance indicators relevant to targeted applications (e.g., as sensors, filters, and nanocarriers) can be computed. Finally, structure-property relationships between computed performance indicators and developed descriptors will be established and implemented into predictive frameworks for functional organic materials.