Doc. dr. Matej Kanduč

works at the Department of theoretical physics. With his collaborators, he focuses predominantly on the molecular modeling of biological and soft-matter systems. His primary research interests are thermoresponsive polymeric hydrogels, lipid structures, surfactants, various wetting processes, as well as hydration and hydrophobic interactions. For his research, he received the Zois distinction in 2021.

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Research programme: Biophysics of polymers, membranes, gels, cooloids and cells
Training topic: Computer simulations of surfactant- and lipid-based systems

The Ph.D. candidate will work in the biophysics group at the Department of theoretical physics. He/she will join an established research framework of Dr. Kanduc composed of several group members as well as researchers from institutions abroad, predominantly in Germany. The research will be focused on computer simulations and theoretical studies of supramolecular structures of surfactants and lipids.

Surfactants (or “surface-active agents”) have a polar head group compatible with water and a nonpolar tail compatible with oil. This dual nature lends them their unique ability to self-assemble into micelles and vesicles and to adsorb to various interfaces. Surfactants are paramount to a wide range of technological applications, ranging from everyday home and personal care products all the way to agriculture, petrochemistry, and beyond. A special class of biological surfactants is lipids, which serve as biochemical building blocks of biological matter, such as cell membranes and lipoproteins. Thus, it is no surprise that much of contemporary soft matter research is driven by a quest to understand and control surfactant self-assembly from fundamental and technological perspectives. Yet, the self-assembly of surfactants remains a modeling challenge because atomistic simulations cannot directly capture the relevant timescales, and special techniques should be invoked.

The main methodological tool during the candidate’s research will be Molecular Dynamics (MD), which is a computer simulation method to model the physical motion of atoms and molecules. The MD simulations are a valuable tool, as they can provide insights into microscopic details, some of which are experimentally difficult to access. The candidate will develop computer models of surfactants and lipids based on the standard interatomic potentials known as force fields. For performing MD simulations, the departmental high-performance computing cluster will be used. The candidate will then combine advanced simulation techniques with a self-consistent theoretical framework to obtain a full thermodynamic description of micellization, aggregation, and interface adsorption of surfactants. We will address several topics, such as the stabilization of hydrophobic/aqueous phases by surfactants and the study of lipid nanoparticles and lipid-coated nanobubbles. Lipid nanoparticles are a novel pharmaceutical drug delivery system, which became a hot research topic in the past two years owing to the success of mRNA vaccines. Lipid-coated nanobubbles are another modern nanotechnological concept, which also Nature uses to stabilize water under tension in plants.

Using modern computational tools and the insights gained into the molecular structure, we will try to explain several of the many unsolved puzzles of these surfactant-based nanoscopic systems.