Anode-free lithium batteries (AF-LIBs) have emerged as a promising alternative to conventional lithium-metal batteries due to their potential for higher energy densities, improved safety, and simplified manufacturing processes. However, their rapid development is hindered by poor charge/discharge cycles. This is due to the side reactions of the conventional battery electrolytes to form dead/inactive lithium, thereby leading to dendritic Li plating. I propose to investigate the use of High Concentrated Electrolytes (HCEs) and Multi-salt Electrolytes (MSEs) as novel approaches to achieve a robust and efficient plating and stripping of Li in AF-LIBs. The high concentration and/or presence of additives in these proposed electrolytes can regulate the thermodynamics and kinetics of the Li deposition/striping process, thereby overcoming dendritic Li growth. To achieve this objective, I will prepare novel HCEs, and MSEs and use various in-situ and operando structural and spectroscopic techniques to gain insights into the effects of the electrolyte types (different types of anion and cation) and composition on the lithium deposition and formation of SEI in AF-LIBs. These fundamental insights will facilitate the development of AF-LIBs, which are among the next-generation advanced energy storage technologies that are pivotal to the realization of energy and environmental sustainability.

Initially a model to describe superconductivity, Landau-Ginzburg (LG) models were promoted in the late 80s to supersymmetric quantum field theories (QFTs) completely characterized by a polynomial W called potential. They gained importance in string theory and algebraic geometry as they play an interesting role in homological mirror symmetry. On the other hand, conformal field theories (CFTs) have been another kind of QFTs which display conformal symmetry. They have focused many efforts to understand the mathematical structures which encode them, e.g. inspiring the definition of vertex operator algebras (Borcherds, Fields medalist ’88) or pushing forward our knowledge of modular tensor categories. Despite seeming two very different topics, LG models and CFTs are intimately related via a result of theoretical physics — the LG/CFT correspondence— stating that the infrared fixed point of a LG model with potential W is a CFT of central charge c(W). Mathematically this implies equivalences of categories of matrix factorizations (which describe defects of LG models) and categories of representations of vertex operator algebras (which describe defects of CFT). Up to date, we lack a complete understanding of the LG/CFT correspondence and we only have a few examples. The main goal of this Marie Curie is to find a mathematical statement for it, via completing a list of examples, exploring their properties (e.g. tensoriality or even modularity of the categories) and then attacking the main goal. Utrecht University (host institution) is one of the few places in Europe hosting experts in representation, category and Galois theory and mathematical physics, providing exactly the necessary and complementary expertise required to achieve this goal. These results will build a surprising bridge between very different areas of mathematics, opening new research gates completely inspired by physics.

Almost all critical functions in the cell rely on specific protein-protein interactions (PPIs). Understanding interactions is therefore a crucial step in the investigation of biological systems and in drug design. Despite all the research efforts that have been devoted to unravel principles of PPIs in the past decades, we still lack a thorough understanding of the energetics of proteins association, which is limiting our ability to consistently predict protein complexes, engineer high-affinity interactions and design new drugs. An improved understanding of protein binding affinity holds the key for resolving some of the most important problems in molecular biology, with wide implications in related fields. In this project I propose a novel approach to reliably predict the binding affinity by adding the so-far neglected dynamical dimension to the problem. Unlike traditional methods like empirical energy-based scoring, I will assess the conservation of interface contacts in protein complexes during dynamics trajectories. By correlating such properties to experimental binding affinities, a new predictor will be developed. Preliminary results on limited set of complexes already indicate that this approach has a great potential, outperforming any predictor proposed to date. Moreover, I will expand this novel approach and assess its applicability to other critical research fields related to biomolecular interactions, such as docking and proteins and interactions engineering. This project will allow me to reinforce and further expand my skills and expertise, create new collaborations and reinforce my position as researcher in Europe, which will enable me to reach full independency in the future.