Lattice structures are ubiquitous in nature, which determine diverse physical and chemical properties of materials. Exploring and controlling crystal structures is a central task of material engineering. Lattice phase transition is considered as a significant approach to manipulate and control functionalities, and thus, understanding the underlying mechanism of phase transition is a basic premise and guarantee for technological applications. A fundamental understanding of the cooperative interplay between charge, spin, orbital and lattice is required to manipulate this process. The emergence of magnetic Van der Waals (vdW) crystals opened up new horizons for engineering phase transition with magnetic orders together beyond the reach of existing materials. Traditional investigation of magnetic phase transition requires neutron diffraction, which requires nuclear reactor to generate neutrons. In this project, I propose to use three-dimensional electron diffraction (3DED) to study the 3D magnetic orderings, which will serve as a complimentary method to neutron diffraction. I will also study the dynamical behaviour of magnetic ordering in vdW crystals under different electric bias conditions. In addition, I will study the 3D magnetic field distribution at the interface of heterostructures constructed by vdW crystals. I will develop continuous fast holographic tomography (CFHT) with much lower dose and higher speed compared to traditional step-wise tomography. I will also apply a special 3D reconstruction algorithm to reveal and visualize the 3D magnetic field at the heterostructure interface. The outputs of this project will provide insight into the synergy effects of charge, spin and lattice in magnetic materials and greatly facilitate the discovery of novel magnetic materials.

Lithium-ion batteries (LIBs) play an important role in our daily life with a variety of applicants. To this day, significant resources have been dedicated to the development of high-performance LIBs, particularly the research necessary to identify the optimum electrolyte materials to solve the safety issue. Up to this point polymer electrolytes are widely investigated for their potential to improve batteries’ safety. Given the relative high ionic conductivity, λ, around 10-3 S/cm, poly-ethylene oxide (PEO) is frequently utilized as the polymer matrix in this scenario. But compared to the commercial liquid electrolyte, the ionic conductivity of polymer electrolyte needs to be improved for at least ten times. It is widely acknowledged that the transportation of Li+ is directly related to the segmental and backbone motions of the polymer indicating to improve the ionic conductivity by structure optimization of polymer. Instead of using the traditional trial and error method, modern innovative studies intend to develop a microscopic picture of the Li–ion transportation process to instruct the polymer optimization but it is difficult with in-house laboratory methods. This project aims at designing a polymer with high ionic conductivity. To achieve this goal, the microscopic view of Li+ transportation in polymer will be elucidated through molecular dynamics (MD) simulation and the polymer dynamics will be clarified with MD simulation and Quasi-elastic Neutron Scattering (QENS).

With the European Green Deal and its goal to reach net zero greenhouse gas emissions in Europe by 2050, the increased use of the subsurface is inevitable. The large-scale exploitation of the subsurface for storage (e.g., gases) and extraction activities (e.g., geothermal energy) will create large scale perturbations which can destabilize the rock and allow leakage of contaminants into groundwater. Therefore, we need a sound understanding of coupled hydro-geochemical processes arising from such activities, as well as tools to predict these impacts reliably. Reactive Transport Modeling (RTM) has so far proven to be the most powerful tool to track the fate of subsurface contaminants from laboratory up to geological timescales. However, the simplistic approaches to describe the gas-water-mineral interactions in RTM do not accurately capture the complex processes in geological environments, as they do not consider relevant processes that take place at the microscopic scale. These processes need to be upscaled (integrated) into RTM. This requires detailed insights into mineral crystallization processes involving gas in confined porous media, particularly (i) coupled mineral dissolution and precipitation with gas generation and (ii) mineral nucleation at the water-gas interface, since both affect the transport properties and mineralogical reactivity of the rock matrix. Genies will integrate cutting-edge lab-on-a-chip, i.e., miniaturized (microfluidic) experiments with advanced, in operando, micro-analytical techniques and an interdisciplinary environment to provide the insights needed for upscaling. This project will provide high-fidelity experimental datasets that will bring new theoretical insights into hydro-geochemical processes involving gases. The resulting extended RTM will allow reliable modeling of the fate of contaminants and consequently reduce uncertainty when assessing the integrity of subsurface storage and extraction systems.