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Evaluation of the ionic conductivity of cation electrolytes by Kinetic Monte Carlo simulations

Subject Area Theoretical Chemistry: Electronic Structure, Dynamics, Simulation
Computer-Aided Design of Materials and Simulation of Materials Behaviour from Atomic to Microscopic Scale
Physical Chemistry of Solids and Surfaces, Material Characterisation
Term since 2021
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 452855747
 
Batteries and fuel cells allow the efficient storage of electrical energy and are inevitable for the energy transition and advancement of electromobility. In solid oxide fuel cells and solid state batteries, the ceramic electrolyte plays a crucial role. The development and optimization of electrolyte materials is thus required to increase efficiency, extend lifetime and lower cost of the devices.A wide variety of possible structures and compositions has been investigated in the past, but the sheer number of compounds complicates the experimental investigation of all possibilities. On an atomic level, material’s properties can be investigated by density functional theory and this approach has gained increasing importance in recent years, mainly due to the availability of computational resources. Using Kinetic Monte Carlo simulation, the energies and processes on the microscopic level can be applied to obtain the macroscopic ionic conductivity of the material by simulating the motion of mobile charge carriers through the lattice.In the present project, the ionic conductivity of selected cation conductors for Li+, Na+ and H+ ions will be investigated by combining density functional theory and Kinetic Monte Carlo simulations. The energy parameters, required in Monte Carlo simulations, will be obtained from literature and complemented by own calculations. The project is composed of four steps. In the first step, promising cation conductors are identified and energy parameters are collected from literature. In the second step, these energies are complemented by own calculations and used to create energy models in the third step. In the fourth step, the energy models are applied in Kinetic Monte Carlo simulations to obtain the ionic conductivity depending on temperature and composition.The goal of the project is the understanding and prediction of ionic conductivity. On the one hand side, a deeper insight into ionic conduction mechanisms and relation between composition, structure and ionic conductivity should be obtained. On the other hand, the project aims to predict materials with high ionic conductivity and optimize the composition.
DFG Programme Research Grants
 
 

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