Relationship between composition, structure and conductivity in ceramic oxygen ion conductors with interstitial mechanism

固体氧化物燃料电池和固体氧化物电解槽电池可以将化学能直接转化为电能，反之亦然。这些电池有效运行的先决条件是具有高氧离子导电性的固体电解质。在普通氧离子导体中，氧的输运是通过氧空位来实现的，而近年来，具有间隙机制的氧离子导体越来越受到人们的关注。在本项目中，将用计算方法研究具有间隙机制的各种成分的氧离子导体。磷灰石和镁铝石结构的离子导体具有较高的氧离子导电性，是一种很有前途的材料。除了对这类材料的理论和实验研究外，对所有可能的成分只进行了一小部分的研究，还有大量的科学问题有待回答。因此，在本研究中，将对这些材料进行系统的研究，并确定具有最高氧离子电导率的成分。本项目分为三个阶段。第一阶段，应用密度泛函理论计算对不同成分的结构进行优化，识别成分对局部结构的影响；在第二阶段，计算间隙离子的迁移障碍，并采用适当的回归方法拟合结构参数。通过这种方法，建立了结构参数与迁移能之间的关系，为低迁移势垒、高电导率的氧离子导体的高效筛选提供了可能。在第三阶段，模拟有前途的材料的离子电导率，以确定氧离子电导率最高的材料。项目重点关注两个方面：1)深入了解导电机理以及结构与电导率的关系。ii)预测未知成分的电导率。在这种情况下，采用逐次筛选的方法，从平衡结构的结构参数估计迁移能量，从而减少计算量，而迁移能量的计算成本很高。在项目结束时，可以根据材料的组成和结构来估计材料的氧离子电导率，并可以预测具有高离子电导率的成分。

Solid oxide fuel cells and solid oxide electrolyzer cells allow the direct conversion of chemical to electrical energy and vice versa. Prerequisite for the efficient operation of these cells are solid electrolytes with high oxygen ion conductivity. In common oxygen ion conductors oxygen transport is enabled by oxygen vacancies, while in recent years oxygen ion conductors with an interstitial mechanism have gained increasing attention.In the present project, oxygen ion conductors of various compositions with an interstitial mechanism will be investigated with computational methods. As promising materials apatite- and melilite-structured ion conductors will be investigated, which exhibit high oxygen ion conductivity in experiments. Besides the theoretical and experimental studies on these types of materials only a small fraction of all possible compositions has been investigated and a large number of scientific questions still has to be answered. Therefore, in this study, these materials will be investigated systematically and compositions with highest oxygen ion conductivities are to be identified. The present project is divided into three stages. At the first stage, the structures of various compositions are optimized applying density functional theory calculations and the influence of the composition on the local structure is identified. At the second stage, the migration barriers for interstitial ions are calculated and are fitted to the structural parameters by suitable regression methods. In this way, a relationship between structural parameters and migration energies is established and an efficient screening process for oxygen ion conductors with low migration barriers and high conductivities is possible. At the third stage, the ionic conductivity of promising materials is simulated to identify materials with highest oxygen ion conductivities.The project focuses on two aspects: i) Deeper insight into conduction mechanisms and the relation between structure and conductivity. ii) Prediction of the conductivity of yet unknown compositions.In this context, a successive screening is applied to decrease the computational demand by estimating the migration energy, which is costly to calculate, from the structural parameters of the equilibrium structures. At the end of the project the oxygen ion conductivity of materials can be estimated based on the composition and the structure and the prediction of compositions with high ionic conductivity is possible.