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允许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传导性的固体电解质。在普通的氧离子导体中，氧的输运是通过氧空位来实现的，而近年来，具有填隙机制的氧离子导体受到了越来越多的关注，在本项目中，将用计算方法研究具有填隙机制的各种组成的氧离子导体。磷灰石和黄长石结构的离子导体是很有前途的材料，在实验中表现出很高的氧离子电导率。除了对这些类型材料的理论和实验研究之外，只研究了所有可能组成中的一小部分，并且仍有大量科学问题需要回答。因此，在这项研究中，这些材料将进行系统的研究，并确定具有最高氧离子电导率的组合物。本项目分为三个阶段。在第一阶段，各种组合物的结构进行了优化，应用密度泛函理论计算和局部结构上的组合物的影响被确定。在第二阶段，计算间隙离子的迁移势垒，并通过合适的回归方法拟合到结构参数。通过这种方式，建立了结构参数和迁移能之间的关系，并且可以有效地筛选具有低迁移势垒和高电导率的氧离子导体。在第三阶段，模拟有前景的材料的离子电导率，以确定具有最高氧离子电导率的材料。该项目集中在两个方面：i）更深入地了解导电机制以及结构与电导率之间的关系。ii）预测未知组分的电导率：在这种情况下，通过从平衡结构的结构参数估计迁移能来应用连续筛选以减少计算需求，所述迁移能计算起来是昂贵的。在项目结束时，可以根据组成和结构估计材料的氧离子电导率，并预测具有高离子电导率的组成是可能的。

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.