Decoding and tuning the surface stability of perovskite oxides at the atomic level for faster oxygen exchange kinetics in energy conversion devices

在原子水平上解码和调整钙钛矿氧化物的表面稳定性，以实现能量转换装置中更快的氧交换动力学

• 批准号: 324830457
• 负责人: Professorin Dr. Franziska Heß
• 金额: --
• 依托单位: Nuclear Science and Engineering Department
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2018-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/324830457?language=en
• 关键词: Decoding; tuning; surface; stability; perovskite

Doped perovskite oxides serve as functional electrocatalyst layers in solid oxide fuel cells (SOFCs) because they can attain high electronic and oxide ion conductivity as well as good compatibility with common electrolyte materials. It has recently been identified that aliovalently doped perovskites, such as La1-xSrxMnO3 (LSM), form segregation layers capping the electrode surface under operating conditions, and this process is detrimental for electrode surface activity, thus degrading the material and SOFC performance over time. Reduction of strain energy due to cation size mismatch and electrostatic interaction with a space charge zone in the near-surface region have been proposed as the key mechanisms leading to cation segregation. The segregation is affected by external parameters, such as p(O2), T and applied potential. Because the interplay between the external conditions and material properties (i.e. cation size mismatch, and oxygen vacancy concentration) are not quantitatively understood on the atomistic level, it has not been possible to stabilize these surfaces using knowledge-based approaches. This project aims to quantitatively understand the relations of surface structure with environmental conditions, and material properties, and to predict conditions where stability against surface segregation and electrochemical activity are improved. The proposed computational framework unites the material properties and thermodynamic factors into a single Monte-Carlo model for predicting the evolution of the near-surface region. The expected outcome of the model is the ability to predict the distribution of dopant and host cations at the near-surface region of perovskite oxides, by accounting explicitly for the distribution of oxygen vacancies (giving rise to the proposed space charge zone). As a technologically important model perovskite electrocatalyst system, this research takes La0.8Sr0.2MnO3 as a starting point. The formation energies of oxygen vacancies and SrLa' defects close to the surface will be computed by density functional theory calculations and analyzed in terms of a cluster expansion in order to obtain a lattice Hamiltonian. Monte Carlo simulations of the near-surface region will yield the distribution of oxygen vacancies, as well as the cation segregation profile as a function of T and p(O2). Secondary phase formation will be studied by ab-initio thermodynamics considering formation and interface energies of likely candidates (e.g., SrO, Ruddlesden-Popper phases). Stabilization of the surface by modification with transition metal cations will be studied by considering the effect of surface substitution of Mn by Hf on the Sr segregation profile. This model will make it possible to understand accurately the factors leading to cation segregation and thus provide a first-principles basis for the optimization of surface properties on the atomic scale.

掺杂钙钛矿氧化物可用作固体氧化物燃料电池（SOFC）中的功能性电催化剂层，因为它们可以获得高电子和氧化物离子电导率以及与常见电解质材料的良好相容性。最近发现，异价掺杂的钙钛矿，例如 La1-xSrxMnO3 (LSM)，在工作条件下会形成覆盖电极表面的偏析层，并且该过程不利于电极表面活性，从而随着时间的推移会降低材料和 SOFC 的性能。由于阳离子尺寸不匹配以及与近表面区域中的空间电荷区的静电相互作用而导致的应变能降低已被认为是导致阳离子分离的关键机制。偏析受外部参数的影响，例如 p(O2)、T 和施加的电势。由于外部条件和材料特性（即阳离子尺寸失配和氧空位浓度）之间的相互作用无法在原子水平上定量理解，因此不可能使用基于知识的方法来稳定这些表面。该项目旨在定量了解表面结构与环境条件和材料特性的关系，并预测提高表面偏析稳定性和电化学活性的条件。所提出的计算框架将材料特性和热力学因素统一到单个蒙特卡罗模型中，用于预测近地表区域的演化。该模型的预期结果是能够通过明确考虑氧空位的分布（产生所提出的空间电荷区）来预测钙钛矿氧化物近表面区域的掺杂剂和主体阳离子的分布。作为技术上重要的模型钙钛矿电催化剂体系，本研究以La0.8Sr0.2MnO3为起点。靠近表面的氧空位和SrLa'缺陷的形成能将通过密度泛函理论计算来计算，并根据团簇展开进行分析，以获得晶格哈密顿量。近表面区域的蒙特卡罗模拟将得出氧空位的分布，以及作为 T 和 p(O2) 函数的阳离子偏析曲线。二次相的形成将通过从头热力学研究，考虑可能候选物（例如 SrO、Ruddlesden-Popper 相）的形成和界面能。通过考虑 Hf 表面取代 Mn 对 Sr 偏析曲线的影响，将研究通过过渡金属阳离子改性实现的表面稳定性。该模型将使得准确理解导致阳离子偏析的因素成为可能，从而为原子尺度上表面性质的优化提供第一性原理基础。