Charge Density at Oxide Surfaces

氧化物表面的电荷密度

• 批准号: 0455371
• 负责人: Laurence Marks
• 金额: --
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0455371&HistoricalAwards=false
• 关键词: Charge; Density; Oxide; Surfaces

The primary focus of the proposed research is to obtain experimental measurements of charge density changes at surfaces, with a particular emphasis on polar oxide surfaces. For the oxide surfaces, the charge transfer at the surface between the metal cation and oxygen will be measured from precision electron diffraction measurements. In addition, the redistribution of charge density will also be measured. These measurements will be compared to quantum-mechanical calculations, primarily using density functional techniques, done both as part of this effort and with theoretical collaborators. Questions of interest include how covalency and ionicity change at the surface, as well as rehybridization of the d-electrons and valence changes. Simultaneous with this work, ancillary data which may be significant in its own right on the character of steps on oxide surfaces will also be obtained, for instance step structures on antiferromagnetic NiO (111) surfaces. A continuing effort, albeit at a smaller scale, will be development of direct methods for surfaces. The idea is to test whether statistical methods such as multivariant statistical analysis or principle component analysis can be applied to the end product of direct methods, greatly simplifying the final analysis. If this concept works, it would have potential applications in other areas, for instance protein crystallography.

拟议的研究的主要重点是获得表面电荷密度变化的实验测量，特别强调极性氧化物表面。对于氧化物表面，金属阳离子和氧之间的表面电荷转移将通过精密电子衍射测量来测量。此外，还将测量电荷密度的再分布。这些测量将与量子力学计算进行比较，主要使用密度泛函技术，作为这项工作的一部分，并与理论合作者一起完成。感兴趣的问题包括共价性和离子性如何在表面变化，以及d-电子的再杂化和价态变化。与此同时，辅助数据，这可能是显着的，在其本身的权利上的氧化物表面上的台阶的字符也将获得，例如反铁磁NiO（111）表面上的台阶结构。一个持续的努力，虽然在较小的规模，将是表面的直接方法的发展。这个想法是为了测试统计方法，如多变量统计分析或主成分分析，是否可以应用于直接方法的最终产品，大大简化了最终分析。如果这个概念可行，它将在其他领域有潜在的应用，例如蛋白质晶体学。