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STM image contrast interpretation and its role in determining the structure of transition metal oxide surfaces.

机译:STM图像对比度解释及其在确定过渡金属氧化物表面结构中的作用。

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摘要

he surfaces of transition metal oxides play a critical role in many applications such as heterogeneous catalysis, gas detection, thermionic emission, electrolysis, and photolysis. Understanding the mechanisms of such surface processes requires a detailed knowledge of the surface microscopic structure. Since its invention in the early 1980's, scanning tunneling microscopy (STM) has come to be a popular tool for oxide surface studies. However, despite some experimental successes, interpretation of the contrast in STM images of metal oxides has remained challenging due to the numerous contributing factors such as nonstoichiometry, structural complexity, surface disorder, and uncertainties regarding the bonding and termination layers in such multicomponent systems. In this thesis work, a computer simulation scheme that explores these effects separately has been developed to assist the interpretation of atomic-scale contrast in STM images.;A semiquantitative technique, based on the one-dimensional square well tunneling model, is used to simulate constant current STM images. This model provides an efficient mechanism to test and explore effects of various ill-defined experimental parameters. The method was applied to the atomic-scale resolution STM study of three transition metal oxides:
机译:过渡金属氧化物的表面在许多应用中起着至关重要的作用,例如多相催化,气体检测,热电子发射,电解和光解。了解这种表面过程的机理需要对表面微观结构有详细的了解。自从1980年代初期发明以来,扫描隧道显微镜(STM)已经成为氧化物表面研究的流行工具。然而,尽管在实验上取得了一些成功,但是由于众多的影响因素,例如非化学计量,结构复杂性,表面无序性以及这种多组分系统中键合和终止层的不确定性,如何解释金属氧化物的STM图像中的对比度仍然具有挑战性。在本文工作中,开发了一种计算机模拟方案,分别探讨了这些效应,以帮助解释STM图像中的原子级对比度。;基于一维方阱隧穿模型的半定量技术用于模拟恒流STM图像。该模型提供了一种有效的机制来测试和探索各种不确定的实验参数的影响。该方法用于三种过渡金属氧化物的原子级分辨率STM研究:

著录项

  • 作者

    Lu, Weier.;

  • 作者单位

    Carnegie Mellon University.;

  • 授予单位 Carnegie Mellon University.;
  • 学科 Materials science.;Chemical engineering.;Condensed matter physics.
  • 学位 Ph.D.
  • 年度 1995
  • 页码 132 p.
  • 总页数 132
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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