Monolayer Intermixed Oxide Surfaces: Fe, Ni, Cr, and V Oxides on Rutile TiO2(011)

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• 作者：Sandamali Halpegamage ; Zhan-Hui Wen ; Xue-Qing Gong ; Matthias Batzill
• 刊名：Journal of Physical Chemistry C
• 出版年：2016
• 出版时间：July 14, 2016
• 年：2016
• 卷：120
• 期：27
• 页码：14782-14794
• 全文大小：1035K
• 年卷期：0
• ISSN：1932-7455

文摘

The oxide/oxide interface for monolayer oxides on rutile TiO₂(011) substrates is investigated for several transition metal (M) oxides, with M = Fe, Ni, Cr, and V. The samples are prepared using ultrahigh vacuum sample preparation procedures and are characterized with a combination of photoemission spectroscopy and scanning tunneling microscopy (STM). Furthermore, stable intermixed monolayer oxides are determined by density functional theory (DFT)-based simulations and compared with the experimental results. Experimentally we find that for specific oxidation conditions a monolayer intermixed oxide is formed for all M. Although different structures as well as oxides in different oxidation states can be obtained depending on the preparation conditions, one common structure has been identified for all M. This intermixed oxide appears to have a defined composition of MTi₂O₅. For very small amounts of M the surface segregates into a pure TiO₂(011)-2 × 1 surface and into domains of the MTi₂O₅ phase, indicating that this intermixed oxide monolayer is a low-energy line phase in a compositional surface phase diagram. The gas-phase oxygen pressure that is required to form the intermixed MTi₂O₅ surface increases in the order of V < Cr < Fe < Ni in accordance of the enthalpy of oxide formation for these transition metals. For V, deposition and annealing in UHV already results in the formation of the intermixed oxide without the presence of any gas-phase oxygen. Exposure to background oxygen, on the contrary, results in the formation of a V-oxide adlayer with higher (3+ and 4+) oxidation states. Stable MTi₂O₅ monolayer phases are also obtained in DFT simulations, and a comparison of simulated STM with experiment allows us to identify the most likely structural model.