Nanostructured oxides find multiple uses in a diverse range of applications including catalysis, energy storage, and environmental management, their higher surface areas, and, in some cases, electronic properties resulting in different physical properties from their bulk counterparts. Developing structure-property relations for these materials requires a determination of surface and subsurface structure. Although microscopy plays a critical role owing to the fact that the volumes sampled by such techniques may not be representative of the whole sample, complementary characterization methods are urgently required. We develop a simple nuclear magnetic resonance (NMR) strategy to detect the first few layers of a nanomaterial, demonstrating the approach with technologically relevant ceria nanoparticles. We show that the 17O resonances arising from the first to third surface layer oxygen ions, hydroxyl sites, and oxygen species near vacancies can be distinguished from the oxygen ions in the bulk, with higher-frequency 17O chemical shifts being observed for the lower coordinated surface sites. H2 17O can be used to selectively enrich surface sites, allowing only these particular active sites to be monitored in a chemical process. 17O NMR spectra of thermally treated nanosized ceria clearly show how different oxygen species interconvert at elevated temperature. Density functional theory calculations confirm the assignments and reveal a strong dependence of chemical shift on the nature of the surface. These results open up new strategies for characterizing nanostructured oxides and their applications.
Bibliographical noteFunding Information:
This work was supported by the National Basic Research Program of China (2013CB934800 and 2011CB808505), the National Natural Science Foundation of China (NSFC) (20903056, 21222302, 21322307, and 21073083), NSFC-Royal Society Joint Program (21111130201), Program for New Century Excellent Talents in University (NCET-10-0483), the Fundamental Research Funds for the Central Universities (1124020512), and National Science Fund for Talent Training in Basic Science (J1103310). The ECUST group also thanks the Shanghai Rising-Star Program (12QH1400700) and National Super Computing Centre in Jinan for computing time. F.B. thanks the EU Marie Curie actions for an International Incoming fellowship 2011-2013 (grant no. 275212), Clare Hall, University of Cambridge, UK, for a Research fellowship and the University of Liverpool, UK, for funding. C.P.G. thanks the European Research Council for an Advanced Fellowship. This work was also supported by a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.