Application of surface chemical analysis tools for characterization of nanoparticles
Abstract
The important role that surface chemical analysis methods can and should play in the characterization of nanoparticles is described. The types of information that can be obtained from analysis of nanoparticles using Auger electron spectroscopy (AES), X-ray photoelectron spectroscopy (XPS), time-of-flight secondary-ion mass spectrometry (TOF-SIMS), low-energy ion scattering (LEIS), and scanning-probe microscopy (SPM), including scanning tunneling microscopy (STM) and atomic force microscopy (AFM), are briefly summarized. Examples describing the characterization of engineered nanoparticles are provided. Specific analysis considerations and issues associated with using surface-analysis methods for the characterization of nanoparticles are discussed and summarized, with the impact that shape instability, environmentally induced changes, deliberate and accidental coating, etc., have on nanoparticle properties.
Atomic force microscopy image of Cu2O nanodots formed on a SrTiO3 substrate.
Keywords
Nanoparticles Nanotechnology X-ray spectroscopy (XPS XRF EDX) CatalystsNotes
Acknowledgements
This paper has evolved from research programs supported by the US Department of Energy (DOE) and research conducted as part of the Environmental Molecular Sciences Laboratory (EMSL) User Program. It has benefited from interactions with colleagues from around the world and input from experts associated with ISO TC 201 Surface Chemical Analysis and ASTM Committee E42 on Surface Analysis. Aspects of the work have been supported by the DOE Offices of Basic Energy Sciences and Biological and Environmental Research. Portions of this work were conducted in EMSL, a DOE user facility operated by Pacific Northwest National Laboratory for the DOE Office of Biological and Environmental Research. We thank MH Engelhard for the XPS data on the iron nanoparticles. DGC and SDT thank NIH grants EB-002027 and GM-074511 for support and for funding some of the experimental work described in this paper. SDT thanks the NSF for an IGERT fellowship.
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