AVS 52nd International Symposium
    Applied Surface Science Wednesday Sessions
       Session AS-WeM

Paper AS-WeM11
Improvements in the Spatial and Spectral Resolution of X-ray Photoelectron Images through Multivariate Analysis and Multisensor Fusion

Wednesday, November 2, 2005, 11:40 am, Room 206

Session: Essential Tools for Surface Analysis
Presenter: K. Artyushkova, The University of New Mexico
Authors: K. Artyushkova, The University of New Mexico
J.E. Fulghum, The University of New Mexico
L.R. Williams, The University of New Mexico
S.J. Hutton, Kratos Analytical Ltd., UK
S.J. Coultas, Kratos Analytical Ltd., UK
Correspondent: Click to Email
Improvements in spectral and spatial resolution of imaging X-ray photoelectron data are of growing importance, as the chemical complexity of materials under study increases, and the size of features to be resolved decreases. In this work we use a combination of multivariate analysis methods (MVA) and multisensor image fusion to resolve photoelectron image features in components that are similar in chemistry and small in size, relative to the spatial resolution of the technique. Methods combining XPS image acquisition schemes with multivariate analysis were tested to facilitate analysis of multicomponent samples containing spectrally overlapped chemical components. Additional spatial distribution information can potentially by obtained through multisensor image fusion of atomic force microscopy (AFM) and XPS images. X-ray photoelectron spectroscopy (XPS) has a high energy resolution but relatively low spatial resolution. In contrast, AFM images have significantly higher spatial resolution. We report initial efforts to combine low resolution color images (XPS) and a high resolution monochromatic images (AFM) to produce a higher spatial resolution XPS images. The validity of these approaches will be demonstrated using patterned SAM samples with known chemistry and spatial morphology. Application of these methods will be shown using images from phase-separated polymer blends. This work has been partially supported by NSF CHE-0350666 and UNM.