| AVS 58th Annual International Symposium and Exhibition | |
| Applied Surface Science Division | Tuesday Sessions |
| Session AS-TuA |
| Session: | Imaging and 3D Chemical Analysis - Part II |
| Presenter: | Kateryna Artyushkova, The University of New Mexico |
| Authors: | K. Artyushkova, The University of New Mexico S.J. Coultas, Kratos Analytical Inc. S.J. Hutton, Kratos Analytical Inc. A.J. Roberts, Kratos Analytical Inc. |
| Correspondent: | Click to Email |
The sputtering of solids with ion beams followed by analysis with photoelectron spectroscopy has been widely used as it offers a powerful strategy for the in-depth characterization of complex inorganic materials. The combination of imaging techniques with depth profiling to create three-dimensional information is an obvious and exciting extension of these experiments. Recent introduction of cluster ion beams, such as coronene, into XPS instrumentation offers capabilities in quantifying the chemical and molecular gradients in the near surface region of soft materials, such as polymers and biomaterials. XPS data can be acquired as a function of sputter depth into organic materials while maintaining molecular integrity.
There are only a handful number of studies combining XPS imaging and depth sputtering. One of the biggest problems when dealing with 3D imaging data sets is visualizing the lateral distribution of chemical moieties as a function of depth. When multispectral images are acquired at each sputtered depth, four-dimensional datasets can result with a full spectrum acquired at each voxel of the space. These datasets represent a huge amount of data which can only be interpreted with assistance of Multivariate Analysis.
In this research we report on application of various types of MSA methods such as two-step PCA and two-step MCR-ALS, PARAFAC, MFA, Tucker and 3D MCR-ALS to multispectral XPS imaging data acquired as a function of sputtering depth for different heterogeneous biomaterials and polymers. The component images extracted from MSA, which show the spatial distribution of the various chemical components, will be visualized in 3D individually or together representing an overall chemistry of individual layers.