Journal
SURFACE AND INTERFACE ANALYSIS
Volume 54, Issue 4, Pages 389-404Publisher
WILEY
DOI: 10.1002/sia.7057
Keywords
cellulose; engineered wood products; lignin; sample preparation; ToF-SIMS; wood; XPS
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This review provides detailed guidance on the surface analysis of wood using XPS and ToF-SIMS, including considerations related to the heterogeneity of wood composition, the impact of chemical removal of extractives, and potential contamination during sample preparation. It emphasizes the important role of multivariable analysis in surface analysis, and provides examples of its application in identifying contamination, quantifying wood composition, and determining the age of wood samples.
The surface analysis of wood and wood products is becoming increasingly important for reasons ranging from the investigation of molecular constituents through to the optimization of industrial processes. As with any natural product, wood analysis is not straightforward, and this review aims to provide guidance for the successful surface analysis of wood by XPS and ToF-SIMS. Through example experiments, three themes are addressed relevant to obtaining meaningful results: considerations related to heterogeneity in the composition of wood (e.g., growth rings); the impact of the chemical removal of minor wood components known as extractives, and whether such a process is necessary; and the potential for misleading or erroneous results as a result of contamination occurring during sample preparation. In addition to discussing successful sample preparation approaches, the important role to be played by MVA in surface analysis is emphasized, particularly in the analysis of ToF-SIMS data. Examples of ToF-SIMS/MVA are provided that highlight the identification of contamination in sample preparation, the quantification of wood composition in terms of cellulose and lignin, and the indication of age of softwood samples. Through consideration of the complexities that influence wood surface analysis, the design and interpretation of consequential experiments become easier and more accurate.
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