Combining PCA and nonlinear fitting of peak models to re-evaluate C 1s XPS spectrum of cellulose

被引:41
作者
Fernandez, Vincent [1 ]
Morgan, David [2 ,3 ]
Bargiela, Pascal [4 ]
Fairley, Neal [5 ]
Baltrusaitis, Jonas [6 ]
机构
[1] Univ Nantes, Inst Materiaux Jean Rouxel, CNRS, IMN, F-44000 Nantes, France
[2] Cardiff Univ, Sch Chem, Main Bldg,Pk Pl, Cardiff CF10 3AT, Wales
[3] Res Complex Harwell RCaH, HarwellXPS EPSRC Natl Facil Photoelectron Spect, Didcot OX11 0FA, Oxon, England
[4] Inst Res Catalysis & Environm Lyon IRCELYON, 2 Ave Albert Einstein, F-69626 Villeurbanne, France
[5] Casa Software Ltd, Bay House,5 Grosvenor Terrace, Teignmouth TQ14 8NE, Devon, England
[6] Lehigh Univ, Dept Chem & Biomol Engn, 111 Res Dr, Bethlehem, PA 18015 USA
基金
英国工程与自然科学研究理事会;
关键词
XPS; PCA; Cellulose; Peak model; Spectra; FIBERS;
D O I
10.1016/j.apsusc.2022.156182
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Cellulose is an example of a material that responds to XPS by the creation of new chemistry not present in the as-received sample. While improvements in instrumentation may be seen in general as beneficial to surface science, recent studies have shown that the consequences for some materials are detrimental. In this work, these problems are illustrated through an analysis of cellulose spectra obtained during a degradation study. C 1s spectra are decomposed into two well-formed component curves that are open to chemical interpretation. In particular, a component-curve representative of pure cellulose is obtained as well as a second component curve that implies cellulose is degraded through the creation of carbon chemistry involving C-O, C--O and O-C--O. Since cel-lulose is a crystalline material, formed through the alignment of molecules under the influence of hydrogen bonds, the analysis and findings presented in this paper are relevant to any material analyzed by XPS whose properties are dependent on hydrogen bonds. The analysis techniques are based on an informed vectorial approach, which extracts directly from data spectral shapes that are used to monitor sample degradation via linear least squares optimization. Related mathematics of Principal Component Analysis and linear analysis are presented.
引用
收藏
页数:10
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