Data Analysis in Metastables Induced Electron Spectroscopy

1. Data Analysis in Metastables Induced Electron Spectroscopy Siddarth Chandrasekaran “Advanced Spectroscopy in Chemistry” University of Leipzig 18/12/2009 Module: Spectroscopy of Fluid Interfaces (13-122-0412)

2. Index Spectroscopy of Fluid Interfaces • Understanding MIES spectra • Data Analysis • Linear Combination • Singular Value Decomposition • Applications of Data Analysis • Conclusion

3. Understanding MIES Spectra Spectroscopy of Fluid Interfaces

4. Understanding MIES spectra Kim et al, J. Phys. Chem. B 107, (2003),592-596 Spectroscopy of Fluid Interfaces • Max. B.E. depends on source • He 23S – 19.8 eV • He 21S – 20.6 eV • Low penetration, outermost orbitals interact • Information about spin-orbit coupling, too

5. Understanding MIES spectra Kim et al, J. Phys. Chem. B 107, (2003),592-596 Spectroscopy of Fluid Interfaces Chemical shift can be observed For example: lowering of Binding Energy, because of neighbors Useful for characterizing surface reactions

6. Chemical Shift Kim et al, J. Phys. Chem. B 107, (2003),592-596 Spectroscopy of Fluid Interfaces Sum of work function of surface and Binding energy of 5p1/2 for adsorbed Xe constant

7. Data Analysis Spectroscopy of Fluid Interfaces

8. Data Analysis Spectroscopy of Fluid Interfaces • What Data? • MIES spectra • Important Prerequisite: Good spectra, so try to record best possible spectra • Why Analysis? • Improve quality of data • varies from simple baseline corrections to complicated mathematical calculations

9. Data analysis Spectroscopy of Fluid Interfaces • Helps to extract hidden (latent) information, but cannot create information • Multicomponent mixtures - Fraction of species present on the surface – QUANTITATIVE Analysis • In this talk focus is on Linear Combination method and Singular Value Decomposition (SVD)

10. Linear Combination Method Spectroscopy of Fluid Interfaces • When liquids with similar surface tensions are mixed • Smixture = a1Sspecies,1+a2Sspecies,2+….+anSspecies,n • S - spectra • a – surface fraction of the species • Only possible in the case of physical homogeneous (macroscopically homogeneous) mixtures • No orientational effects • No large domain formations • We need to know the pure spectra of the components

11. Linear combination Method H. Morgner* & M. Wulf , J. of Elec. Spec. and Rel. Phen. 74 (1995)91-97 Spectroscopy of Fluid Interfaces Reference Spectra

12. Linear Combination Method H. Morgner et aI. , Molecular Physics, 73, (1991), No. 6, 1295-1306 Smix = aBA* SBA + aFA* SFA aBA + aFA = 1 Recorded spectrum Simulated spectrum Inference: Linear combination of spectra are very effective in a few simple cases Spectroscopy of Fluid Interfaces

13. Example where linear combination not possible Lescop et al, Surface Science 565, (2004), 223-231 Spectroscopy of Fluid Interfaces The reaction has at least two intermediates with variable conc.'s which couldn’t be identified in this paper

14. Why Singular Value Decomposition (SVD) SVD Spectroscopy of Fluid Interfaces When linear combination of individual spectra not enough to reproduce the total spectra

15. When & what SVD? Spectroscopy of Fluid Interfaces • What information can we get from SVD • No. of components & their compositions • Spectra of unknown components possible • Pure spectra of one species can be obtained from mixture of species, especially useful when • Single monolayer spectra cannot be recorded • Orientational effects or chemical reactions

16. Singular Value Decomposition (SVD) Spectroscopy of Fluid Interfaces • Handy mathematical technique that has application to many problems • Given any mn matrix A, algorithm to find matrices U, V, and W such that A = UWVT U is mn and orthonormal W is nn and diagonal V is nn and orthonormal

17. SVD Spectroscopy of Fluid Interfaces • code used in Matlab • [U,W,V]=svd(A,0); • Matrix A contains the spectra recorded

18. SVD on 27 different spectra(optical spectroscopy) Performed SVD to get U,W & V matrix Spectroscopy of Fluid Interfaces SVD to be performed on the above spectra

19. W- Matrix The W-Matrix obtained by using the SVD algorithm The diagonal elements in percentage values to highlight the importance of the value Spectroscopy of Fluid Interfaces

20. Choice of no. of components Spectroscopy of Fluid Interfaces Red and Green line overlaps almost perfectly Two components not enough to reproduce spectra

21. Spectroscopy of Fluid Interfaces

22. U- Matrix for first three components Spectroscopy of Fluid Interfaces • The columns of the U-matrix have no physical significance. • Negative peaks • Linear combinations of the elements of the U-Matrix can represent spectra

23. Obtaining spectra of unknown components Spectroscopy of Fluid Interfaces • Lets consider three species system • Smixture = aαSspeciesα+aβSspeciesβ+aγSspeciesγ • aα+ aβ + aγ = 1 • In ideal case we know Sspeciesα & Sspeciesβ • Sspeciesγ = a1B1 + a2B2 + a3B3 • B1, B2, & B3 are basis of the U matix

24. Applications Spectroscopy of Fluid Interfaces

25. Determination of pure spectra of TBAI J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000)231–238 Spectroscopy of Fluid Interfaces PROBLEM : Pure spectra of solute (e.g.: salt) cannot be observed in liquid state • Earlier Methods used • Difference spectra Ssalt = S salt+solvent – a * Ssolvent • S is spectra & a is scaling factor (both are input parameters) • Peak areas fitting by ratio of salt/solvent • Intrinsic knowledge of intensity, position and linewidth of solvent spectra • Lots of assumptions

26. Determination of pure spectra of TBAI J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000)231–238 Spectroscopy of Fluid Interfaces MIE reference data of the pure solvents formamide and hydroxy-propionitrile.

27. Determination of pure spectra of TBAI J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000)231–238 Spectroscopy of Fluid Interfaces Three base spectra sufficient We expect three species – FA, TBAI & HPN

28. Determination of pure spectra of TBAI J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000)231–238 Spectroscopy of Fluid Interfaces Results obtained by SVD comparable with that by difference spectra method Greater sensitivity because of lower noise

29. Determination of pure spectra J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000)231–238 Spectroscopy of Fluid Interfaces MIES used to evaluate the surface fraction of each of the species

30. Determination of spectra of unknown component H. Morgner*, J. Oberbrodhage, J. of Elec. Spec. and Rel. Phen. 87 (1997)9-18 Spectroscopy of Fluid Interfaces Mixture of Pentadecane (PD) and Formamide (FA) The linear combination using only two species was not enough and hence need for third component

31. Determination of spectra of unknown component H. Morgner*, J. Oberbrodhage, J. of Elec. Spec. and Rel. Phen. 87 (1997)9-18 Spectroscopy of Fluid Interfaces Third component spectra similar to that of a standing alkane – orientation of the alkane (PD) can be seen

32. Determination of spectra of unknown component H. Morgner*, J. Oberbrodhage, J. of Elec. Spec. and Rel. Phen. 87 (1997)9-18 Spectroscopy of Fluid Interfaces Percentage contribution of each species is shown in the graph to the left

33. Conclusion Spectroscopy of Fluid Interfaces

34. Conclusion Spectroscopy of Fluid Interfaces • MIES – Surface specific • Data Analysis techniques like SVD & Linear Combinations are tools to extract hidden information • SVD is rather simple when we have acquired good quality spectra • But there is a need for good computational abilities and high speed computers

35. THANK YOU for your attention Spectroscopy of Fluid Interfaces

36. Metastables Electron Emission Microscopy (MEEM) Harada et al*, Nature 372 (1994) 657-659 Spectroscopy of Fluid Interfaces Controlling Helium beam diameter difficult Area from which electrons are abstracted can be controlled – spatial resolution Surface electron can be mapped non-destructively