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Siddarth Chandrasekaran “Advanced Spectroscopy in Chemistry” “Advanced Spectroscopy in Chemistry” University of Leipzig 18/12/2009 Module: Spectroscopy.

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Presentation on theme: "Siddarth Chandrasekaran “Advanced Spectroscopy in Chemistry” “Advanced Spectroscopy in Chemistry” University of Leipzig 18/12/2009 Module: Spectroscopy."— Presentation transcript:

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

2 Index  Understanding MIES spectra  Data Analysis  Linear Combination  Singular Value Decomposition  Applications of Data Analysis  Conclusion 18/12/09Spectroscopy of Fluid Interfaces2

3 18/12/09Spectroscopy of Fluid Interfaces3

4 Understanding MIES spectra  Max. B.E. depends on source  He 2 3 S – 19.8 eV  He 2 1 S – 20.6 eV  Low penetration, outermost orbitals interact  Information about spin-orbit coupling, too 18/12/09Spectroscopy of Fluid Interfaces4 Kim et al, J. Phys. Chem. B 107, (2003), 592-596

5 Understanding MIES spectra  Chemical shift can be observed  For example: lowering of Binding Energy, because of neighbors  Useful for characterizing surface reactions 18/12/09Spectroscopy of Fluid Interfaces5 Kim et al, J. Phys. Chem. B 107, (2003), 592-596

6 Chemical Shift  Sum of work function of surface and Binding energy of 5p 1/2 for adsorbed Xe constant 18/12/09Spectroscopy of Fluid Interfaces6 Kim et al, J. Phys. Chem. B 107, (2003), 592-596

7 18/12/09Spectroscopy of Fluid Interfaces7

8 Data Analysis  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 18/12/09Spectroscopy of Fluid Interfaces8

9 Data analysis  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) 18/12/09Spectroscopy of Fluid Interfaces9

10 Linear Combination Method  When liquids with similar surface tensions are mixed  S mixture = a 1 S species,1 +a 2 S species,2 +….+a n S species,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 18/12/09Spectroscopy of Fluid Interfaces10

11 Linear combination Method  Reference Spectra 18/12/09Spectroscopy of Fluid Interfaces11 H. Morgner* & M. Wulf, J. of Elec. Spec. and Rel. Phen. 74 (1995) 91-97

12 Linear Combination Method 18/12/09Spectroscopy of Fluid Interfaces12 H. Morgner et aI., Molecular Physics, 73, (1991), No. 6, 1295-1306 S mix = a BA * S BA + a FA * S FA a BA + a FA = 1 Inference: Linear combination of spectra are very effective in a few simple cases

13 Example where linear combination not possible  The reaction has at least two intermediates with variable conc.'s which couldn’t be identified in this paper 18/12/09Spectroscopy of Fluid Interfaces13 Lescop et al, Surface Science 565, (2004), 223-231

14 Why Singular Value Decomposition (SVD)  When linear combination of individual spectra not enough to reproduce the total spectra 18/12/09Spectroscopy of Fluid Interfaces14

15 When & what SVD?  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 18/12/09Spectroscopy of Fluid Interfaces15

16 Singular Value Decomposition (SVD)  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 = U W V T U is m  n and orthonormal W is n  n and diagonal V is n  n and orthonormal 18/12/09Spectroscopy of Fluid Interfaces16

17 SVD  code used in Matlab  [U,W,V]=svd(A,0);  Matrix A contains the spectra recorded 18/12/09Spectroscopy of Fluid Interfaces17

18 SVD on 27 different spectra (optical spectroscopy) SVD to be performed on the above spectra 18/12/09Spectroscopy of Fluid Interfaces18 Performed SVD to get U,W & V matrix

19 W- Matrix 18/12/09Spectroscopy of Fluid Interfaces19 The W-Matrix obtained by using the SVD algorithm The diagonal elements in percentage values to highlight the importance of the value

20 Choice of no. of components  Red and Green line overlaps almost perfectly  Two components not enough to reproduce spectra 18/12/09Spectroscopy of Fluid Interfaces20

21 18/12/09Spectroscopy of Fluid Interfaces21

22 U- Matrix for first three components  The columns of the U-matrix have no physical significance.  Negative peaks  Linear combinations of the elements of the U-Matrix can represent spectra 18/12/09Spectroscopy of Fluid Interfaces22

23 Obtaining spectra of unknown components  Lets consider three species system  S mixture = a α S species α +a β S species β +a γ S species γ  a α + a β + a γ = 1  In ideal case we know S species α & S species β  S species γ = a 1 B 1 + a 2 B 2 + a 3 B 3  B 1, B 2, & B 3 are basis of the U matix 18/12/09Spectroscopy of Fluid Interfaces23

24 18/12/09Spectroscopy of Fluid Interfaces24

25 PROBLEM : Pure spectra of solute (e.g.: salt) cannot be observed in liquid state  Earlier Methods used  Difference spectra S salt = S salt+solvent – a * S solvent  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 18/12/09Spectroscopy of Fluid Interfaces25 Determination of pure spectra of TBAI J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000) 231–238

26 Determination of pure spectra of TBAI  MIE reference data of the pure solvents formamide and hydroxy- propionitrile. 18/12/09Spectroscopy of Fluid Interfaces26 J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000) 231–238

27  Three base spectra sufficient  We expect three species – FA, TBAI & HPN 18/12/09Spectroscopy of Fluid Interfaces27 Determination of pure spectra of TBAI J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000) 231–238

28  Results obtained by SVD comparable with that by difference spectra method  Greater sensitivity because of lower noise 18/12/09Spectroscopy of Fluid Interfaces28 Determination of pure spectra of TBAI J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000) 231–238

29  MIES used to evaluate the surface fraction of each of the species 18/12/09Spectroscopy of Fluid Interfaces29 Determination of pure spectra J. Oberbrodhage*,J. of Elec. Spec. and Rel. Phen.107 (2000) 231–238

30 Determination of spectra of unknown component  Mixture of Pentadecane (PD) and Formamide (FA)  The linear combination using only two species was not enough and hence need for third component 18/12/09Spectroscopy of Fluid Interfaces30 H. Morgner*, J. Oberbrodhage, J. of Elec. Spec. and Rel. Phen. 87 (1997) 9-18

31  Third component spectra similar to that of a standing alkane – orientation of the alkane (PD) can be seen 18/12/09Spectroscopy of Fluid Interfaces31 Determination of spectra of unknown component H. Morgner*, J. Oberbrodhage, J. of Elec. Spec. and Rel. Phen. 87 (1997) 9-18

32  Percentage contribution of each species is shown in the graph to the left 18/12/09Spectroscopy of Fluid Interfaces32 Determination of spectra of unknown component H. Morgner*, J. Oberbrodhage, J. of Elec. Spec. and Rel. Phen. 87 (1997) 9-18

33 18/12/09Spectroscopy of Fluid Interfaces33

34 Conclusion  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 18/12/09Spectroscopy of Fluid Interfaces34

35 THANK YOU for your attention 18/12/09Spectroscopy of Fluid Interfaces35

36 MEEM) Metastables Electron Emission Microscopy (MEEM)  Controlling Helium beam diameter difficult  Area from which electrons are abstracted can be controlled – spatial resolution  Surface electron can be mapped non-destructively 18/12/09Spectroscopy of Fluid Interfaces36 Harada et al*, Nature 372 (1994) 657-659


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