Removal of the 1st order rayleigh scatter effect
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Removal of the 1st order Rayleigh scatter effect. Åsmund Rinnan. Introduction Treating scatter Revelation A step back Good reasons Model scatter Conclusion. Fluorescence - EEM. Excitation. Emission. Introduction Treating scatter Revelation A step back Good reasons Model scatter

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Removal of the 1st order Rayleigh scatter effect

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Removal of the 1st order rayleigh scatter effect

Removal of the 1st order Rayleigh scatter effect

Åsmund Rinnan


Fluorescence eem

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Fluorescence - EEM

Excitation

Emission


Parafac

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

PARAFAC

An extension from PCA

X is the EEM

a are the scores

b are the emissions

c are the excitations

E is the residual


Light scatter in fluorescence

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Light scatter in Fluorescence

1st order Rayleigh

Raman

2nd orderRayleigh

Excitation

Emission


Why is this a problem

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Why is this a problem?

X

X


Eem s with analytes

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

EEM’s with analytes


Ways of treating scatter

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Ways of treating scatter

  • Cut off and insert missing

  • Subtraction of standard

  • Weights

  • Modeling of Rayleigh


Subtraction of standard

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Subtraction of standard

It is not always possible with a standard


Why isn t one method enough

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Why isn’t onemethod enough!?

  • The data presented so far is a bit simple  Sugar data

1st order Rayleigh

Emission

Excitation


Cutting off inserting zeros

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Cutting off – inserting zeros

Emission loadings

Excitation loadings


Weighting miles

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Weighting - MILES

Emission loadings

Excitation loadings


So now everybody says

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

So now everybody says

  • We need a new model to take care of this

  • Hold your horses (a bit longer)


Band of missing values

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Band of missing values


Using a band of missing values hard weights

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Using a band of missing valuesHard weights

Emission loadings

Excitation loadings


Using a band of missing values miles weights

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Using a band of missing valuesMILES weights

Emission loadings

Excitation loadings


Another method why why why

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Another method?Why, why, why?

  • The Rayleigh scatter width has to be estimated quite accurately

  • The band width of missing data should also be correct

  • What about an automatic method of removing the Rayleigh scatter, that was not so prone to the estimation of the width of the Rayleigh scatter?

  • Modeling the Rayleigh is the answer!


Ways of modeling rayleigh

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Ways of modeling Rayleigh

  • Rasmus has tested a Gauss-Lorentz curve fitting method


Modeling rayleigh

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Modeling Rayleigh


Fancy doesn t mean good

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Fancy doesn’t mean good


With constraints even better

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

With constraints even better

Emission loadings

Excitation loadings


Conclusion

Introduction

Treating scatter

Revelation

A step back

Good reasons

Model scatter

Conclusion

Conclusion

  • Modeling is less sensitive to the estimated Rayleigh peak

  • Give good models, even without constraints or other modifications of the data (band of missing values)

  • The shifting method is relatively fast


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