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# Practical Three-Way Calibration

- 1st Edition - March 15, 2014
- Authors: Alejandro Olivieri, Graciela M. Escandar
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 4 1 0 4 0 8 - 2
- eBook ISBN:9 7 8 - 0 - 1 2 - 4 1 0 4 5 4 - 9

Practical Three-Way Calibration is an introductory-level guide to the complex field of analytical calibration with three-way instrumental data. With minimal use of mathemati… Read more

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Request a sales quote*Practical Three-Way Calibration* is an introductory-level guide to the complex field of analytical calibration with three-way instrumental data. With minimal use of mathematical/statistical expressions, it walks the reader through the analytical methodologies with helpful images and step-by-step explanations. Unlike other books on the subject, there is no need for prior programming experience and no need to learn programming languages. Easy-to-use graphical interfaces and intuitive descriptions of mathematical and statistical concepts make three-way calibration methodologies accessible to analytical chemists and scientists in a wide range of disciplines in industry and academia.

- Numerous detailed examples of slowly increasing complexity
- Exposure to several different data sets and techniques through figures and diagrams
- Computer program screenshots for easy learning without prior knowledge of programming languages
- Minimal use of mathematical/statistical expressions

Chemists; chemical engineers; pharmacists; environmental, forensics, atmospheric, and life scientists; graduate level students in these disciplines

- Dedication
- Preface
- Foreword
- Acknowledgments
- Chapter 1. Calibration Scenarios
- 1.1. Calibration
- 1.2. Univariate calibration
- 1.3. Multivariate calibration
- 1.4. Nomenclature for data and calibrations
- 1.5. Nomenclature for constituents and samples
- 1.6. Multiway calibration
- 1.7. Why multiway calibration?
- 1.8. Analytical advantages

- Chapter 2. Data Properties
- 2.1. Data properties
- 2.2. Bilinear data
- 2.3. Normalization and concentration effects
- 2.4. A word of caution on bilinearity
- 2.5. Nonbilinear data
- 2.6. Trilinear data
- 2.7. Nontrilinear data
- 2.8. Transforming three-way data into matrix data
- 2.9. Normalization and concentration effects
- 2.10. Classification of three-way data
- 2.11. Importance of classifying three-way data

- Chapter 3. Experimental Three-way/Second-order Data
- 3.1. Generation of three-way data
- 3.2. Matrix fluorescence spectroscopy
- 3.3. Chromatography with spectral detection
- Other second-order instrumental data
- 3.5. Data organization in files
- 3.6. Samples for calibration and validation

- Chapter 4. The MVC2 Software
- 4.1. Methods, models, algorithms and software
- 4.2. The MVC2 software
- 4.3. The MVC2 data examples
- 4.4. The EEFM_data example
- 4.5. Plotting EEFM_data matrices
- 4.6. The LCDAD_data example
- 4.7. Plotting LCDAD_data matrices
- 4.8. Further MVC2 features

- Chapter 5. Parallel Factor Analysis: Trilinear Data
- 5.1. Trilinear modeling and decomposition
- 5.2. Uniqueness and the second-order advantage
- 5.3. Processing the EEFM_data example
- 5.4. PARAFAC analysis of a test sample
- 5.5. Estimating the number of components
- 5.6. Analyte quantitation in the test sample
- 5.7. Analysis of the remaining samples
- 5.8. Profiles for potential interferents
- 5.9. Further processing options
- 5.10. Multiple-sample processing
- 5.11. Concluding remarks
- 5.12. Homework 1
- 5.13. Homework 2

- Chapter 6. Analytical Figures of Merit
- 6.1. Definition of figure of merit
- 6.2. Importance of analytical figures of merit
- Sensitivity
- 6.4. Selectivity
- 6.5. Analytical sensitivity
- 6.6. Prediction uncertainty
- 6.7. Limit of detection
- 6.8. Limit of quantitation
- 6.9. The complete PARAFAC report
- 6.10. Final considerations

- Chapter 7. Parallel Factor Analysis: Nontrilinear Data of Type 1
- 7.1. An apparent contradiction
- 7.2. Description of the data set
- 7.3. PARAFAC study of a test sample
- 7.4. Increasing the number of PARAFAC components
- 7.5. Study of the remaining samples
- 7.6. Other separation data and what to do
- 7.7. A PARAFAC variant for chromatographic data
- 7.8. PARAFAC2 calibration with the LCDAD_data
- 7.9. Chromatographic alignment
- 7.10. Homework

- Chapter 8. Multivariate Curve Resolution–Alternating Least-Squares
- 8.1. Multivariate curve resolution–alternating least-squares
- 8.2. Estimating the number of components
- 8.3. MCR–ALS initialization
- 8.4. Constraints
- MCR–ALS analysis of the LCDAD_data set
- 8.6. Analyte prediction in the test samples
- 8.7. Analyte prediction in all test samples simultaneously
- 8.8. Analytical figures of merit
- 8.9. Conclusion
- 8.10. Homework 1
- 8.11. Homework 2

- Chapter 9. Partial Least-Squares with Residual Bilinearization
- 9.1. Introduction
- 9.2. Unfolded partial least-squares
- 9.3. Estimating the number of calibration components
- 9.4. Residual bilinearization
- 9.5. The EEFM_data set: cross-validation
- 9.6. The EEFM_data set: RBL and prediction
- 9.7. Analytical figures of merit
- 9.8. The LCDAD_data set
- 9.9. The EEFM_IF_data set
- 9.10. U-PLS calibration in the EEFM_IF_data set
- 9.11. RBL in the EEFM_IF_data set
- 9.12. Other RBL methodologies
- 9.13. Other Nontrilinear Type 2 data
- 9.14. The Cinderella type 3 data
- 9.15. Conclusion
- 9.16. Homework 1
- 9.17. Homework 2
- 9.18. Homework 3

- Chapter 10. Three-way/Second-order Standard Addition
- 10.1. Why standard addition?
- 10.2. The EEFM_SA example
- 10.3. Processing the EEFM_SA data set with PARAFAC
- 10.4. Processing the EEFM_SA data set with MCR–ALS
- 10.5. Can the EEFM_SA data set be processed with U-PLS/RBL?

- Chapter 11. Third-order/Four-way Calibration and Beyond
- 11.1. Third-order/four-way data
- 11.2. Generation of third-order/four-way data
- Classification of third-order/four-way data
- 11.4. Algorithms
- 11.5. Data points in each mode
- 11.6. Fourth-order/five-way data
- 11.7. Figures of merit
- 11.8. Further higher-order advantages

- Chapter 12. Application Example: PARAFAC
- 12.1. Trilinear data
- 12.2. What algorithm should be chosen?
- 12.3. A literature EEFM example
- 12.4. How was the whole experiment designed?
- 12.5. How were the calibration concentrations chosen?
- 12.6. How were the validation concentrations chosen?
- 12.7. How were the wavelength ranges chosen?
- 12.8. PARAFAC processing using MVC2: validation samples
- 12.9. What happens for a smaller number of components?
- 12.10. What happens for a larger number of components?
- 12.11. Analyte prediction
- 12.12. Why analyzing test samples?
- 12.13. PARAFAC processing using MVC2: test samples
- 12.14. Why analyzing real samples?

- Chapter 13. Application Example: MCR–ALS
- 13.1. Nontrilinear data of Type 1
- 13.2. How to solve this problem?
- 13.3. Why coupling multivariate calibration to a separative method?
- 13.4. A literature example
- 13.5. Which are the difficulties of aligning chromatographic bands in this complex system?
- 13.6. What algorithm should be chosen?
- 13.7. How was the whole experiment designed?
- 13.8. Preparing the calibration and validation sets
- 13.9. How were the validation concentrations chosen?
- 13.10. How were the measuring ranges selected?
- 13.11. MCR–ALS processing using MVC2: validation samples
- 13.12. Why test samples should be analyzed?
- 13.13. MCR–ALS processing using MVC2: test samples
- 13.14. Analysis of real samples
- 13.15. Conclusion

- Chapter 14. Application Example: U–PLS/RBL
- 14.1. Nontrilinear data of Type 2
- 14.2. How to solve this problem?
- 14.3. What algorithm should be chosen?
- 14.4. An experimental literature example
- 14.5. How was the whole experiment designed?
- 14.6. Preparing the calibration and validation sets
- 14.7. How to choose the wavelength ranges?
- 14.8. U-PLS processing using MVC2: validation samples
- 14.9. Analysis of samples with potential interferences
- 14.10. Analysis of real samples
- 14.11. Conclusion

- Chapter 15. Solutions to Homework
- Homework to Chapter 5
- Homework to Chapter 7
- Homework to Chapter 8
- Homework to Chapter 9
- 15.5. Conclusion

- Index

- No. of pages: 330
- Language: English
- Edition: 1
- Published: March 15, 2014
- Imprint: Elsevier
- Hardback ISBN: 9780124104082
- eBook ISBN: 9780124104549

AO

### Alejandro Olivieri

GE

### Graciela M. Escandar

*Practical Three-Way Calibration*on ScienceDirect