Quantitative iterative target transformation factor analysis

Journal of Chemometrics

Volumn 22, Issue 1, 2008, Pages 63-80

  Richards, Selena E ^a   Walmsley, Anthony D ^b  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF HULL   (United Kingdom)

Author keywords

Chemometrics; Multivariate curve resolution; NIR; Quantitative; Vinyl acetate process

Indexed keywords

FACTOR ANALYSIS; HIGH PERFORMANCE LIQUID CHROMATOGRAPHY; INFRARED DEVICES;

ALTERNATING LEAST SQUARES; CHEMOMETRICES; ITERATIVE TARGET TRANSFORMATION FACTOR ANALYSIS; MULTIVARIATE CURVE RESOLUTION; NEAR INFRARED; NEAR-INFRARED; QUANTITATIVE; SOLUTION SPACE; VINYL ACETATE PROCESS; VINYL ACETATES;

MULTIVARIANT ANALYSIS;

EID: 50549086569     PISSN: 08869383     EISSN: 1099128X     Source Type: Journal    
DOI: 10.1002/cem.1102     Document Type: Article

References (39)

1. Tauler R, Lacorte S, Barcelo D. Application of multivariate self-modeling curve resolution to the quantitation of trace levels of organophosphorus pesticides in natural waters from interlaboratory studies. J. Chromatogr. A 1996; 730: 177-183.
2. Bylund D, Danielsson R, Markides KE. Peak purity assessment in liquid chromatography-mass spectrometry. J. Chromatogr. A 2001; 915: 43-52.
3. De Braekeleer K, de Juan A, Massart DL. Purity assessment and resolution of tetracycline hydrochloride samples analysed using high-performance liquid chromatography with diode array detection. J. Chromatogr. A 1999; 832:67-86.
4. De Braekeleer K, De Maesschalck R, Hailey PA, Sharp DCA, Massart DL On-line application of the orthogonal projection approach (OPA) and the soft independent modelling of class analogy approach (SIMCA) for the detection of the end point of a polymorph conversion reaction by near infrared spectroscopy (NIR). Chemometr. Intell. Lab. Syst. 1999; 46: 103-116.
5. Gemperline PJ, Zhu M, Cash E, Walker DS. Chemometric characterization of batch reactions. Isa Trans. 1999; 38: 211-216.
6. Ma B, Gemperline PJ, Cash E, Bosserman M, Comas E. Characterizing batch reactions with in situ spectroscopic measurements, calorimetry and dynamic modeling. J. Chemometr. 2003; 17:470-479.
7. Richards S, Ropic M, Blackmond D, Walmsley A. Quantitative determination of the catalysed asymmetric transfer hydrogenation of l-methyl-6,7-dimethoxy-3, 4-dihydroisoquinoline using in situ FTIR and multivariate curve resolution. Anal. Chim. Acta 2004; 519:1-9.
8. Sasic S, Kita Y, Furukawa T, Watari M, Siesler HW, Ozaki Y. Monitoring the melt-extrusion transesterification of ethylene-vinylacetate copolymer by self-modeling curve resolution analysis of on-line near-infrared spectra. Analyst 2000; 125: 2315-2321.
9. de Juan A, Tauler R. Chemometrics applied to unravel multicomponent processes and mixtures - Revisiting latest trends in multivariate resolution. Anal. Chim. Acta 2003; 500: 195-210.
10. Jiang TH, Liang Y, Ozaki Y. Principles and methodologies in self-modeling curve resolution. Chemometr. Intell. Lab. Syst. 2004; 71: 1-12.
11. Gampp HL, Maeder M, Meyer CJ, Zuberbuhler AD. Calculation of Equilibrium-Constants from Multiwavelength Spectroscopic Data .3. Model-Free Analysis of Spectrophotometric and Electron-Spin-Resonance Titrations. Talanta 1985; 32: 1133-1139.
12. Maeder M. Evolving Factor-Analysis for the Resolution of Overlapping Chromatographic Peaks. Anal. Chem. 1987; 59 :527-530.
13. Keller HR, Massart DL. Peak Purity Control in Liquid-Chromatography with Photodiode-Array Detection by a Fixed Size Moving Window Evolving Factor-Analysis. Anal. Chim. Acta 1991; 246: 379-390.
14. Liang YZ, Kvalheim OM. Heuristic Evolving Latent Projections -Resolving Hyphenated Chromatographic Profiles by Component Stripping. Chemometr. Intell. Lab. Syst. 1993; 20: 115-125.
15. Kvalheim OM, Liang YZ. Heuristic Evolving Latent Projections -Resolving 2-Way Multicomponent Data.1. Selectivity, Latent-Projective Graph, Datascope, Local Rank, and Unique Resolution. Anal. Chem. 1992; 64: 936-946.
16. Liang YZ, Kvalheim OM, Keller HR, Massart DL, Kiechle P, Emi F. Heuristic Evolving Latent Projections - Resolving 2-Way Multi-component Data .2. Detection and Resolution of Minor Constituents. Anal. Chem. 1992; 64: 946-953.
17. Malinowski ER. Window Factor-Analysis - Theoretical Derivation and Application to Flow-Injection Analysis Data. J. Chemometr. 1992; 6: 29-40.
18. Manne R, Shen.H.L., Liang YZ. Subwindow factor analysis. Chemometrics and Intell. Lab. Syst. 1999; 45: 171-176.
19. Vandeginste BGM, Derks W, Kateman G. Multicomponent Self-Modeling Curve Resolution in High-Performance Liquid-Chromatography by Iterative Target Transformation Analysis. Anal. Chim. Acta 1985; 173: 253-264.
20. Gemperline PJ. A Priori Estimates of the Elution Profiles of the Pure Components in Overlapped Liquid-Chromatography Peaks Using Target Factor-Analysis. J. Inform. Comput. Sci. 1984; 24: 206-212.
21. Karjalainen EJ. The Spectrum Reconstruction Problem - Use of Alternating Regression for Unexpected Spectral Components in 2-Dimensional Spectroscopies. Chemometr. Intell. Lab. Syst. 1989; 7: 31-38.
22. Tauler R, Casassas E. Spectroscopic Resolution of Macromolecular Complexes Using Factor-Analysis - Cu(li)-Polyethyleneimine System. Chemometr. Intell. Lab. Syst. 1992; 14: 305-317.
23. Windig W, Guilment J. Interactive Self-Modeling Mixture Analysis. Anal. Chem. 1991; 63: 1425-1432.
24. Windig W. The Use of 2nd-Derivative Spectra for Pure-Variable Based Self-Modeling Mixture Analysis Techniques. Chemometr. Intell. Lab. Syst. 1994; 23: 71-86.
25. Windig W. Spectral data files for self-modeling curve resolution with examples using the Simplisma approach. Chemometr. Intell. Lab. Syst. 1997;36:3-16.
26. Windig W, Heckler CE, Agblevor FA, Evans RJ. Self-Modeling Mixture Analysis of Categorized Pyrolysis Mass-Spectral Data with the Simplisma Approach. Chemometr. Intell. Lab. Syst. 1992; 14: 195-207.
27. Windig W, Stephenson DA. Self-Modeling Mixture Analysis of 2nd-Derivative near-Infrared Spectral Data Using the Simplisma Approach. Anal. Chem. 1992; 64: 2735-2742.
28. De Braekeleer K, Massart DL Evaluation of the orthogonal projection approach (OPA) and the SIMPLISMA approach on the Windig standard spectral data sets. Chemometr. Intell. Lab. Syst. 1997; 39:127-141.
29. Sanchez FC, Toft J, vandenBogaert B. Massart DL Orthogonal projection approach applied to peak purity assessment. Anal. Chem. 1996;68:79-85.
30. Windig W, Antalek B, Lippert JL, Batonneau Y, Bremard C Combined use of conventional and second-derivative data in the SIMPLISMA self-modeling mixture analysis approach. Anal. Chem. 2002; 74: 1371-1379.
31. Windig W, Gallagher NB, Shaver JM, Wise BM. A new approach for interactive self-modeling mixture analysis. Chemometr. Intell. Lab. Syst. 2005; 77: 85-96.
32. Sanchez FC Massart DL Application of Simplisma for the Assessment of Peak Purity in Liquid-Chromatography with Diode-Array Detection. Anal. Chim. Acta 1994; 298: 331-339.
33. deJuan A, VanderHeyden Y, Tauler R, Massart DL Assessment of new constraints applied to the alternating least squares method. Anal. Chim. Acta 1997; 346: 307-318.
34. Tauler R, Juan Ad. http://www.ub.es/gesq/mcr/mcr.htm
35. Bro R, De Jong S. A fast non-negativity-constrained least squares algorithm. J. Chemometr. 1997; 11: 393-401.
36. Tauler R, Smilde A, Kowalski B. Selectivity, Local Rank, 3-Way Data-Analysis and Ambiguity in Multivariate Curve Resolution. J. Chemometr. 1995; 9: 31-58.
37. Bezemer E, Rutan SC Multivariate curve resolution with non-linear fitting of kinetic profiles. Chemometr. Intell. Lab. Syst. 2001; 59: 19-31.
38. de Juan A, Maeder M, Martinez M, Tauler R. Combining hard- and soft-modelling to solve kinetic problems. Chemometr. Intell. Lab. Syst. 2000; 54: 123-141.
39. Vandeginste BGM, Massart DL Buydens LMC Jong SD, Lewi PJ, Smeyers-Verbeke J. Data Handling in Science and Technology. Volume 20B. 1998; Elsevier Netherlands.