Assuming only background knowledge of algebra and elementary calculus, and access to a modern personal computer, Nonlinear Computer Modeling of Chemical and Biochemical Data presents the fundamental basis and procedures of data modeling by computer using nonlinear regression analysis. Bypassing the need for intermediary analytical stages, this method allows for rapid analysis of highly complex processes, thereby enabling reliable information to be extracted from raw experimental data.By far the greater part of the book is devoted to selected applications of computer modeling to various experiments used in chemical and biochemical research. The discussions include a short review of principles and models for each technique, examples of computer modeling for real and theoretical data sets, and examples from the literature specific to each instrumental technique.The book also offers detailed tutorial on how to construct suitable models and a score list of appropriate mathematics software packages.
Author(s): James F. Rusling, Thomas F. Kumosinski
Edition: 1
Publisher: Academic Press
Year: 1996
Language: English
Pages: 285
Front Cover......Page 1
Nonlinear Computer Modeling of Chemical and Biochemical Data......Page 4
Copyright Page......Page 5
Contents......Page 8
Preface......Page 14
Acknowledgments......Page 16
Part I: General Introduction to Regression Analysis......Page 18
A. What Is Nonlinear Modeling?......Page 20
B. Objectives of This Book......Page 22
References......Page 23
A. Linear Models......Page 24
B. Nonlinear Regression Analysis......Page 35
C. Sources of Mathematics Software Capable of Linear and Nonlinear Regression......Page 47
References......Page 48
A. Sources of Data and Background Contributions......Page 50
B. Examples of Model Types......Page 55
C. Finding the Best Models......Page 66
References......Page 71
A. Correlations and How to Minimize Them......Page 74
B. Avoiding Pitfalls in Convergence......Page 84
References......Page 89
Part II: Selected Applications......Page 92
A. Introduction......Page 94
References......Page 102
A. The Concept of Linked Functions......Page 104
B. Applications of Thermodynamic Linkage......Page 108
References......Page 132
A. Introduction......Page 134
B. Analysis of Spectra—Examples......Page 140
References......Page 150
A. Fundamentals of NMR Relaxation......Page 152
B. Applications from NMR in Solution......Page 154
C. Applications from NMR in the Solid State......Page 164
References......Page 168
A. Theoretical Considerations......Page 170
B. Applications......Page 173
References......Page 182
A. Sedimentation......Page 184
References......Page 192
A. General Characteristics of Voltammetry......Page 194
B. Steady State Voltammetry......Page 197
C. Cyclic Voltammetry......Page 213
D. Square Wave Voltammetry......Page 218
References......Page 221
A. Basic Principles......Page 224
B. Estimation of Diffusion Coefficients......Page 225
C. Surface Concentrations of Adsorbates from Double Potential Steps......Page 231
D. Rate Constant for Reaction of a Product of an Electrochemical Reaction......Page 234
References......Page 242
A. Considerations for Analyses of Overlapped Signals......Page 244
B. Automated Analysis of Data with an Unknown Number of Exponentials......Page 246
References......Page 260
A. Overlapped Chromatographic Peaks with Single-Channel Detection......Page 262
B. Multichannel Detection......Page 271
References......Page 276
Appendix I. Linear Regression Analysis......Page 278
Index......Page 282
