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Design and Optimization in Organic Synthesis: Second Revised and Enlarged Edition, Volume 24 [Kõva köide]

(EISLAB, Luleå University of Technology, Luleå, Sweden), (University of Tromsoe, Tromsoe, Norway)
  • Formaat: Hardback, 596 pages, kõrgus x laius: 240x165 mm, kaal: 1230 g
  • Sari: Data Handling in Science and Technology
  • Ilmumisaeg: 08-Apr-2005
  • Kirjastus: Elsevier Science Ltd
  • ISBN-10: 0444515275
  • ISBN-13: 9780444515278
Teised raamatud teemal:
Design and Optimization in Organic Synthesis: Second Revised and Enlarged Edition, Volume 24Suurem pilt
  • Formaat: Hardback, 596 pages, kõrgus x laius: 240x165 mm, kaal: 1230 g
  • Sari: Data Handling in Science and Technology
  • Ilmumisaeg: 08-Apr-2005
  • Kirjastus: Elsevier Science Ltd
  • ISBN-10: 0444515275
  • ISBN-13: 9780444515278
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780444515278.html
Märksõnad:
Revised, and updated Design and Optimization in Organic Synthesis presents strategies to explore experimental conditions and methodologies for systematic studies of entire reaction systems (substrates, reagent(s), catalyst(s), and solvents). Chemical phenomena are not usually the result of a single factor and this book describes how statistically designed methods can be used to analyse and evaluate synthetic procedures. The methodology is based on multivariate statistical techniques. The accompanying CD contains data tables and programmes. This book is essential reading for anyone working in process design and development in fine chemicals or the pharmaceutical industry, and is suitable for those with no experience in the field.

* Contains recalculated models and redrawn figures, as well as new chapters on for example, the design of combinatorial libraries
* Presents strategies to explore experimental conditions and methodologies
* Enables the analysis and prediction of the best synthetic procedures

Revised, and updated Design and Optimization in Organic Synthesis presents strategies to explore experimental conditions and methodologies for systematic studies of entire reaction systems (substrates, reagent(s), catalyst(s), and solvents). Chemical phenomena are not usually the result of a single factor and this book describes how statistically designed methods can be used to analyse and evaluate synthetic procedures. The methodology is based on multivariate statistical techniques. The accompanying CD contains data tables and programmes. This book is essential reading for anyone working in process design and development in fine chemicals or the pharmaceutical industry, and is suitable for those with no experience in the field.

* Contains recalculated models and redrawn figures, as well as new chapters on for example, the design of combinatorial libraries
* Presents strategies to explore experimental conditions and methodologies
* Enables the analysis and prediction of the best synthetic procedures

Arvustused

"This is a welcome re-issue for a modern classic of the organic chemistry literature. The author presents a revised and enlarged edition, incorporating some fresh material, updated references, and novel strategies. I would urge all organic chemists to read this book and become acquainted with these valuable tools. Provides methods by which good chemists will be able to do even better chemistry. --Derek Robinson, ORGANIC PROCESS RESEARCH AND DEVELOPMENT, 2005

Muu info

A revised and updated second edition to the only book on Design and Optimization in Organic Synthesis
CHAPTER 1: INTRODUCTION: STRATEGIES ON DIFFERENT LEVELS IN ORGANIC SYNTHESIS 1(14)
1.1 The target
2(1)
1.2 The synthetic path
3(1)
1.3 The synthetic reaction
4(3)
1.4 Strategies for elaborating synthetic reactions
7(1)
1.5 Theme and variations
8(7)
CHAPTER 2: EXPERIMENTAL STUDY OF REACTION CONDITIONS. INITIAL REMARKS 15(12)
2.1 Organic synthesis and experimental design
15(1)
2.2 How to approach the problem
16(2)
2.3 Concretisation of the problem
18(2)
2.4 Screening and optimisation
20(3)
2.5 When to use multivariate designs?
23(4)
CHAPTER 3: MODELS AS TOOLS 27(40)
3.1 Synthetic chemistry and quantitative models
28(1)
3.2 Local models by Taylor expansions of the response function
29(10)
3.3 Initial aspects on modelling
39(4)
3.4 Modelling
43(11)
3.5 Significance of estimated model parameters
54(11)
3A Least squares fit of response surface models
65(2)
CHAPTER 4: GENERAL OUTLINE OF SCREENING EXPERIMENTS 67(20)
4.1 Some initial questions and comments
67(1)
4.2 Steps to be taken in a screening experiment
68(13)
4.3 Example: Synthesis of 1,4-dibromobenzene
81(6)
CHAPTER 5: TWO-LEVEL FACTORIAL DESIGNS 87(32)
5.1 Introductory remarks
87(2)
5.2 Different representations of factorial designs
89(5)
5.3 Generalisation to any number of factors
94(7)
5.4 Examples of two-level factorial designs
101(9)
5.5 Quality of model parameters
110(4)
5.6 Suggestions for further reading
114(5)
CHAPTER 6: TWO-LEVEL FRACTIONAL FACTORIAL DESIGNS 119(50)
6.1 Introductory remarks
119(1)
6.2 How to construct a fractional factorial design
120(3)
6.3 What is lost by using fractional factorial designs
123(6)
6.4 Example: Synthesis of a semicarbazone
129(6)
6.5 How to separate confounded effects
135(7)
6.6 Normal probability plots
142(13)
6.7 Other uses of normal probability plots
155(4)
6.8 Running experiments in blocks
159(5)
6.9 All runs in a fractional factorial design are useful
164(5)
CHAPTER 7: OTHER DESIGNS FOR SCREENING EXPERIMENTS 169(26)
7.1 Redundancy can be expensive
169(1)
7.2 Plackett-Burman designs
169(3)
7.3 Screening by D-optimal designs
172(7)
7.4 Suggestions for further reading
179(4)
7A Confounding pattern in Plackett-Burman designs
183(3)
7B Algorithms for the construction of D-optimal designs
186(4)
7C Some comments on the "optimality" of a design
190(5)
CHAPTER 8: SUMMARY OF SCREENING EXPERIMENTS 195(6)
8.1 Objectives
195(1)
8.2 Steps to be taken in a screening experiment
196(5)
CHAPTER 9: OPTIMISATION 201(6)
9.1 The problem
201(1)
9.2 The methods
202(1)
9.3 The requisites
203(4)
CHAPTER 10: STEEPEST ASCENT 207(12)
10.1 Principles
207(9)
10.2 Advantages and disadvantages of steepest ascent
216(3)
CHAPTER 11: SIMPLEX METHODS 219(24)
11.1 A sequential technique
219(2)
11.2 How to use a simplex for optimisation
221(6)
11.3 The Basic simplex method
227(5)
11.4 Modified simplex methods
232(6)
11.5 A few comments on the choice of simplex method
238(1)
11.6 Suggestions for further reading
239(4)
CHAPTER 12: RESPONSE SURFACE METHODS 243(78)
12.1 Preliminaries
243(3)
12.2 Step-wise strategy by composite designs
246(6)
12.3 Validation of the model
252(4)
12.4 Optimum conditions
256(3)
12.5 Canonical analysis
259(18)
12.6 Visualisation by projections
277(3)
12.7 Other designs for quadratic models
280(9)
12.8 More than one response
289(11)
12.9 Links between theory and experiments
300(11)
12A Obtaining a diagonal dispersion matrix
311(3)
12B Transformation of response variables
314(7)
CHAPTER 13: REACTION KINETICS BY SEQUENTIAL RESPONSE SURFACE MODELLING 321(18)
13.1 Yield evolution and rates
321(1)
13.2 Outline of the principles
322(3)
13.3 Example: A rate model
325(4)
13.4 A real experiment: Williamson ether synthesis
329(5)
13.5 A note on statistics
334(1)
13.6 Comments
335(4)
CHAPTER 14: SUMMARY OF STRATEGIES FOR EXPLORING THE EXPERIMENTAL SPACE 339(4)
14.1 Benefits of a step-wise strategy
339(1)
14.2 Flow sheet to define a strategy
340(3)
CHAPTER 15: THE REACTION SPACE 343(8)
15.1 What is the reaction space?
343(2)
15.2 A design which varies more than one factor is necessary
345(1)
15.3 Interdependencies
345(6)
CHAPTER 16: PRINCIPAL PROPERTIES 351(52)
16.1 Molecular properties
351(4)
16.2 Geometrical description of PCA
355(10)
16.3 Mathematical description of PCA and FA
365(14)
16.4 Some general aspects on the use of PCA
379(4)
16.5 Some examples of principal properties in organic synthesis
383(8)
16.6 Summary
391(1)
16.7 Suggestions for further reading
392(5)
16A On factoring of matrices
397(3)
16B The NIPALS algorithm
400(3)
CHAPTER 17: STRATEGIES FOR THE SELECTION OF TEST SYSTEMS 403(22)
17.1 Selection of solvents by their principal properties
404(8)
17.2 Selection according to the principles of factorial design
412(1)
17.3 Example of experimental design in principal properties
413(8)
17.4 Conclusions
421(4)
CHAPTER 18: QUANTITATIVE RELATIONS: OBSERVED RESPONSES AND EXPERIMENTAL VARIATIONS 425(46)
18.1 The problem
425(1)
18.2 Multiple regression cannot always be used
426(9)
18.3 PLS
435(4)
18.4 Cross validation of the PLS model
439(2)
18.5 Plots from the PLS model
441(1)
18.6 Examples on the use of PLS modelling in organic synthesis
442(6)
18.7 Inverse PLS
448(12)
18.8 Conclusions
460(1)
18.9 Suggestions for further reading
460(5)
18A Reaction systems
465(6)
CHAPTER 19: EXPLORING DISCRETE VARIATIONS: NEAR-ORTHOGONAL EXPERIMENTS BY SINGULAR VALUE DECOMPOSITION 471(18)
19.1 Introduction
471(3)
19.2 Method
474(4)
19.3 An example: The Fischer indole synthesis
478(1)
19.4 Sequential experimentation
479(1)
19.5 Some comments
480(2)
19.6 A note on D-optimal designs
482(1)
19.7 Summary of the strategy
482(5)
19A Minimising Epsilon {epsilonTX†TX†epsilon}
487(2)
CHAPTER 20: OPTIMIZATION WHEN THERE ARE SEVERAL RESPONSES VARIABLES 489(20)
20.1 Introduction
489(1)
20.2 Response matrix
490(3)
20.3 Connecting the response space to the experimental space
493(10)
20.4 Types of problems
503(2)
20.5 Summary and some advice
505(4)
CHAPTER 21: A METHOD FOR DETERMINING SUITABLE ORDER OF INTRODUCING REAGENTS IN "ONE-POT" PROCEDURES 509(8)
21.1 The problem
509(1)
21.2 Strategy
510(2)
21.3 Example: Self-condensation of 3,3-dimethyl-2-butanone
512(1)
21.4 A note on "ad hoc" explanations
513(4)
CHAPTER 22: BOOKS, JOURNALS, AND COMPUTER PROGRAMS 517(10)
22.1 Books
517(2)
22.2 Journals
519(1)
22.3 Computer programs
519(8)
CHAPTER 23: CONCLUDING REMARKS 527(8)
23.1 Comments on statistics and chemistry
527(2)
23.2 Strategies for analysing synthetic reactions
529(6)
EPILOGUE 535(2)
APPENDIX A: MATRIX ALGEBRA 537(14)
A.1 Definitions
537(3)
A.2 Matrix operations
540(11)
APPENDIX B: STATISTICAL TABLES 551(11)
B.1 Table B1, t-distribution
551(1)
B.2 Tables B2-B4, F-distribution
552(1)
B.3 Sources
553(9)
INDEX 562