Design and Optimization in Organic Synthesis

Data Handling in Science and Technology

Book 8
Elsevier
Free sample

This is the first general textbook on experimental design and optimization in organic synthesis. The book presents a unified methodology for carrying out systematic studies when the objective is to develop efficient and optimum synthetic methods. Strategies are included both for exploring the experimental conditions and for systematic studies of entire reaction systems (substrates, reagent(s) and solvents). The methodology is based on multivariate statistical techniques.


The following topics are treated in depth: classical two-level designs for screening experiments, gradient methods (steepest ascent, simplex methods) as well as response surface techniques for optimization, principal components analysis and PLS modelling.


The book is intended as a hands-on text for chemists and engineers engaged in developing synthetic methods in industrial research, e.g. in fine chemicals and pharmaceuticals production, as well as for advanced undergraduate students, graduate students, and researchers in an academic environment.

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Additional Information

Publisher
Elsevier
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Published on
Nov 21, 1991
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Pages
552
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ISBN
9780080868356
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Language
English
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Genres
Science / Chemistry / Organic
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Content Protection
This content is DRM protected.
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Available on Android devices
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Eligible for Family Library

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Although sampling errors inevitably lead to analytical errors, the importance of sampling is often overlooked. The main purpose of this book is to enable the reader to identify every possible source of sampling error in order to derive practical rules to (a) completely suppress avoidable errors, and (b) minimise and estimate the effect of unavoidable errors. In short, the degree of representativeness of the sample can be known by applying these rules.


The scope covers the derivation of theories of probabilistic sampling and of bed-blending from a complete theory of heterogeneity which is based on an original, very thorough, qualitative and quantitative analysis of the concepts of homogeneity and heterogeneity. All sampling errors result from the existence of one form or another of heterogeneity. Sampling theory is derived from the theory of heterogeneity by application of a probabilistic operator to a material whose heterogeneity has been characterized either by a simple scalar (a variance: zero-dimensional batches) or by a function (a variogram: one-dimensional batches). A theory of bed-blending (one-dimensional homogenizing) is then easily derived from the sampling theory.


The book should be of interest to all analysts and to those dealing with quality, process control and monitoring, either for technical or for commercial purposes, and mineral processing.


Although this book is primarily aimed at graduates, large portions of it are suitable for teaching sampling theory to undergraduates as it contains many practical examples provided by the author's 30-year experience as an international consultant. The book also contains useful source material for short courses in Industry.

Now available is the second edition of a book which has been described as "...an exceptionally lucid, easy-to-read presentation... would be an excellent addition to the collection of every analytical chemist. I recommend it with great enthusiasm." (Analytical Chemistry)

N.R. Draper reviewed the first edition in Publication of the International Statistical Institute "...discussion is careful, sensible, amicable, and modern and can be recommended for the intended readership."

The scope of the first edition has been revised, enlarged and expanded. Approximately 30% of the text is new. The book first introduces the reader to the fundamentals of experimental design. Systems theory, response surface concepts, and basic statistics serve as a basis for the further development of matrix least squares and hypothesis testing. The effects of different experimental designs and different models on the variance-covariance matrix and on the analysis of variance (ANOVA) are extensively discussed. Applications and advanced topics (such as confidence bands, rotatability, and confounding) complete the text. Numerous worked examples are presented.

The clear and practical approach adopted by the authors makes the book applicable to a wide audience. It will appeal particularly to those with a practical need (scientists, engineers, managers, research workers) who have completed their formal education but who still need to know efficient ways of carrying out experiments. It will also be an ideal text for advanced undergraduate and graduate students following courses in chemometrics, data acquisition and treatment, and design of experiments.

Although sampling errors inevitably lead to analytical errors, the importance of sampling is often overlooked. The main purpose of this book is to enable the reader to identify every possible source of sampling error in order to derive practical rules to (a) completely suppress avoidable errors, and (b) minimise and estimate the effect of unavoidable errors. In short, the degree of representativeness of the sample can be known by applying these rules.


The scope covers the derivation of theories of probabilistic sampling and of bed-blending from a complete theory of heterogeneity which is based on an original, very thorough, qualitative and quantitative analysis of the concepts of homogeneity and heterogeneity. All sampling errors result from the existence of one form or another of heterogeneity. Sampling theory is derived from the theory of heterogeneity by application of a probabilistic operator to a material whose heterogeneity has been characterized either by a simple scalar (a variance: zero-dimensional batches) or by a function (a variogram: one-dimensional batches). A theory of bed-blending (one-dimensional homogenizing) is then easily derived from the sampling theory.


The book should be of interest to all analysts and to those dealing with quality, process control and monitoring, either for technical or for commercial purposes, and mineral processing.


Although this book is primarily aimed at graduates, large portions of it are suitable for teaching sampling theory to undergraduates as it contains many practical examples provided by the author's 30-year experience as an international consultant. The book also contains useful source material for short courses in Industry.

Now available is the second edition of a book which has been described as "...an exceptionally lucid, easy-to-read presentation... would be an excellent addition to the collection of every analytical chemist. I recommend it with great enthusiasm." (Analytical Chemistry)

N.R. Draper reviewed the first edition in Publication of the International Statistical Institute "...discussion is careful, sensible, amicable, and modern and can be recommended for the intended readership."

The scope of the first edition has been revised, enlarged and expanded. Approximately 30% of the text is new. The book first introduces the reader to the fundamentals of experimental design. Systems theory, response surface concepts, and basic statistics serve as a basis for the further development of matrix least squares and hypothesis testing. The effects of different experimental designs and different models on the variance-covariance matrix and on the analysis of variance (ANOVA) are extensively discussed. Applications and advanced topics (such as confidence bands, rotatability, and confounding) complete the text. Numerous worked examples are presented.

The clear and practical approach adopted by the authors makes the book applicable to a wide audience. It will appeal particularly to those with a practical need (scientists, engineers, managers, research workers) who have completed their formal education but who still need to know efficient ways of carrying out experiments. It will also be an ideal text for advanced undergraduate and graduate students following courses in chemometrics, data acquisition and treatment, and design of experiments.

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