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This book offers an accessible introduction to application-oriented multivariate methods of data analysis and procedures that are highly beneficial to solving a variety of problems by using analytical chemistry and statistics. It presents a diverse selection of topics that include experimental designs applied for the optimisation of liquid chromatographic and capillary electrophoresis, variable selection in chemical data, calibration of the first order: data, algorithms, and analytical applications, characterisation of polyphenols from natural products using separation techniques coupled with chemometrics, detection of malignant tumors using FT-IR spectroscopy combined with chemometrics, guidelines in synthesis of new anticancer compounds, direct analysis of solid samples by spectroscopy and chromatographic techniques, application of data fusion in different levels with examples, and analysis of pharmaceutical and food products by various analytical techniques. This book helps thereader embrace the growing role of chemometrics in some of the latest research trends, such as characterisation of polyphenolic compounds in natural, pharmaceutical, and food products in analytical problems, such as classification and quantification using the multivariate calibration of the second order. This book also identifies several areas for future development and applications. The chapters are written by leading experts. Chemometrics: Methods, Applications, and New Research offers a reliable source of useful information in a style that is accessible to all levels of students, professionals, and researchers involved in analysing scientific data.
Die Mehrwegeanalyse ist eine moderne Methode der Datenanalyse, die sich in chemischen und industriellen Labors zunehmender Beliebtheit erfreut. Während etliche Werke auf dem Markt sind, die sich mit den mathematischen Grundlagen des Verfahrens beschäftigen, fehlte bisher eine speziell für den Chemiker geeignete praxisbezogene Einführung. "Multi-Way Analysis in Chemistry" schließt diese Lücke und bietet eine ideale Mischung aus theoretischen Hintergrundinformationen und chemischen Anwendungen.
Process analytical chemistry (PAC) can be defined as the technology of obtaining quantitative and qualitative information about a chemical process in order to control or optimise its performance. This highly practical book provides an up-to-date introduction to the field with a special emphasis placed on industrial processes. Edited by representatives from one of the world's leading chemical companies and centres of excellence for research into the subject, the book is written by a transatlantic team of authors who provide a global perspective.
Most chemists, whether they are biochemists, organic, analytical, pharmaceutical or clinical chemists and many pharmacists and biologists need to perform chemical analysis. Consequently, they are not only confronted with carrying out the actual analysis, but also with problems such as method selection, experimental design, optimization, calibration, data acquisition and handling, and statistics in order to obtain maximum relevant chemical information. In other words: they are confronted with chemometrics. This book on chemometrics, written by some of the leaders in the field, aims to provide a thorough, up-to-date introduction to this subject. The reader is given the opportunity to acquaint himself with the tools used in this discipline and the way in which they are applied. Some practical examples are given and the reader is shown how to select the appropriate tools in a given situation. As such the book provides the means to approach and solve analytical problems strategically and systematically, without the need for the reader to become a fully-fledged chemometrician. The authors' aim was to write a tutorial book which would be useful to readers at every level in this field.
This book is aimed at the large number of people who need to use chemometrics but do not wish to understand complex mathematics, therefore it offers a comprehensive examination of the field of chemometrics without overwhelming the reader with complex mathematics. * Includes five chapters that cover the basic principles of chemometrics analysis. * Provides two chapters on the use of Excel and MATLAB for chemometrics analysis. * Contains 70 worked problems so that readers can gain a practical understanding of the use of chemometrics.
Chemometrics is the chemical discipline that uses mathematical, statistical and other methods employing formal logic: to design or select optimal measurement procedures and experiments, and -- to provide maximum relevant chemical information by analysing chemical data. Being conceived as a branch of analytical chemistry, chemometrics now is a general approach. It extracts relevant information out of measured data, regardless of their origin: chemical, physical, biological, etc. Chemometrics has been applied in different areas, and most successfully in multivariate calibration, pattern recognition, classification and discriminant analysis, multivariate modelling, and monitoring of processes. The main chemometric principle is a concept of hidden data structures that can be found using methods of multivariate data analysis. These are the well-known statistic tools such as partial least squares (PLS), soft independent modelling of class analogy (SIMCA), principal-component regression (PCR), wavelet analysis, and many others. Current activities of chemometricians fall into two main categories: (1) development of new methods for manipulating multivariate data and (2) new applications of the known chemometric techniques in different areas such as environment control, food industry, agriculture, medicine, and engineering.
Chemometrics Explore chemometrics from basic statistics to the latest artificial intelligence and neural network developments in this new edition Chemometrics is an area of study combining chemistry and mathematics. It governs the interpretation of data generated by chemical analysis, and its growth as a subfield promises to streamline and revolutionize analytical chemistry. Chemometrics has long been the leading introductory textbook in this subject. Beginning with an introduction to the statistical-mathematical evaluation of chemical measurements, it leads readers through modern chemometric approaches in a pedagogically sound and highly readable style. Now fully updated to reflect the latest research and applications of this exciting discipline, it provides essential tools for a new generation of analytical chemists. Readers of the fourth edition of Chemometrics will also find: New or expanded treatment of subjects such as deep learning, ANNOVA simultaneous component analysis, instrumental data output, and more Detailed discussion of approaches to signal processing, design and optimization of experiments, pattern recognition and classification, and many other areas Balance of theoretical and practical knowledge to enable rapid application of key techniques Chemometrics is ideal for advanced students in chemistry, analytical chemistry, pharmaceutical chemistry, biochemistry, or related subjects, and as a useful reference for practicing researchers and laboratory professionals.
Chemometrics: Data Treatment and Applications demonstrates the best practices for treating real-world analytical instrument data and how to apply chemometrics to this data. Rather than focusing on the mathematical theory involved in chemometrics, this book is meant for the industrial chemist, and academics and advanced students that want to use chemometrics in practice. Case studies on several applications are presented. Unlike existing literature, this book focuses on best practices, practical realities, and challenges when treating data, rather than on the mathematical theory. It also provides basic information on chemometrics, several chapters on how to treat, and the best practices used to treat, data from different analytical instruments, as well as case studies and uses of chemometrics in different fields. The book is written primarily for analytic chemists as practitioners in analytical laboratories and other industries. It will also be useful to academics and graduate, masters and postdoc students chiefly working in analytical chemistry who want to improve the practical aspects of their research activities. Presents topical and important chapters for the most-used analytical instruments Focuses on practical issues in the implementation of chemometrics Examines advances in the application of chemometrics in several fields Includes frank perspectives on what works well for the data of a certain analytical instrument given the multiple choices of mathematical models and protocols that can be applied Covered protocols are heavily illustrated with case studies showing their potential use and the advances in chemometrics
A new, full-color, completely updated edition of the key practical guide to chemometrics This new edition of this practical guide on chemometrics, emphasizes the principles and applications behind the main ideas in the field using numerical and graphical examples, which can then be applied to a wide variety of problems in chemistry, biology, chemical engineering, and allied disciplines. Presented in full color, it features expansion of the principal component analysis, classification, multivariate evolutionary signal and statistical distributions sections, and new case studies in metabolomics, as well as extensive updates throughout. Aimed at the large number of users of chemometrics, it includes extensive worked problems and chapters explaining how to analyze datasets, in addition to updated descriptions of how to apply Excel and Matlab for chemometrics. Chemometrics: Data Driven Extraction for Science, Second Edition offers chapters covering: experimental design, signal processing, pattern recognition, calibration, and evolutionary data. The pattern recognition chapter from the first edition is divided into two separate ones: Principal Component Analysis/Cluster Analysis, and Classification. It also includes new descriptions of Alternating Least Squares (ALS) and Iterative Target Transformation Factor Analysis (ITTFA). Updated descriptions of wavelets and Bayesian methods are included. Includes updated chapters of the classic chemometric methods (e.g. experimental design, signal processing, etc.) Introduces metabolomics-type examples alongside those from analytical chemistry Features problems at the end of each chapter to illustrate the broad applicability of the methods in different fields Supplemented with data sets and solutions to the problems on a dedicated website, www.booksupport.wiley.com Chemometrics: Data Driven Extraction for Science, Second Edition is recommended for post-graduate students of chemometrics as well as applied scientists (e.g. chemists, biochemists, engineers, statisticians) working in all areas of data analysis.