This book is about the development of knowledge-based, and related, expert systems in chemistry and toxicology. It shows how computers can work with qualitative information where precise numerical methods are not satisfactory.

This new edition has been thoroughly revised and updated to reflect the advances in using knowledge-based expert systems for chemistry.

Expert systems allow scientists to access, manage, and apply data and specialized knowledge from various disciplines to their own research. Expert Systems in Chemistry Research explains the general scientific basis and computational principles behind expert systems and demonstrates how they can improve the efficiency of scientific workflows

Food Chemical Risk Analysis provides an introduction to the sciences of food chemistry and risk analysis and demonstrates how the potential hazards associated with food chemicals can be assessed and managed. Food scares are never far from the news and particular attention is therefore focused on the consumer perception of risk and risk communication. Leading international experts provide unique insights in the future of food chemical risk analysis. Chapters on alternatives to animal testing show how emerging methods offer the prospect of a more rational human-based approach to toxicity testing. Discussions about relative risks and protective factors highlight the possibility that risks from food can be over-estimated and approaches to avoid such risks are proposed. The science of risk management is presented as more than just a method for translating science into policy by demonstrating how social, psychological, economic ethical and other factors can, and should be taken into account. The book makes it clear that if risk communication is to be effective, an integrated approach to risk analysis must be adopted.

Various emerging techniques for automating intelligent functions in the laboratory are described in this book. Explanations on how systems work are given and possible application areas are suggested. The main part of the book is devoted to providing data which will enable the reader to develop and test his own systems. The emphasis is on expert systems; however, promising developments such as self-adaptive systems, neural networks and genetic algorithms are also described. The book has been written by chemists with a great deal of practical experience in developing and testing intelligent software, and therefore offers first-hand knowledge. Laboratory staff and managers confronted with commercial intelligent software will find information on the functioning, possibilities and limitations thereof, enabling them to select and use modern software in an optimum fashion. Finally, computer scientists and information scientists will find a wealth of data on the application of contemporary artificial intelligence techniques.

Written chemical formulas, such as C2H6O, can tell us the constituent atoms a molecule contains but they cannot differentiate between the possible geometrical arrangements (isomers) of these models. Yet the chemical properties of different isomers can vary hugely. Therefore, to understand the world of chemistry we need to ask what kind of isomers can be produced from a given atomic composition, how are isomers converted into each other, how do they decompose into smaller pieces, and how can they be made from smaller pieces? The answers to these questions will help us to discover new chemistry and new molecules. A potential energy surface (PES) describes a system, such as a molecule, based on geometrical parameters. The mathematical properties of the PES can be used to calculate probable isomer structures as well as how they are formed and how they might behave. Exploration on Quantum Chemical Potential Energy Surfaces focuses on the PES search based on quantum chemical calculations. It describes how to explore the chemical world on PES, discusses fundamental methods and specific techniques developed for efficient exploration on PES, and demonstrates several examples of the PES search for chemical structures and reaction routes.

This document presents principles and helpful guides for validating (Q)SAR technology for a variety of applications.

TRAC: Trends in Analytical Chemistry, Volume 11 presents relevant topics in global analytical chemistry research. This book discusses the fundamental principle of competitive immunoassays. Organized into 27 chapters, this volume begins with an overview of the general and important contributions relating to the presentation of forensic evidence to courts of law. This text then discusses the importance of the analysis of scanned measuring quantities. Other chapters consider the advantages as well as the drawbacks of coupled chromatographic methods. This book discusses as well the status of analytical chemistry within the broader scientific arena as a practical rather than fundamentally oriented discipline. The final chapter deals with the properly functioning process control system in manufacturing insulin by reversed-phase high-performance liquid chromatography (RP–HPLC). This book is a valuable resource for analytical, organic, clinical, and regulatory chemists. Electrochemists, scientists, students, engineers, researcher workers, and other practitioners will also find this book extremely useful.

This text is primarily intended for readers who have some background in chemistry and who wish to find out more about the ways in which computers and electronics are influencing the techniques of observing chemical systems, the acquisition of data, its storage, and its transmission from one location to another. Many important concepts - such as interfacing, data collection, data bases, information services and computer networks - are covered in an easily assimilated and comprehensive way.

Artificial intelligence (AI) is the part of computer science concerned with designing intelligent computer systems (systems that exhibit characteristics we associate with intelligence in human behavior). This book is the first published textbook of AI in chemical engineering, and provides broad and in-depth coverage of AI programming, AI principles, expert systems, and neural networks in chemical engineering. This book introduces the computational means and methodologies that are used to enable computers to perform intelligent engineering tasks. A key goal is to move beyond the principles of AI into its applications in chemical engineering. After reading this book, a chemical engineer will have a firm grounding in AI, know what chemical engineering applications of AI exist today, and understand the current challenges facing AI in engineering. - Allows the reader to learn AI quickly using inexpensive personal computers - Contains a large number of illustrative examples, simple exercises, and complex practice problems and solutions - Includes a computer diskette for an illustrated case study - Demonstrates an expert system for separation synthesis (EXSEP) - Presents a detailed review of published literature on expert systems and neural networks in chemical engineering