Problem-Oriented Analytical Chemistry Driven by Chemometrics

Many analytical chemists dealing with complex, real-world problems face significant difficulties extracting information from their data. Problem-Oriented Analytical Chemistry Driven by Chemometrics provides a novel approach starting from case studies and allowing the analytical chemist to understand how sometimes seemingly impenetrable chemometrics techniques can be applied to the problems they want to solve. In many cases, solutions are available in the chemometrics arena but relevant books in that field are usually too technical and do not always focus on the 'general perspective' needed by the analyst when facing those complex tools. The contributions will focus on actual case studies of applications with examples of the results to be obtained and a clear description of which conditions need to be met for a given chemometric technique to be applicable with those different conditions/instruments. The first part of the book focuses on the optimization, acquisition, and processing of analytics. The second then looks at the qualitative and quantitative characterization of analytical instruments and material systems, before the final part displays how chemometric support can be provided for special analytical matters. Problem-Oriented Analytical Chemistry Driven by Chemometrics is written primarily to assist graduate and postdoc analytical chemists and early researchers, with applicability to industry too. The challenges addressed in this book are also highly relevant to adjacent fields using analytical techniques including food quality and safety, environmental studies, product authentication, and petrochemistry.

• Novel, problem-oriented approach to using chemometrics based on case studies
• The most common analytical techniques are considered through looking at case studies of application and how to get sound information from their signals
• Accessible perspective on chemometrics is provided, rather than simply presenting complex Mathematics and/or algorithms in an impenetrable manner