Wesley Johnson – författare

Precious Metals Analysis: From Fire Assay to Spectrometry outlines the advances and innovations in analysis of precious metals over the past three decades, focusing on both established fire assaying techniques and the most sophisticated spectroscopic analysis techniques. This book covers both the fundamentals of these techniques and provides strategies to define the analysis route of a specific sample most related to the reader’s individual research needs and target applications. This book is structured to provide comprehensive information about all areas of precious metals analysis, such as synthesis, characterization, recycling, and potential applications.The first three chapters cover the formalism of precious metals analysis, including historical context, sampling principles, techniques and details of mass measurement. The next four chapters build on these fundamentals to delve into the complexities of widely used and recognised methodologies of precious metals analysis, such as crucible fusion dire assay, NiS fusion, cupellation for crucible fusion and bullion, inquartation and parting, bullion fire assay. Chapters eight and nine explain the specifics of sample preparation, dissolution and dilution and the ways these can be used in wet chemical methods of multiple types of previous metals. Chapters ten to twelve outline the principles of qualitative analysis, covering multiple spectroscopic and separation techniques, collection methods and spectrometric determination and statistical analyses. Finally, the concluding chapters of this book cover best practice to ensure readers are equipped with information and troubleshooting for common analytical errors, method validation, quality control, assay costing, automation, and data management. This book will be an invaluable resource to analytical chemists and metallurgists working with these techniques. Precious Metals Analysis will also be extremely useful for any specialists interested in the study, applications, extraction, and recycling of precious metals, such as assayers, previous metal refiners and fabricators, geologists, geochemists, materials scientists, materials engineers, and chemical engineers.The book also outlines specific precious metals and includes chapters on special topics such as coarse gold in ore samples; it will therefore also be of significant interest to groups active in the precious metals business, such as precious metal traders, scrap dealers, jewellers, and waste materials recyclers. There is a final special topic chapter on environmental sampling, so this book will also be relevant for researchers and academics interested in environmental testing and monitoring research.Practical guide to the most used and robust analytical approaches for those carrying out precious metals analysis, whether it be on ore samples or the analysis of ultra-high purity precious metals and everything in betweenDesigned to be a resource for all participants in the precious metals industry, from exploration to mining, to refining, fabrication and recycling and will serve as an aid to training a new generation of fire assayers and precious metals analystsCover all types of precious metals, providing a deeper knowledge about their analysis, extraction, and recycling as well as characterization using various routine and advanced techniquesIncludes both the fundamentals of these techniques and provides strategies to define the analysis route of a specific sample most related to the reader’s individual research needs and target applications Outlines best practices for precious metals analysis including, method validation, quality control, sampling techniques and quantitative statistical analysis, automation, and data management

Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, and the need for scientists and statisticians to collaborate in analyzing data. The WinBUGS code provided offers a convenient platform to model and analyze a wide range of data.The first five chapters of the book contain core material that spans basic Bayesian ideas, calculations, and inference, including modeling one and two sample data from traditional sampling models. The text then covers Monte Carlo methods, such as Markov chain Monte Carlo (MCMC) simulation. After discussing linear structures in regression, it presents binomial regression, normal regression, analysis of variance, and Poisson regression, before extending these methods to handle correlated data. The authors also examine survival analysis and binary diagnostic testing. A complementary chapter on diagnostic testing for continuous outcomes is available on the book’s website. The last chapter on nonparametric inference explores density estimation and flexible regression modeling of mean functions.The appropriate statistical analysis of data involves a collaborative effort between scientists and statisticians. Exemplifying this approach, Bayesian Ideas and Data Analysis focuses on the necessary tools and concepts for modeling and analyzing scientific data.Data sets and codes are provided on a supplemental website.

Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, and the need for scientists and statisticians to col