Mathematics for Enzyme Reaction Kinetics and Reactor Performance, 2 Volume Set – PDF

Mathematics for Enzyme Reaction Kinetics and Reactor Performance, (PDF) is the first set in an exceptional 11 volume-collection on Enzyme Reactor Engineering. This two volume-set relates especially to the wide mathematical background needed for systematic and rational simulation of both reaction kinetics and reactor performance, and to completely understand and capitalize on the modeling concepts developed. It accordingly reviews fundamental and useful concepts of Algebra (first volume), and Calculus and Statistics (second volume). A concise overview of such native algebraic entities as scalars, matrices, vectors, and determinants constitutes the starting point of the first volume; the key features of germane functions are then addressed. Vector operations proceed, followed by the calculation of determinants. Finally, exact methods for the solution of those algebraic equations – including sets of linear equations, are considered, in addition to numerical methods for utilization at large. The second volume starts with an introduction to fundamental concepts in calculus, i.e. limits, derivatives, differential equations and integrals; limits, along with continuity, are further expanded afterward, covering uni- and multivariate cases, along with classical theorems. After recovering the concept of differential and implementing it to generate (regular and partial) derivatives, the most vital rules of differentiation of functions, in implicit, explicit, and parametric form, are retrieved – along with the nuclear theorems supporting simpler manipulation thereof. The ebook then tackles strategies to optimize uni- and multivariate functions, before addressing integrals in both definite and indefinite forms. Next, the ebook emphasizes on the methods of solution of differential equations for practical applications, followed by analytical geometry and vector calculus. Concise coverage of statistics–including continuous probability functions, statistical descriptors, and statistical hypothesis testing, brings the second volume to a close.

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