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Kinetics of Enzymatic Synthesis gives insight into different aspects of chemical reactions that are catalyzed by enzymes. This book is divided into two sections: ""Enzyme Kinetics"" and ""Enzymatic Synthesis"". The first section consists of two chapters with a halophilic enzyme kinetics and thermodynamic approach towards analyzing the influence of co-solvents on the Michaelis constants of enzyme-catalyzed reactions. The second section consists of three chapters. Production of isoamyl acetate using the enzymatic synthesis method between acetic anhydride and isoamyl alcohol by having enzyme Candida antarctica Lipase B as catalyst in a solvent-free system is discussed in the third chapter. The integrated scheme with the use of the filtrate from the pretreatment of the CS and the growth conditions of Pleurotus cystidiosus is studied in the fourth chapter. The last chapter of this section provides the conditions of the key parameters in microfluidic systems (residence times, flow rates, concentrations) applied for a sequential process from liquid/liquid extraction of LVV-h7.

Biochemistry. --- Enzyme kinetics. --- Enzymes --- Synthesis. --- Enzyme synthesis --- Dynamics, Enzyme --- Enzyme dynamics --- Kinetics, Enzyme --- Chemical kinetics --- Biological chemistry --- Chemical composition of organisms --- Organisms --- Physiological chemistry --- Biology --- Chemistry --- Medical sciences --- Kinetics --- Composition --- Life Sciences --- Genetics and Molecular Biology --- Biochemistry --- Enzymology

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State Estimation Strategies in Lithium-ion Battery Management Systems presents key technologies and methodologies in modeling and monitoring charge, energy, power and health of lithium-ion batteries. Sections introduce core state parameters of the lithium-ion battery, reviewing existing research and the significance of the prediction of core state parameters of the lithium-ion battery and analyzing the advantages and disadvantages of prediction methods of core state parameters. Characteristic analysis and aging characteristics are then discussed. Subsequent chapters elaborate, in detail, on modeling and parameter identification methods and advanced estimation techniques in different application scenarios.Offering a systematic approach supported by examples, process diagrams, flowcharts, algorithms, and other visual elements, this book is of interest to researchers, advanced students and scientists in energy storage, control, automation, electrical engineering, power systems, materials science and chemical engineering, as well as to engineers, R&D professionals, and other industry personnel.

Lithium ion batteries. --- Lithium ion batteries --- Mathematical models.

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Iron is one of the most common metal centers in bioinorganic chemistry. The many processes in which iron plays a part are governed by its electronic structure. Particularly, the different accessible oxidation and spin states can display distinct physical and chemical properties. In this regard, computational chemistry provides an invaluable tool for the study of the electronic structure of the different iron centers. However, not all the theoretical methods are equally precise or accurate. Furthermore, it is not always easy to discern which answer is the correct one whenever different methods are in conflict. The most often used methodology for this type of studies is density functional theory, but its accuracy for the description of transition metal centers is not always consistent, especially when studying spin-state energetics. Ab initio (or wavefunction) methods can sometimes be more accurate, but they tend to be much more computationally expensive, and only applicable to small or medium-sized systems.In this thesis we will explore the accuracy of different wavefunction and density functional methods. The systems that we have studied are related to iron sites of biological importance, such as non-heme high-valent iron centers or iron-sulfur clusters. We have found limitations in some of the wavefunction methods, and further study is needed to understand the reasons behind these limitations and in order to improve the methods. We also show how composite multireference methods that have a balanced treatment of electron correlation provide a description in best agreement with experimental evidence. With respect to the density functional methods we have developed metrics to assess their sensitivity to small changes in the density. These metrics show that some biologically important iron-sulfur clusters, such as the iron molybdenum cofactor of nitrogenase, are extremely sensitive to small changes in the density, which stresses the need for better, consistently accurate, density functionals.

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