Silicon Carbon 18650 Battery


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Silicon Anode Systems for Lithium-Ion Batteries


Silicon Anode Systems for Lithium-Ion Batteries

Author: Prashant N. Kumta

language: en

Publisher: Elsevier

Release Date: 2021-09-10


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Silicon Anode Systems for Lithium-Ion Batteries is an introduction to silicon anodes as an alternative to traditional graphite-based anodes. The book provides a comprehensive overview including abundance, system voltage, and capacity. It provides key insights into the basic challenges faced by the materials system such as new configurations and concepts for overcoming the expansion and contraction related problems. This book has been written for the practitioner, researcher or developer of commercial technologies. - Provides a thorough explanation of the advantages, challenge, materials science, and commercial prospects of silicon and related anode materials for lithium-ion batteries - Provides insights into practical issues including processing and performance of advanced Si-based materials in battery-relevant materials systems - Discusses suppressants in electrolytes to minimize adverse effects of solid electrolyte interphase (SEI) formation and safety limitations associated with this technology

Nanostructured Lithium-ion Battery Materials


Nanostructured Lithium-ion Battery Materials

Author: Sabu Thomas

language: en

Publisher: Elsevier

Release Date: 2024-10-17


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Nanostructured Lithium-ion Battery Materials: Synthesis and Applications provides a detailed overview of nanostructured materials for application in Li-ion batteries, supporting improvements in materials selection and battery performance. The book begins by presenting the fundamentals of Lithium-ion batteries, including electrochemistry and reaction mechanism, advantages and disadvantages of Li-ion batteries, and characterization methods. Subsequent sections provide in-depth coverage of a range of nanostructured materials as applied to cathodes, electrolytes, separators, and anodes. Finally, other key aspects are discussed, including industrial scale-up, safety, life cycle analysis, recycling, and future research trends.This is a valuable resource for researchers, faculty, and advanced students across nanotechnology, materials science, battery technology, energy storage, chemistry, applied physics, chemical engineering, and electrical engineering. In an industrial setting, this book will be of interest to scientists, engineers, and R&D professionals working with advanced materials for Li-ion batteries and other energy storage applications. - Introduces fundamental of Lithium-ion batteries, electrochemistry, and characterization methods - Offers in-depth information on nanostructured cathode, electrolyte, separator, and anode materials - Addresses lab to industry challenges, safety, lifecycle analysis, recycling, and future opportunities

Battery System Modeling


Battery System Modeling

Author: Shunli Wang

language: en

Publisher: Elsevier

Release Date: 2021-06-23


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Battery System Modeling provides advances on the modeling of lithium-ion batteries. Offering step-by-step explanations, the book systematically guides the reader through the modeling of state of charge estimation, energy prediction, power evaluation, health estimation, and active control strategies. Using applications alongside practical case studies, each chapter shows the reader how to use the modeling tools provided. Moreover, the chemistry and characteristics are described in detail, with algorithms provided in every chapter. Providing a technical reference on the design and application of Li-ion battery management systems, this book is an ideal reference for researchers involved in batteries and energy storage. Moreover, the step-by-step guidance and comprehensive introduction to the topic makes it accessible to audiences of all levels, from experienced engineers to graduates. - Explains how to model battery systems, including equivalent, electrical circuit and electrochemical nernst modeling - Includes comprehensive coverage of battery state estimation methods, including state of charge estimation, energy prediction, power evaluation and health estimation - Provides a dedicated chapter on active control strategies