Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. 2023rd edition NO-PA16APR2015-KAP.
EUR 190,49
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a comprehensive review of the latest modelling developments in flow batteries, as well as some new results and insights. Flow batteries have long been considered the most flexible answer to grid scale energy storage, and modelling is a key component in their development. Recent modelling has moved beyond macroscopic methods, towards mesoscopic and smaller scales to select materials and design components. This is important for both fundamental understanding and the design of new electrode, catalyst and electrolyte materials. There has also been a recent explosion in interest in machine learning for electrochemical energy technologies. The scope of the book includes these latest developments and is focused on advanced techniques, rather than traditional modelling paradigms. The aim of this book is to introduce these concepts and methods to flow battery researcher, but the book would have a much broader appeal since these methods also employed in other battery and fuel cell systems and far beyond. The methods will be described in detail (necessary fundamental material in Appendices). The book appeals to graduate students and researchers in academia/industry working in electrochemical systems, or those working in computational chemistry/machine learning wishing to seek new application areas.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 142,27
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore Aug 2024, 2024
ISBN 10: 9819925266 ISBN 13: 9789819925261
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 181,89
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a comprehensive review of the latest modelling developments in flow batteries, as well as some new results and insights. Flow batteries have long been considered the most flexible answer to grid scale energy storage, and modelling is a key component in their development. Recent modelling has moved beyond macroscopic methods, towards mesoscopic and smaller scales to select materials and design components. This is important for both fundamental understanding and the design of new electrode, catalyst and electrolyte materials. There has also been a recent explosion in interest in machine learning for electrochemical energy technologies. The scope of the book includes these latest developments and is focused on advanced techniques, rather than traditional modelling paradigms. The aim of this book is to introduce these concepts and methods to flow battery researcher, but the book would have a much broader appeal since these methods also employed in other battery and fuel cell systems and far beyond. The methods will be described in detail (necessary fundamental material in Appendices). The book appeals to graduate students and researchers in academia/industry working in electrochemical systems, or those working in computational chemistry/machine learning wishing to seek new application areas. 392 pp. Englisch.
Lingua: Inglese
Editore: Springer, Springer Aug 2024, 2024
ISBN 10: 9819925266 ISBN 13: 9789819925261
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 181,89
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a comprehensive review of the latest modelling developments in flow batteries, as well as some new results and insights. Flow batteries have long been considered the most flexible answer to grid scale energy storage, and modelling is a key component in their development. Recent modelling has moved beyond macroscopic methods, towards mesoscopic and smaller scales to select materials and design components. This is important for both fundamental understanding and the design of new electrode, catalyst and electrolyte materials. There has also been a recent explosion in interest in machine learning for electrochemical energy technologies. The scope of the book includes these latest developments and is focused on advanced techniques, rather than traditional modelling paradigms. The aim of this book is to introduce these concepts and methods to flow battery researcher, but the book would have a much broader appeal since these methods also employed in other battery and fuel cell systems and far beyond. The methods will be described in detail (necessary fundamental material in Appendices). The book appeals to graduate students and researchers in academia/industry working in electrochemical systems, or those working in computational chemistry/machine learning wishing to seek new application areas.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 392 pp. Englisch.
Da: Majestic Books, Hounslow, Regno Unito
EUR 247,42
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 249,57
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.