Machine Learning for Advanced Functional Materials
Language: English
Published by Springer, 2024
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
US$ 216.37
Quantity: 1 available
Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material's electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.…
Seller Inventory # 9789819903955
- Title
- Machine Learning for Advanced Functional Materials
- Author
- Nirav Joshi
- Publisher
- Springer
- Publication year
- 2024
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 9819903955
- ISBN 13
- 9789819903955
- Item weight
- 476 grams
- Dimensions
- 235x155x17 mm
This book presents recent advancements of machine learning methods and their applications in material science and nanotechnologies. It provides an introduction to the field and for those who wish to explore machine learning in modeling as well as conduct data analyses of material characteristics. The book discusses ways to enhance the material’s electrical and mechanical properties based on available regression methods for supervised learning and optimization of material attributes. In summary, the growing interest among academics and professionals in the field of machine learning methods in functional nanomaterials such as sensors, solar cells, and photocatalysis is the driving force for behind this book. This is a comprehensive scientific reference book on machine learning for advanced functional materials and provides an in-depth examination of recent achievements in material science by focusing on topical issues using machine learning methods.
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Niravkumar J. Joshi is Physicist, having completed his doctorate at the Maharaja Sayajirao University of Baroda, India. He is Visiting Professor at Federal University of ABC, Brazil. He has postdoctoral experience from South Korea, Brazil, and at the University of California Berkeley, USA, where he developed selective and sensitive microsensors by MEMS techniques. His present research focuses on the synthesis and characterization of oxide nanostructures and 2D material-based gas sensors.
Dr. Vinod Kushvaha earned his Dual Degree (B. Tech. + M. Tech.) from the Indian Institute of Technology Bombay (IIT Bombay) in Civil Engineering (Specialization in Structural Engineering), following that he earned his second master’s and a Ph.D. degree in Mechanical Engineering (focused on Fracture Characterization of Composite Materials under Impact Loading) at Auburn University, Auburn, AL, USA. Presently, Vinod is working at the Indian Institute of Technology Jammu (IIT Jammu) as Assistant Professor in the Civil Engineering department."About the title" may belong to another edition of this title.
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