Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 305,49
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EUR 235,39
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This contributed volumeexplores the application of machine learning in predictive modeling within the fields of materials science, nanotechnology, and cheminformatics. It covers a range of topics, including electronic properties of metal nanoclusters, carbon quantum dots, toxicity assessments of nanomaterials, and predictive modeling for fullerenes and perovskite materials. Additionally, the book discusses multiscale modeling and advanced decision support systems for nanomaterial risk management, while also highlighting various machine learning tools, databases, and web platforms designed to predict the properties of materials and molecules. It is a comprehensive guide and a great tool for researchers working at the intersection of machine learning and material sciences.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 182,29
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Librería: moluna, Greven, Alemania
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Idioma: Inglés
Publicado por Springer, Springer Mär 2025, 2025
ISBN 10: 3031787277 ISBN 13: 9783031787270
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 235,39
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This contributed volumeexplores the application of machine learning in predictive modeling within the fields of materials science, nanotechnology, and cheminformatics. It covers a range of topics, including electronic properties of metal nanoclusters, carbon quantum dots, toxicity assessments of nanomaterials, and predictive modeling for fullerenes and perovskite materials. Additionally, the book discusses multiscale modeling and advanced decision support systems for nanomaterial risk management, while also highlighting various machine learning tools, databases, and web platforms designed to predict the properties of materials and molecules. It is a comprehensive guide and a great tool for researchers working at the intersection of machine learning and material sciences. 316 pp. Englisch.
Idioma: Inglés
Publicado por Springer, Springer Mär 2025, 2025
ISBN 10: 3031787277 ISBN 13: 9783031787270
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 235,39
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This contributed volume explores the application of machine learning in predictive modeling within the fields of materials science, nanotechnology, and cheminformatics. It covers a range of topics, including electronic properties of metal nanoclusters, carbon quantum dots, toxicity assessments of nanomaterials, and predictive modeling for fullerenes and perovskite materials. Additionally, the book discusses multiscale modeling and advanced decision support systems for nanomaterial risk management, while also highlighting various machine learning tools, databases, and web platforms designed to predict the properties of materials and molecules. It is a comprehensive guide and a great tool for researchers working at the intersection of machine learning and material sciences.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 316 pp. Englisch.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 300,21
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Librería: Majestic Books, Hounslow, Reino Unido
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