9783032095398 - smart materials engineering: data-driven approaches and multiscale modelling (14 risultati)

- Rilegato
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
Contatta il venditoreVenditore con 3 stelleCondizione: Nuovo
EUR 166,29
EUR 8,00 spedizioneSpedito da Italia a U.S.A.Quantità: 5 disponibili
Condizione: new.

- Rilegato
Da: Brook Bookstore, Milano, MI, ItaliaBrook Bookstore
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 161,55
EUR 27,99 spedizioneSpedito da Italia a U.S.A.Quantità: 5 disponibili
Condizione: new.

- Rilegato
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 218,29
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimization of smart materials. It provides a holistic perspect…ive essential for researchers, engineers, and students exploring the intersection of materials engineering and AI technologies.The book examines the connection between recent advancements in materials science and multiscale machine learning, facilitating predictive and prescriptive modeling for assessing material behavior based on composition, structure, and processing. It includes comprehensive discussions on smart material design, optimization, complexity analysis, and advanced computational methods for synthesizing and characterizing materials. Challenges in multiscale modeling, such as biologically inspired material design and the influence of nanotechnology on current trends, are thoroughly explored.Emphasizing the critical role of multiscale machine learning and nanotechnology in creating sustainable smart materials, the book also addresses the ethical implications of this research. It discusses opportunities and challenges in biomaterials, particularly in healthcare and biomedical applications, and anticipates future trends in machine learning for sustainable materials design. The book provides insights into how predictive and prescriptive modeling through machine learning can accelerate the material discovery process, guiding researchers toward promising candidates for further exploration.Serving as a roadmap for researchers and scientists, this book offers valuable insights into innovative approaches that support the future of materials science. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

- Rilegato
Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 214,79
EUR 14,48 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Hardcover. Condizione: Brand New. 300 pages. 9.26x6.11x9.49 inches. In Stock.

- Rilegato
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 196,89
EUR 42,87 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimization of smart materials. It provides a holistic perspect…ive essential for researchers, engineers, and students exploring the intersection of materials engineering and AI technologies.The book examines the connection between recent advancements in materials science and multiscale machine learning, facilitating predictive and prescriptive modeling for assessing material behavior based on composition, structure, and processing. It includes comprehensive discussions on smart material design, optimization, complexity analysis, and advanced computational methods for synthesizing and characterizing materials. Challenges in multiscale modeling, such as biologically inspired material design and the influence of nanotechnology on current trends, are thoroughly explored.Emphasizing the critical role of multiscale machine learning and nanotechnology in creating sustainable smart materials, the book also addresses the ethical implications of this research. It discusses opportunities and challenges in biomaterials, particularly in healthcare and biomedical applications, and anticipates future trends in machine learning for sustainable materials design. The book provides insights into how predictive and prescriptive modeling through machine learning can accelerate the material discovery process, guiding researchers toward promising candidates for further exploration.Serving as a roadmap for researchers and scientists, this book offers valuable insights into innovative approaches that support the future of materials science. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

- Rilegato
Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 278,13
EUR 3,45 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New.

- Rilegato
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 220,29
EUR 62,64 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimization of smart mater…ials. It provides a holistic perspective essential for researchers, engineers, and students exploring the intersection of materials engineering and AI technologies.The book examines the connection between recent advancements in materials science and multiscale machine learning, facilitating predictive and prescriptive modeling for assessing material behavior based on composition, structure, and processing. It includes comprehensive discussions on smart material design, optimization, complexity analysis, and advanced computational methods for synthesizing and characterizing materials. Challenges in multiscale modeling, such as biologically inspired material design and the influence of nanotechnology on current trends, are thoroughly explored.Emphasizing the critical role of multiscale machine learning and nanotechnology in creating sustainable smart materials, the book also addresses the ethical implications of this research. It discusses opportunities and challenges in biomaterials, particularly in healthcare and biomedical applications, and anticipates future trends in machine learning for sustainable materials design. The book provides insights into how predictive and prescriptive modeling through machine learning can accelerate the material discovery process, guiding researchers toward promising candidates for further exploration.Serving as a roadmap for researchers and scientists, this book offers valuable insights into innovative approaches that support the future of materials science.

- Rilegato
Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 303,32
EUR 14,48 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: Brand New. 300 pages. 9.26x6.11x9.49 inches. In Stock.

- Rilegato
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 324,26
EUR 31,97 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Hardcover. Condizione: new. Hardcover. This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimization of smart materials. It provides a holistic perspect…ive essential for researchers, engineers, and students exploring the intersection of materials engineering and AI technologies.The book examines the connection between recent advancements in materials science and multiscale machine learning, facilitating predictive and prescriptive modeling for assessing material behavior based on composition, structure, and processing. It includes comprehensive discussions on smart material design, optimization, complexity analysis, and advanced computational methods for synthesizing and characterizing materials. Challenges in multiscale modeling, such as biologically inspired material design and the influence of nanotechnology on current trends, are thoroughly explored.Emphasizing the critical role of multiscale machine learning and nanotechnology in creating sustainable smart materials, the book also addresses the ethical implications of this research. It discusses opportunities and challenges in biomaterials, particularly in healthcare and biomedical applications, and anticipates future trends in machine learning for sustainable materials design. The book provides insights into how predictive and prescriptive modeling through machine learning can accelerate the material discovery process, guiding researchers toward promising candidates for further exploration.Serving as a roadmap for researchers and scientists, this book offers valuable insights into innovative approaches that support the future of materials science. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

- Rilegato
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 213,99
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimizatio…n of smart materials. It provides a holistic perspective essential for researchers, engineers, and students exploring the intersection of materials engineering and AI technologies.The book examines the connection between recent advancements in materials science and multiscale machine learning, facilitating predictive and prescriptive modeling for assessing material behavior based on composition, structure, and processing. It includes comprehensive discussions on smart material design, optimization, complexity analysis, and advanced computational methods for synthesizing and characterizing materials. Challenges in multiscale modeling, such as biologically inspired material design and the influence of nanotechnology on current trends, are thoroughly explored.Emphasizing the critical role of multiscale machine learning and nanotechnology in creating sustainable smart materials, the book also addresses the ethical implications of this research. It discusses opportunities and challenges in biomaterials, particularly in healthcare and biomedical applications, and anticipates future trends in machine learning for sustainable materials design. The book provides insights into how predictive and prescriptive modeling through machine learning can accelerate the material discovery process, guiding researchers toward promising candidates for further exploration.Serving as a roadmap for researchers and scientists, this book offers valuable insights into innovative approaches that support the future of materials science. 230 pp. Englisch.

- Rilegato
- Print on Demand
Da: preigu, Osnabrück, Germaniapreigu
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 186,70
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Buch. Condizione: Neu. Smart Materials Engineering | Data-Driven Approaches and Multiscale Modelling | Ali Ahmadian (u. a.) | Buch | viii | Englisch | 2026 | Springer | EAN 9783032095398 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbi…eter: preigu Print on Demand.

- Rilegato
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 213,99
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book bridges the gap between conventional materials science and emerging data-driven methodologies, highlighting the integration of AI, machine learning, and deep learning technologies to enhance the design, analysis, and optimization of… smart materials. It provides a holistic perspective essential for researchers, engineers, and students exploring the intersection of materials engineering and AI technologies.The book examines the connection between recent advancements in materials science and multiscale machine learning, facilitating predictive and prescriptive modeling for assessing material behavior based on composition, structure, and processing. It includes comprehensive discussions on smart material design, optimization, complexity analysis, and advanced computational methods for synthesizing and characterizing materials. Challenges in multiscale modeling, such as biologically inspired material design and the influence of nanotechnology on current trends, are thoroughly explored.Emphasizing the critical role of multiscale machine learning and nanotechnology in creating sustainable smart materials, the book also addresses the ethical implications of this research. It discusses opportunities and challenges in biomaterials, particularly in healthcare and biomedical applications, and anticipates future trends in machine learning for sustainable materials design. The book provides insights into how predictive and prescriptive modeling through machine learning can accelerate the material discovery process, guiding researchers toward promising candidates for further exploration.Serving as a roadmap for researchers and scientists, this book offers valuable insights into innovative approaches that support the future of materials science.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 240 pp. Englisch.

- Rilegato
- Print on Demand
Da: Majestic Books, Hounslow, , Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 293,06
EUR 7,53 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.

- Rilegato
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 292,95
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.