Enhancing Hybrid Nanodevice Fabrication Efficiency Using Machine Learning (Hardcover)

Udit Mamodiya

ISBN 10: 1394355289 / ISBN 13: 9781394355280

Editore: John Wiley & Sons Inc, 2026

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Hardcover. Gain a competitive edge in the semiconductor industry with this essential guide, which provides the practical insights and machine learning techniques needed to optimize the fabrication of hybrid nanodevices for integrated circuits. Enhancing Hybrid Nanodevice Fabrication Efficiency Using Machine Learning explores the intersection of advanced manufacturing techniques and machine learning applications in the field of nanotechnology, specifically focusing on hybrid nanodevices for integrated circuits. This book provides a comprehensive understanding of how machine learning algorithms and techniques can optimize the fabrication processes of hybrid nanodevices, improving their efficiency, reliability, and performance in integrated circuit applications. The book begins with an introduction to the fundamentals of hybrid nanodevice fabrication and the role of machine learning in enhancing these processes. It then delves into various machine learning algorithms and models used for process optimization, quality control, and predictive maintenance in integrated circuit fabrication. Case studies and practical examples illustrate real-world applications of machine learning in improving yield, reducing costs, and accelerating time-to-market for hybrid nanodevices. It also addresses the pressing need for a comprehensive guide on machine learning applications in nanodevice fabrication. It provides researchers, engineers, and industry professionals with practical insights for implementing machine learning techniques to tackle challenges such as variability reduction, defect detection, and process optimization. By bridging the gap between theory and practice, the book equips readers with the knowledge and tools necessary to leverage machine learning for a competitive advantage in the semiconductor industry. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Codice articolo 9781394355280

Dati bibliografici

• Titolo: Enhancing Hybrid Nanodevice Fabrication Efficiency Using Machine Learning (Hardcover)
• Editore: John Wiley & Sons Inc
• Data di pubblicazione: 2026
• Lingua: Inglese
• ISBN 10: 1394355289
• ISBN 13: 9781394355280
• Rilegatura: Hardcover
• Condizione: new

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Riassunto

Gain a competitive edge in the semiconductor industry with this essential guide, which provides the practical insights and machine learning techniques needed to optimize the fabrication of hybrid nanodevices for integrated circuits.

Enhancing Hybrid Nanodevice Fabrication Efficiency Using Machine Learning explores the intersection of advanced manufacturing techniques and machine learning applications in the field of nanotechnology, specifically focusing on hybrid nanodevices for integrated circuits. This book provides a comprehensive understanding of how machine learning algorithms and techniques can optimize the fabrication processes of hybrid nanodevices, improving their efficiency, reliability, and performance in integrated circuit applications. The book begins with an introduction to the fundamentals of hybrid nanodevice fabrication and the role of machine learning in enhancing these processes. It then delves into various machine learning algorithms and models used for process optimization, quality control, and predictive maintenance in integrated circuit fabrication. Case studies and practical examples illustrate real-world applications of machine learning in improving yield, reducing costs, and accelerating time-to-market for hybrid nanodevices. It also addresses the pressing need for a comprehensive guide on machine learning applications in nanodevice fabrication. It provides researchers, engineers, and industry professionals with practical insights for implementing machine learning techniques to tackle challenges such as variability reduction, defect detection, and process optimization. By bridging the gap between theory and practice, the book equips readers with the knowledge and tools necessary to leverage machine learning for a competitive advantage in the semiconductor industry.