River Publishers Rapids Series on Intelligence in Chips – serie

This book tries to discover how using nano-designed materials might increase the performance and sustainability of existing green energy systems. The book covers a wide range of subjects reflecting the most recent developments and new trends in the industry, including:Synthesis, the electronic layout, green design, and work in energy storage and production are described for carbon nanomaterials in the scope of green energy systems.Since carbon nanostructures are essential parts of fuel cells, quantifying their environmental impact offers useful information.Advanced nanomaterials for lithium-ion batteries: progress in developing nanomaterials to enhance how well lithium-ion batteries work and how far they can be advanced.Studies on nanoengineered materials for solar cells: developing and making different designs for nano-enabled solar panels, looking at their benefits, weaknesses, and possible advances.Apart from discussing main concepts and synthesis methods, this book will underline how CNTs are applied in modern energy technologies. It is important to solve the issues related to the environment, the ability to make those materials in large quantities, and how long the materials will last. With the help of nanoengineering, this book seeks to boost the growth of energy solutions that are energy-efficient, affordable, and environmentally responsible, therefore adding to the worldwide job of promoting green energy technology.

This is essential reading for semiconductor professionals seeking to expand their knowledge on silicon processes, understand the significance of defect prevention, and explore methods for optimizing processes by reducing defects using AI and IoT technologies.In the dynamic landscape of semiconductor manufacturing, the focus on processes and defect prevention stands paramount. Traditional approaches have yielded valuable insights, yet the emergence of Artificial Intelligence (AI) and Internet of Things (IoT) technologies heralds a new era in defect prevention strategies. Engineers specializing in AI and machine learning, interdisciplinary researchers, and early graduates aspiring to enter the semiconductor industry will also find this book invaluable.Meticulously crafted, this book provides concise, yet insightful content tailored to today's fast-paced readers. It emphasizes semiconductors, manufacturing processes, and defect prevention, offering a comprehensive understanding of these critical areas. The integration of AI and IoT in chip manufacturing defect prevention represents a groundbreaking advancement.Targeting semiconductor engineers, researchers, technology professionals, and students, this book serves as a valuable resource for understanding the interplay between semiconductors, manufacturing processes, defects, and the transformative potential of AI and IoT integration. Practical tools for failure analysis and parameter control are provided, along with hypothetical use cases and theoretical applications that inspire innovation. Through interdisciplinary insights, this book charts a course toward a future where semiconductor manufacturing defects are minimized, productivity is maximized, and innovation thrives at the intersection of technology and industry.

This book explores the growing focus on artificial intelligence (AI) systems in both industry and academia. It evaluates and justifies AI applications while enhancing trust in AI outcomes and aiding comprehension of AI feature development. Key topics include an overview of explainable AI, black box model understanding, interpretability techniques, practical XAI applications, and future trends and challenges in XAI.Technical topics discussed in the book include:Explainable AI overviewUnderstanding black box modelsTechniques for model interpretabilityPractical applications of XAIFuture trends and challenges in XAI