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This contributed volume provides a comprehensive overview of how artificial intelligence (AI) and machine learning (ML) are transforming experimental research in nanomaterials. It covers foundational AI concepts, data acquisition and preprocessing tailored to nanomaterials and explores AI-enhanced synthesis and characterization techniques. The volume discusses applications in catalysis, environmental remediation, energy storage, and sensor technologies, emphasizing green synthesis and high-performance materials. It concludes with future directions, including responsible AI practices, policy frameworks, and educational strategies. Designed for graduate students, academic researchers, and R&D professionals in materials science, chemistry, physics, nanotechnology, and engineering, as well as policymakers and educators, this book aims to illuminate how AI can revolutionize nanomaterials research for energy, environmental, and biomedical applications.
This contributed volume provides a comprehensive overview of how artificial intelligence (AI) and machine learning (ML) are transforming experimental research in nanomaterials. It covers foundational AI concepts, data acquisition and preprocessing tailored to nanomaterials and explores AI-enhanced synthesis and characterization techniques. The volume discusses applications in catalysis, environmental remediation, energy storage, and sensor technologies, emphasizing green synthesis and high-performance materials. It concludes with future directions, including responsible AI practices, policy frameworks, and educational strategies. Designed for graduate students, academic researchers, and R&D professionals in materials science, chemistry, physics, nanotechnology, and engineering, as well as policymakers and educators, this book aims to illuminate how AI can revolutionize nanomaterials research for energy, environmental, and biomedical applications.
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