Call for Chapters: Leveraging AI and Nanotechnology for Materials, Devices, and Manufacturing

Editors

Ashok Vaseashta, International Clean Water Institute, United States
Ioan STAMATIN, University of Bucharest, Romania

Call for Chapters

Proposals Submission Deadline: May 15, 2025
Full Chapters Due: August 15, 2025

Introduction

The book “Leveraging AI and Nanotechnology for Materials, Devices, and Manufacturing”, provides an interdisciplinary exploration of the transformative synergy between AI and nanotechnology. It offers insights into how these cutting-edge fields revolutionize material discovery, device fabrication, and manufacturing processes. The book begins with foundational concepts, introducing the principles of artificial intelligence and nanotechnology. It delves into the basics of nanomaterials, their unique properties, synthesis techniques, and a primer on machine learning and AI tools tailored for materials science. A significant focus is given to AI-driven advancements in materials research. Topics include predictive modeling for material properties, data-driven design, and AI-assisted material characterization using techniques like image processing and spectroscopy analysis. These sections showcase how AI accelerates nanomaterial discovery and optimizes their performance. The intersection of nanotechnology and device engineering is explored through applications in nanoelectronics, photonics, and sensor technologies. The book also highlights AI’s role in nanomanufacturing, emphasizing automation, robotics, quality control, and sustainability. The book describes the use of decision-support tools and technology accelerators to accelerate research. Case studies illustrate real-world implementations, offering insights into eco-friendly and efficient production techniques. The book bridges into education by examining how AI and nanotechnology are transforming STEM learning. It discusses innovative tools such as virtual labs, AI-driven simulations, and interdisciplinary curriculum development. Ethical considerations, societal impacts, and strategies for public engagement are also addressed. Concluding with a forward-looking perspective, the book explores emerging trends like quantum computing, nanoscale robotics, and the integration of AI with IoT. Challenges such as scalability, reproducibility, and ethical dilemmas are analyzed, alongside a roadmap for future innovations.

Objective

The objective of this book is to bridge the gap between fundamental nanotechnology principles and cutting-edge AI techniques, offering a holistic perspective on their synergistic applications. Hence, the book is aimed at providing a comprehensive exploration of the convergence of AI and nanotechnology in advancing materials science, device engineering, and manufacturing processes, as industries push the boundaries of innovation . AI-driven methodologies are revolutionizing the design, synthesis, and optimization of nanomaterials, enabling unprecedented precision and efficiency and the book delves into AI-powered material discovery, predictive modeling, and autonomous experimentation, demonstrating how machine learning accelerates the identification and fabrication of novel nanomaterials with tailored properties. The book will also examine how AI enhances nanoscale device engineering, from semiconductor advancements to biomedical applications. A key focus will be on AI-integrated smart manufacturing, where nanotechnology and automation converge to drive sustainable, scalable, and adaptive production processes. By presenting state-of-the-art research, case studies, and real-world applications, this book will serve as a vital resource for researchers, engineers, and industry professionals seeking to harness AI and nanotechnology for next-generation materials and manufacturing paradigms. Ultimately, it aims to inspire innovation and foster interdisciplinary collaboration in these transformative fields. This book will serve as an essential resource for researchers, educators, and professionals seeking to understand and leverage AI and nanotechnology for groundbreaking advancements in science, technology, and manufacturing.

Target Audience

The target audience of this book will consist of professionals and researchers working in the fields of Materials Science, Materials Engineering, Nanoscience, Artificial Intelligence, Advanced Manufacturing, and various other related disciplines, e.g., Environment, Chemistry, Education, Administrative sciences and management, Sociology, and subjects related to Public Policies and Decision Support. Moreover, the book will provide insights and support to executives concerned with the management of expertise, knowledge, information, and policy development. Additionally, the book will be very useful to many researchers, graduate/postgraduate students, scientists, policymakers, industry professionals, and practitioners. Several chapters from this book may be adopted as text supplements for classroom lessons or independent study.

Recommended Topics

Section I: Fundamentals and Foundations 1. Introduction to Artificial Intelligence and Nanotechnology Overview of AI and its applications Basics of nanotechnology and its significance Interdisciplinary synergy between AI and nanotechnology 2. Principles of Nanomaterials Types of nanomaterials Properties and applications Synthesis and characterization techniques 3. Core Concepts of AI for Material Science Machine learning basics Neural networks and deep learning AI tools and platforms for materials research Section II: AI in Materials Science 4. AI-Driven Discovery of Nanomaterials Predictive modeling for material properties Design of experiments using AI Case studies of AI-enabled material discovery 5. Data-Driven Approaches in Materials Design Big data in material science Data mining and analysis for structure-property relationships Role of generative AI in material synthesis 6. AI Applications in Material Characterization Image processing for microscopy Spectroscopy data analysis Defect detection and classification using AI Section III: Nanotechnology in Devices and Manufacturing 7. Nanotechnology in Device Fabrication Nanoscale device design and applications Role of AI in optimizing device performance Case studies in nanoelectronics and nanophotonics 8. AI for Nanomanufacturing Automation and robotics in nanomanufacturing Quality control using machine vision Real-time monitoring and optimization 9. Sustainable Nanomanufacturing Environmental impact of nanotechnology AI for eco-friendly manufacturing Circular economy approaches in nanomaterial production Section IV: AI and Nanotechnology in Education 10. Educational Tools for AI and Nanotechnology Virtual labs and simulations AI-driven teaching tools Hands-on nanotechnology workshops 11. Curriculum Development Integrating AI and nanotechnology into STEM education Case studies from universities and research institutions Future trends in interdisciplinary education 12. Ethics and Public Awareness Societal impact of AI and nanotechnology Ethical considerations in research and application Strategies for public engagement and education Section V: Future Trends and Challenges 13. Emerging Technologies Quantum computing and nanotechnology AI for nanoscale robotics Integration with IoT and edge computing 14. Challenges and Opportunities Limitations of current AI and nanotechnology tools Addressing scalability and reproducibility Roadmap for future innovations

Submission Procedure

Researchers and practitioners are invited to submit on or before May 15, 2025, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by May 29, 2025 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by August 15, 2025, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, Leveraging AI and Nanotechnology for Materials, Devices, and Manufacturing. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery^® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2026.

Important Dates

May 15, 2025: Proposal Submission Deadline
May 29, 2025: Notification of Acceptance
August 15, 2025: Full Chapter Submission
October 6, 2025: Review Results Returned
November 3, 2025: Final Acceptance Notification
November 30, 2025: Final Chapter Submission

Inquiries

Prof. Dr. Ashok Vaseashta
International Clean Water Institute
prof.vaseashta@ieee.org

Prof. Dr. Ioan Stamatin
University of Bucharest
istarom@3nanosae.org

Classifications

Computer Science and Information Technology; Physical Sciences and Engineering

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