AUTHOR=Sivasubramani Santhosh , Prodromakis Themis 

TITLE=Reaching new frontiers in nanoelectronics through artificial intelligence

JOURNAL=Frontiers in Nanotechnology

VOLUME=Volume 7 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/nanotechnology/articles/10.3389/fnano.2025.1627210

DOI=10.3389/fnano.2025.1627210

ISSN=2673-3013

ABSTRACT=Artificial Intelligence (AI) is revolutionizing industries worldwide, delivering unprecedented productivity gains across diverse sectors, from healthcare to manufacturing. Recent advances in generative AI models have particularly accelerated innovation, enabling more efficient execution of complex tasks such as drug discovery, autonomous driving, and predictive maintenance. In the areas of electronics manufacturing: a sector crucial to the advancement of modern technologies, the impact of AI is profound, with the potential to transform every stage of the supply chain. This perspective investigates the role of AI in reshaping the electronics and semiconductor industries, exploring how it integrates into various stages of production and development. The approach to AI integration is structured and methodical, addressing both challenges and opportunities across five key nanotechnology areas: materials discovery, device design, circuit and system design, testing/verification, and modeling. In materials discovery, AI aids in identifying new, more efficient and sustainable materials. In device design, it enhances the functionality and integration of components. AI’s capabilities in circuit and system design enables more complex and precise electronic systems. During the testing and verification stage, AI contributes to more rigorous and faster testing processes, ensuring reliability before market release. Finally, in modeling, AI’s predictive capabilities allow for accurate simulations, crucial for anticipating performance under various scenarios. Each pillar of this electronics supply chain underscores AI’s ability to accelerate processes, optimize performance, and reduce costs. Supported by case studies of AI-driven breakthroughs, this perspective provides a comprehensive review of current AI applications across the entire electronic supply chain, illustrating improvements in yield and sustainable manufacturing practices.