The convergence of nanomanufacturing and artificial intelligence: trends and future directions.

Abstract

The integration of nanoscale production processes with Artificial intelligence (AI) algorithms has the potential to open new frontiers in nanomanufacturing by accelerating development timelines, optimizing production, reducing costs, enhancing quality control, and improving sustainability. Such changes are already underway with digital and cyber-physical technologies becoming increasingly intertwined with 'smart' manufacturing and industrial processes today. With the nanomanufacturing sector focused on the scalable production of complex (nano)materials, (nano)devices, and biologics, AI and its sub-fields, including machine learning (ML), are positioned to be key enablers of efficiency and innovation. In this topical review, we briefly explore the current state-of-the-art of how AI and ML techniques can be employed within nanomanufacturing. We discuss from a birds-eye perspective, the impact of AI/ML on various stages of the production lifecycle, and examine future opportunities and challenges. Key areas include computational design and discovery, process optimization, predictive maintenance, and quality assurance/defect detection. Further, challenges in implementation, process complexity, and ethical and regulatory considerations are explored in light of the increasing reliance on data-driven approaches for manufacturing.