Bridging Nanomanufacturing and Artificial Intelligence—A Comprehensive Review

Abstract

Nanomanufacturing and digital manufacturing (DM) are defining the forefront of the fourth industrial revolution—Industry 4.0—as enabling technologies for the processing of materials spanning several length scales. This review delineates the evolution of nanomaterials and nanomanufacturing in the digital age for applications in medicine, robotics, sensory technology, semiconductors, and consumer electronics. The incorporation of artificial intelligence (AI) tools to explore nanomaterial synthesis, optimize nanomanufacturing processes, and aid high-fidelity nanoscale characterization is discussed. This paper elaborates on different machine-learning and deep-learning algorithms for analyzing nanoscale images, designing nanomaterials, and nano quality assurance. The challenges associated with the application of machine- and deep-learning models to achieve robust and accurate predictions are outlined. The prospects of incorporating sophisticated AI algorithms such as reinforced learning, explainable artificial intelligence (XAI), big data analytics for material synthesis, manufacturing process innovation, and nanosystem integration are discussed.

Nanoimprint Lithography for Next-Generation Carbon Nanotube-Based Devices

“…Further, single walled carbon nanotubes can exist in armchair, zigzag, and chiral configurations [ 5 , 6 ]. Several methods have been devised for the synthesis and fabrication of CNT-based devices [ 7 , 8 , 9 ]. Many products using CNTs today incorporate CNT powders dispersed in polymer matrices or deposited as thin films in order to commercialize these products [ 10 , 11 , 12 , 13 , 14 ].…”