I-Corps: Highly secure anticounterfeiting tags with deep learning software for reliable product authentication

Award ID: 2136807

The broader impacts and commercial potential of this I-Corps project enable a new platform for anticounterfeiting and authentication of physical goods. This project uses physically unclonable devices such as small anticounterfeiting tags that are essentially impossible to replicate. Because these tags are not readily copied by current manufacturing processes, they ensure uniqueness and security with distinct advantages over other chaosmetric approaches. Current anticounterfeiting technologies often face challenges with low pattern complexity that allows the security tag to be copied, lack of facile authentication tools for high-complexity tags, and physical instabilities that can limit applications. This technology platform addresses these challenges as it offers potential commercial applications in markets with high safety standards, such as pharmaceuticals and automobile parts, or in high-value sectors where authentication can often be destructive or difficult. This I-Corps project develops two dimensional (2D) nanomaterials and their microstructures for use in anticounterfeiting applications. By physically deforming the 2D nanomaterial thin films randomly, the resulting microstructure shows chaosmetric properties and high structural stability which can be utilized as a new type of anticounterfeiting tag. The 2D nanomaterial tags may be irreplaceable and can be utilized in a variety of extreme environments such as at very high or very low temperatures, in strong acidic or basic solutions, and after physical washing. These physical environments are areas where conventional anti-counterfeiting tags often fail. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Ruth Shuman