SBIR/STTR Research Award

Rapid Counterfeit Detection System by Grafting DNA Taggants to NanoCrystal Cellulose

Award identifier f5d1a1178fb59a51bf89a27f686cc2c7c697f60dcb0ffb6781e05e052f739affAwarding agency Department of Defense · Defense Microelectronics Activity

Award amount

$167,477

Program and phase

SBIR · Phase I

Award year

2020

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Award details

Awarding agency
Department of Defense
Branch
Defense Microelectronics Activity
Recipient company
PRIXARC LLC
Proposal award date
2020-08-10
Contract end date
2021-03-18
UEI
F4N3H1J8CDC8
Solicitation number
20.1
Topic code
DMEA201-001

Research abstract

Prixarc will develop and commercialize a secure and rapid counterfeit detection system using botanical DNA taggants grafted to NanoCrystal Cellulose (NCC) to safeguard electronic components in supply chains and to protect against counterfeiting and diversion. We will advance the science behind grafting of botanical DNA taggants to NCC, along with its application to semiconductors and microchips. Our counterfeit detection system is based on the random color pattern formed by the duplexed DNA-NCC hybrid material. The random pattern which is unique to every tag cannot be replicated or reengineered or counterfeited. Further, the random pattern once formed as a solid NCC thin film retains the pattern throughout its life. Machine learning algorithms will be developed to quickly identify microscale optical iridescent/fluorescence patterns and the design of the rapid detection system based on polarized optical microscopy. At the front-end, our detection system only requires a circular polarized Ultra-Violet (UV) light for reading the tag. The back-end of the detection system is protected by a sophisticated machine learning algorithm and a database system that takes advantage of the random distribution of the DNA taggants within NCC film during grafting and the tag manufacturing. In Phase I, we will conduct analysis, design, and fabrication of hybrid DNA-NCC tags. The feasibility study is expected to include the following items: 1) read and interpret signature hybrid DNA-NCC tags with a yield of greater than 95%, 2) incorporate artificial intelligent (AI) machine learning to predict issues of counterfeiting, and 3) distinguish between defect-free hybrid DNA-NCC tags and one with defects included.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

17 SBIR/STTR records share this UEI (2018–2024). Reported award amounts total $6,275,539. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Energy

Agency intelligence

Department of Defense

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