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Graphene-Based Physically Unclonable Functions with Dual Source of Randomness.

Sangsun Lee1, Sami Pekdemir2,3, Nilgun Kayaci2

  • 1Department of Materials Science and Engineering, Inha University, Incheon 22212, Korea.

ACS Applied Materials & Interfaces
|July 10, 2023
PubMed
Summary
This summary is machine-generated.

Graphene’s unique properties enable novel physically unclonable functions (PUFs) for anti-counterfeiting. Two stochastic processes create complex graphene surfaces that are highly resistant to cloning.

Keywords:
ORB feature matchingRaman spectrumdewettinggraphenephysically unclonable functions

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Area of Science:

  • Materials Science
  • Nanotechnology
  • Physical Chemistry

Background:

  • Growing interest in randomized response systems for physically unclonable functions (PUFs).
  • Graphene's atomic-level thickness control and unique Raman spectrum make it suitable for PUF applications.

Purpose of the Study:

  • To develop graphene-based PUFs using two independent stochastic processes.
  • To create unique and complex surfaces that are difficult to clone for anticounterfeiting and authentication.

Main Methods:

  • Utilizing chemical vapor deposition (CVD) to control graphene adlayer shape and number.
  • Employing polymer film dewetting and oxygen plasma etching for random positioning of graphene domains.
  • Raman mapping to generate multicolor images from varied graphene layer numbers and spectra.

Main Results:

  • Successfully generated graphene PUFs with randomized shapes, numbers of layers, and positions.
  • Created multicolor images with high encoding capacity via Raman mapping.
  • Demonstrated advanced feature-matching algorithms for multicolor image authentication.

Conclusions:

  • The developed method leverages two independent stochastic processes on a 2D nanomaterial platform.
  • This approach yields surfaces with inherent complexity, significantly challenging clonability.
  • Graphene PUFs offer a promising solution for robust anticounterfeiting and authentication.