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Updated: May 5, 2026

Fabrication, Densification, and Replica Molding of 3D Carbon Nanotube Microstructures
Published on: July 2, 2012
Simulation of a randomly percolated CNT network for an improved analog physical unclonable function
Hyo-In Yang1, Hanbin Lee1, Jeonghee Ko1
1School of Electrical Engineering, Kookmin University, Seoul, 02707, Korea.
This study uses simulations to optimize carbon nanotube network (CNT) fabrication for physically unclonable functions (PUFs). It introduces a novel 2D patterned analog PUF with enhanced security and error compensation, validated by a new performance evaluation method.
Area of Science:
- Materials Science
- Electrical Engineering
- Computer Science
Background:
- Carbon nanotube networks (CNTs) offer inherent randomness suitable for physically unclonable functions (PUFs).
- Manufacturing variations in CNT networks significantly impact PUF performance, necessitating process optimization.
- Directly fabricating and testing under various conditions is time-consuming and costly.
Purpose of the Study:
- To optimize process conditions for high-performance CNT-based PUFs using simulation.
- To develop a 2D patterned analog PUF with improved security and error resilience.
- To propose a new evaluation method for analog PUF performance.
Main Methods:
- Simulated randomly formed CNT networks to analyze process variable correlations.
- Implemented a 2D patterned analog PUF through simulation.
- Developed and applied a novel evaluation method for analog PUF performance.
Main Results:
- Confirmed correlations between CNT network variables (density, metallic ratio) and PUF performance.
- Demonstrated a 2D patterned analog PUF with enhanced security and error compensation capabilities.
- Validated the effectiveness of the new analog PUF evaluation method.
Conclusions:
- Simulation is a viable approach for optimizing CNT PUF fabrication processes.
- The proposed 2D patterned analog PUF offers a promising solution for secure and reliable PUF applications.
- This research provides a foundation for developing customized CNT PUFs through simulation-guided process design.
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