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The DNA Helix

The DNA Helix

The DNA Helix

The DNA Helix

The DNA Helix

The DNA Helix

Deoxyribonucleic acid, or DNA, is the genetic material responsible for passing traits from generation to generation in all organisms and most viruses. DNA is composed of two strands of nucleotides that wind around each other to form a spring-like structure called a double helix. However, the double helix is not perfectly symmetrical. Instead, there are regularly occurring grooves in the structure. The major groove occurs where the sugar-phosphate backbones are relatively far apart. This space...

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Updated: Jun 13, 2026

Fine-tuning the Size and Minimizing the Noise of Solid-state Nanopores

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DNA Helix Bundle-Encoded Multi-Bit Information Readout by Sapphire-Supported Nanopores.

Pengkun Xia^1,2,3, Deeksha Satyabola^3,4, Nimarpreet Kaur Bamrah^1,2,3

¹School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA.

Advanced Functional Materials

|April 22, 2026

Summary

This summary is machine-generated.

Researchers developed a novel DNA data storage system using sapphire nanopores for secure, high-density information retrieval. This method achieved high signal-to-noise ratios and accurate message classification using machine learning.

Keywords:

Cryptography DNA origami DNA storage Data encryption Helix bundles Low-noise sensing Sapphire-supported nanopores

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Area of Science:

Biotechnology
Nanotechnology
Data Storage

Background:

The demand for high-capacity data storage fuels innovation in memory technologies.
DNA offers a promising medium for high-density data storage due to its molecular nature.
Nanostructured DNA combined with nanopore detection presents a viable storage solution.

Purpose of the Study:

To demonstrate a flexibly programmable and secure DNA data storage readout scheme.
To utilize sapphire-supported, low-noise nanopores for detecting nanostructured DNA.
To achieve a high signal-to-noise ratio for reliable data retrieval.

Main Methods:

Employing four-helix bundle (4HB) DNA nanostructures for data encoding.
Utilizing sapphire-supported nanopores for low-noise DNA detection.
Applying decision-tree supervised learning for message classification.

Main Results:

Achieved a high signal-to-noise ratio of approximately 22 with 250 kHz filtering.
Successfully classified up to ~93% of encoded messages using machine learning.
Demonstrated the feasibility of encoding letters and messages for information retrieval.

Conclusions:

Sapphire-supported nanopores provide a robust platform for DNA data storage.
The proposed scheme offers a secure and programmable method for data readout.
This technology shows significant potential for future high-density information storage solutions.