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Breaking the barrier to biomolecule limit-of-detection via 3D printed multi-length-scale graphene-coated electrodes

Author

Listed:
  • Md. Azahar Ali

    (Carnegie Mellon University)

  • Chunshan Hu

    (Carnegie Mellon University)

  • Bin Yuan

    (Carnegie Mellon University)

  • Sanjida Jahan

    (Carnegie Mellon University)

  • Mohammad S. Saleh

    (Carnegie Mellon University)

  • Zhitao Guo

    (Carnegie Mellon University)

  • Andrew J. Gellman

    (Carnegie Mellon University)

  • Rahul Panat

    (Carnegie Mellon University)

Abstract

Sensing of clinically relevant biomolecules such as neurotransmitters at low concentrations can enable an early detection and treatment of a range of diseases. Several nanostructures are being explored by researchers to detect biomolecules at sensitivities beyond the picomolar range. It is recognized, however, that nanostructuring of surfaces alone is not sufficient to enhance sensor sensitivities down to the femtomolar level. In this paper, we break this barrier/limit by introducing a sensing platform that uses a multi-length-scale electrode architecture consisting of 3D printed silver micropillars decorated with graphene nanoflakes and use it to demonstrate the detection of dopamine at a limit-of-detection of 500 attomoles. The graphene provides a high surface area at nanoscale, while micropillar array accelerates the interaction of diffusing analyte molecules with the electrode at low concentrations. The hierarchical electrode architecture introduced in this work opens the possibility of detecting biomolecules at ultralow concentrations.

Suggested Citation

  • Md. Azahar Ali & Chunshan Hu & Bin Yuan & Sanjida Jahan & Mohammad S. Saleh & Zhitao Guo & Andrew J. Gellman & Rahul Panat, 2021. "Breaking the barrier to biomolecule limit-of-detection via 3D printed multi-length-scale graphene-coated electrodes," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-27361-x
    DOI: 10.1038/s41467-021-27361-x
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    Cited by:

    1. Matin Ataei Kachouei & Jacob Parkulo & Samuel D. Gerrard & Tatiane Fernandes & Johan S. Osorio & Md. Azahar Ali, 2025. "Attomolar-sensitive milk fever sensor using 3D-printed multiplex sensing structures," Nature Communications, Nature, vol. 16(1), pages 1-17, December.

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