Monolayer graphene/platinum-modified 3D origami microfluidic paper-based biosensor for smartphone-assisted biomarkers detection: Original scientific article

Arda Fridua Putra; Annisa Septyana Ningrum; Suyanto Suyanto; Vania Mitha Pratiwi; Muhammad Yusuf Hakim  Widianto; Irkham Irkham; Wulan Tri Wahyuni; Isnaini Rahmawati; Fu-Ming Wang; Chi-Hsien Huang; Ruri Agung  Wahyuono

doi:10.5599/admet.2833

Authors

Arda Fridua Putra Department of Engineering Physics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia https://orcid.org/0009-0009-3816-459X
Annisa Septyana Ningrum Department of Engineering Physics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia https://orcid.org/0009-0009-9833-8328
Suyanto Suyanto Department of Engineering Physics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia https://orcid.org/0009-0008-6861-6246
Vania Mitha Pratiwi Department of Materials Engineering, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia https://orcid.org/0000-0001-8300-7520
Muhammad Yusuf Hakim Widianto Department of Mathematics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia https://orcid.org/0000-0002-1720-9754
Irkham Irkham Department of Chemistry, University of Padjadjaran, Sumedang 45363, Indonesia https://orcid.org/0000-0001-9938-2931
Wulan Tri Wahyuni Department of Chemistry, Institut Pertanian Bogor (IPB) University, Bogor 16680, Indonesia https://orcid.org/0000-0002-3071-4974
Isnaini Rahmawati Department of Chemistry, University of Indonesia, Depok 16424, Indonesia https://orcid.org/0000-0003-1327-592X
Fu-Ming Wang Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taipei 10607, Taiwan and Graduate Institute of Energy and Sustainability Technology, National Taiwan University of Science and Technology, Taipei 10607, Taiwan https://orcid.org/0000-0003-4407-3554
Chi-Hsien Huang Department of Engineering Physics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia and Department of Materials Engineering, Ming Chi University of Technology, New Taipei City 24031, Taiwan https://orcid.org/0000-0003-0369-3124
Ruri Agung Wahyuono Department of Engineering Physics, Institut Teknologi Sepuluh Nopember, Surabaya 60111, Indonesia https://orcid.org/0000-0002-6937-9907

DOI:

https://doi.org/10.5599/admet.2833

Keywords:

Colorimetry, diagnostic kit, dopamine, NADH, nanocatalyst

Abstract

Background and purpose: Imbalances in biomarkers such as dopamine and NADH are linked to neurological and metabolic disorders, including Parkinson’s disease, depression, and stroke, underscoring the need for rapid and accessible diagnostics. This study presents a smartphone-assisted, 3D origami microfluidic paper-based analytical device (µPAD) modified with photochemically synthesized graphene/platinum (G/Pt) nanocatalysts for multiplex colorimetric detection of dopamine and NADH. Experimental approach: G/Pt catalysts were prepared using 2.5 to 10 mM Pt precursors under UV irradiation. µPADs were laser-printed on commercial-grade filter paper, patterned, and folded into three layers of 3D Origami. Key results: The optimized 10 mM G/Pt catalyst significantly improved reaction rates (18× faster), leading to a rapid detection time constant of 6.69 and 4.59 s for dopamine and NADH, respectively. Furthermore, the utilization of 10 mM G/Pt catalyst increased colour intensity (2.48×) on the µPAD platform. An application for smartphones integrated with an image processing algorithm was developed using Kotlin to enable automatic quantification of colorimetric signals from saturation and hue channels for dopamine and NADH, respectively. The detection exhibited the lowest mean absolute percentage errors of 0.52 and 0.07 % as well as a limit of detection of 0.56 and 0.99 mM for dopamine and NADH, respectively. Conclusion: The 3D origami structure facilitates efficient fluid handling and multiplex detection, while the nanocatalyst modification improves pore infiltration and sensitivity. This work demonstrates, for the first time, a cost-effective, portable, and high-performance biosensor for dual biomarker detection, offering substantial promise for point-of-care diagnostics in neurological and metabolic health monitoring.

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