Reduced Graphene Oxide for Surface-Enhanced Infrared Absorption Detection of Cannabidiol in Beverages

Surface-enhanced infrared absorption (SEIRA) spectroscopy is a powerful tool for trace molecular detection, but its efficiency strongly depends on the choice of substrate and its molecular interactions. In this study, we report the synthesis of reduced graphene oxide (rGO) as an enhancement layer for SEIRA-based detection of cannabidiol (CBD). rGO was chemically synthesized using ascorbic acid and characterized via scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and UV–visible spectroscopy to confirm its morphological and electronic properties. SEIRA measurements were performed using a Bio-ATR setup integrated with a Bruker Vertex MCT detector. Laboratory-synthesized rGO yielded markedly stronger vibrational signals than commercially procured graphene nanoplatelets. This effect is attributed to improved molecular adsorption and charge-transfer pathways, which was confirmed by XPS analysis. Density functional theory (DFT) simulations were employed to support spectral assignments. Furthermore, concentration-dependent measurements confirmed the sensitivity of the rGO substrate. The practical application is illustrated by the detection of CBD in complex real beverage solutions. These findings demonstrate that rGO can serve as an effective and scalable substrate for sensitive SEIRA detection of cannabinoid compounds, with potential applications in pharmaceutical quality control, industrial, and forensic analysis.

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Publication Details

Journal
ACS Applied Nano Materials
Published
2026-05-08
DOI
https://doi.org/10.1021/acsanm.6c00649
Primary Topic
Cannabis and Cannabinoid Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Reduced Graphene Oxide for Surface-Enhanced Infrared Absorption Detection of Cannabidiol in Beverages

Nisha Rani Agarwal, Janani Balasubramanian, Diellza Bajrami, Boris Mizaikoff et al.
ACS Applied Nano Materials
Cannabis and Cannabinoid Research
article

Reduced Graphene Oxide for Surface-Enhanced Infrared Absorption Detection of Cannabidiol in Beverages

Nisha Rani Agarwal, Janani Balasubramanian, Diellza Bajrami, Boris Mizaikoff, Matteo Tommasini
article en

Abstract

Surface-enhanced infrared absorption (SEIRA) spectroscopy is a powerful tool for trace molecular detection, but its efficiency strongly depends on the choice of substrate and its molecular interactions. In this study, we report the synthesis of reduced graphene oxide (rGO) as an enhancement layer for SEIRA-based detection of cannabidiol (CBD). rGO was chemically synthesized using ascorbic acid and characterized via scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and UV–visible spectroscopy to confirm its morphological and electronic properties. SEIRA measurements were performed using a Bio-ATR setup integrated with a Bruker Vertex MCT detector. Laboratory-synthesized rGO yielded markedly stronger vibrational signals than commercially procured graphene nanoplatelets. This effect is attributed to improved molecular adsorption and charge-transfer pathways, which was confirmed by XPS analysis. Density functional theory (DFT) simulations were employed to support spectral assignments. Furthermore, concentration-dependent measurements confirmed the sensitivity of the rGO substrate. The practical application is illustrated by the detection of CBD in complex real beverage solutions. These findings demonstrate that rGO can serve as an effective and scalable substrate for sensitive SEIRA detection of cannabinoid compounds, with potential applications in pharmaceutical quality control, industrial, and forensic analysis.

ACS Applied Nano Materials
Universität Ulm (DE), Ontario Tech University (CA), Hahn-Schickard-Gesellschaft für angewandte Forschung (DE), Politecnico di Milano (IT)
Deutscher Akademischer Austauschdienst, Natural Sciences and Engineering Research Council of Canada
Zero hunger
Openalex Percentile: Top 8%
Cannabis and Cannabinoid Research
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