Journal
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
Volume 281, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.saa.2022.121598
Keywords
THC; CBN; Silver nanorods; SERS; Multianalyte detection; Independent component analysis
Categories
Funding
- National Electronics and Computer Technology Center (NECTEC) [P1952671]
- National Science and Technology Development Agency (NSTDA), Thailand
Ask authors/readers for more resources
This study developed a rapid, effective, and reliable method for detecting THC and CBN in cannabis using surface-enhanced Raman scattering (SERS) chips. By tuning the dimensions of silver nanorods, the SERS chips demonstrated high sensitivity and reproducibility in detecting trace amounts of THC and CBN. The study also identified characteristic Raman lines of THC and CBN, providing critical information for further data analysis and interpretation. Additionally, the method successfully enabled multianalyte detection of THC and CBN in a mixture using independent component analysis (ICA) model.
Many countries have legalized cannabis and its derived products for multiple purposes. Consequently, it has become necessary to develop a rapid, effective, and reliable tool for detecting delta-9-tetrahydrocannabinol (THC) and cannabinol (CBN), which are important biologically active compounds in cannabis. Herein, we have fabricated SERS chips by using glancing angle deposition and tuned dimensions of silver nanorods (AgNRs) for detecting THC and CBN at low concentrations. Experimental and computational results showed that the AgNR substrate with film thickness (or nanorod length) of 150 nm, corresponding to nanorod diameter of 79 nm and gap between nanorods of 23 nm, can effectively sense trace THC and CBN with good reproducibility and sensitivity. Due to limited spectral studies of the cannabinoids in previous reports, this work also explored towards identifying characteristic Raman lines of THC and CBN. This information is critical to further reliable data analysis and interpretation. Moreover, multianalyte detection of THC and CBN in a mixture was successfully demonstrated by applying an open-source independent component analysis (ICA) model. The overall method is
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available