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Rahele Aboltaman

Rahele Aboltaman

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0002-0015-6692
Education: PhD.
ScopusId: 57194160357
HIndex:
Faculty: Science
Address: Arak University
Phone: 08632627528

Research

Title
Application of sensitive SERS plasmonic biosensor for high detection of metabolic disorders
Type
JournalPaper
Keywords
Surface-enhanced Raman scattering (SERS), silver dendritic nanostructures, nondestructive biosensor, organoacids, metabolic disorders.
Year
2023
Journal Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
DOI
Researchers Rahele Aboltaman ، Zeinab Kiamehr ، Akbar Cheraghi ، Rasoul Malekfar

Abstract

Due to the importance of early detection of metabolic diseases in newborns, it is essential to measure organoacids; L-Tryptophan, Sebacic acid, and Glutaric acid in very low concentrations. Therefore, the necessity of the construction of a powerful nondestructive biosensor just like the surface-enhanced Raman scattering (SERS) sensor is demonstrated. Through the growth of silver dendritic nanostructures on different substrates like aluminum (Al), copper (Cu), indium tin oxide (ITO), and silicon (Si), a new SERS-based biosensor was developed. Because the Raman signal of molecules adsorbed on dendritic nanostructures is significantly increased, SERS biosensors based on these nanostructures can be used to detect very low concentrations of materials. In this study, first, the organoacid L-Lysine was detected up to a concentration of 10-12 M, by using a biosensor based on Al, Cu, ITO, and Si substrates. Then, by comparing the results obtained from different substrates, the silicon substrate as the most successful substrate with the best results was used in the SERS biosensor to detect the organoacids, L-Tryptophan, Sebacic acid, and Glutaric acid up to a concentration of 10-12 M. SEM imaging was used to characterize silver dendritic nanostructures on solid substrates. The successful performance of the SERS biosensor based on silver dendrites in this study promises to be effective in diagnostic applications such as cancer diagnosis (the limit of single molecular detection).