Silver Nanoparticle Produced by Using Abelmoschus esculentus (L.) Moench Leaves Extract Via Bioreduction Processs as Blood Glucose Nanosensor

Document Type : Original Article

Authors

1 Faculty of Pharmacy, University of East Indonesia, Makassar-Indonesia Jalan. Rappocini Raya, Makassar-Indonesia

2 Department of Chemistry, Faculty Mathematics and Natural Science, University of Hasanuddin, Jalan. Perintis Kemerdekaan 90245, Makassar-Indonesia

3 Department of Chemistry, Faculty of Mathematics and Natural Sciences, Hasanuddin University

4 Chemistry Department, Mathematics and Natural Sciences, Hasanuddin University, Makassar, Indonesia

Abstract

Silver nanoparticles were produced through bioreduction using Abelmoschus esculentus leaves extract and applied as a blood glucose nano sensor. The biosynthetic reaction produced silver nanoparticles by mixing Abelmoschus esculentus leaves extract and Ag+. The formation of silver nanoparticles was characterized by a color change in the solution from yellow to brown. Silver nanoparticles were analyzed using UV-Vis, FT-IR, PSA, and TEM. Furthermore, the design and testing of blood glucose nanosensors was carried out. The UV-Vis test results showed that the best silver nanoparticles were produced during an incubation period of 6 days with a band gap energy of 2.096 eV. The FT-IR spectrum showed that there had been a bioreduction process as indicated by a decrease in the intensity of the functional groups which were bioreductors. TEM and PSA results showed that silver nanoparticles were spherical and oval in shape with a size of less than 50 nm. The design and application results for the nanosensor showed that silver nanoparticles were in the range of 0.5 mM - 8 mM with a Regression (R) of 0.9494. The detection limit of the silver nanoparticle sensor was at a concentration of 1.68 mM with a sensitivity of 3.27 A. mM-1. mm-2. The glucose level contained in blood samples with silver nanoparticle sensors was 93.05 mg / dL with a measurement difference of 1.95% when compared to Automated Analyzed Clinical Chemistry.

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