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All Journal International Journal of Renewable Energy Development METANA ASEAN Journal of Chemical Engineering JURNAL REKAYASA KIMIA & LINGKUNGAN
Pranolo, Sunu Herwi
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Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Energy Engineering

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Journal : ASEAN Journal of Chemical Engineering

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Application of Nanocrystal Cellulose Based on Empty Palm Oil Fruit Bunch as Glucose Biosensing Pranolo, Sunu Herwi; Waluyo, Joko; Ikbar, Royhan; Damayanthy, Ramanda Ayu; Lestary, Septy; Qadarusman, Muhammad Luqman
ASEAN Journal of Chemical Engineering Vol 23, No 3 (2023)
Publisher : Department of Chemical Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ajche.83422

Abstract

Abstract. Biosensors for glucose sensing purposes are important since diabetes is a worldwide disease. One of the components of glucose biosensors is cellulose nanocrystals (CNCs). CNCs are cellulose derivatives that could be extracted from oil palm empty fruit bunch (OPEFB). Indonesia has a high potential for OPEFB due to its abundance of resources. CNCs have poor conductivity as biosensors, so adding supporting electro-conductor components such as graphene and carbon nanotubes (G-CNT) is necessary. In this research, the amount of bleaching agent of H2O2 in CNCs extraction varies between 1.5% and 10%, and the portion of CNCs in the composite varies between 5%, 15%, and 30%. The purpose of this research is to create an optimum biosensor composite based on its CNCs quality through particle size analysis (PSA) and X-ray diffraction (XRD) tests followed by cyclic voltammetry to determine biosensor’s impedance, limit of detection (LOD), and performance stability. Fourier transform infra red (FTIR) tests are also conducted as process control. The research shows the success of delignification in CNC extraction based on FTIR. Crystallinity enhancement up to 51% as delignification using 1.5% and 10% H2O2 yields CNC with a crystallinity index of 87.1% and 94.0%. The average size of CNCs with delignification by 1.5% and 10% H2O2 are 640.0 nm and 579.8 nm, respectively. Results of testing the biosensor glucose G-CNT/CNC showed the best composition is 5% CNCs that using 10% H2O2 which the highest oxidation peak is 0.00205 A and reduction peak is -0.00223 A. Data of variance composition show the difference of the data is significant by using ANOVA SPSS Test. The biosensor has an accuracy of 83.2% in a test for diabetic urine.
Co-Authors Anis Kristiani, Anis Ari Diana Susanti, Ari Diana Ary Setyawan Basworo, Agung Tri Dahlan, Irvan Damayanthy, Ramanda Ayu Dewi, Kristina Ratna Ikbar, Royhan Joko Waluyo Lestary, Septy Luthfiana Nurul Hidayati, Luthfiana Nurul Margono Margono Norman, Hafiz Paryanto Paryanto Prabang Setyono Putro, Firman Asto Qadarusman, Muhammad Luqman Rossari, Meydiana SATRIYAS ILYAS Sembodo, Bregas Siswahjono Tatag