New design of a commercial chip-based GMR sensor with magnetite nanoparticles for biosensing applications

Ardiyanti, Harlina and Mabarroh, Ni’matil and Wibowo, Nur Aji and Istiqomah, Nurul Imani and Tumbelaka, Rivaldo Marsel and Absor, Moh. Adhib Ulil and Suharyadi, Edi (2023) New design of a commercial chip-based GMR sensor with magnetite nanoparticles for biosensing applications. Artificial Intelligence in Agriculture.

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Abstract

The availability of rapid and low-cost instruments to detect magnetic nanoparticles (MNPs) concentrations
is vital in giant magnetoresistance (GMR)-based biosensors. This paper reports a new setup for a
simple GMR sensor using the commercial chip AAL024 as a transducer. It was combined with a basic
differential amplifier and microcontroller to acquire digital output voltages for the detection of greensynthesized
(GS)-Fe3O4 MNPs as a label and streptavidin-coated MNPs in biosensor applications. As a
characteristic feature of Fe3O4, the GS-Fe3O4 MNPs displayed a cubic inverse spinel structure. The average
GS-Fe3O4 particle size was 11 nm and they exhibited soft ferromagnetic behavior with a saturation
magnetization (MS) of 55.5 emu/g. Owing to the presence of phytochemical components in the Moringa
oleifera (MO) extract, the MS of GS-Fe3O4 was lower than that of Fe3O4. To study sensor performance, the
detection of the GS-Fe3O4 MNP labels and streptavidin-coated MNPs assay was investigated. Using the
microcontroller as the supply voltage for the AAL024 and an analog-to-digital converter simplified data
collection and made any additional measuring instruments unnecessary. The sensor showed promising
performance with the GS-Fe3O4 MNP label and streptavidin assay owing to the linear correspondence
between the signal and concentration of the MNP label. A small limit-of-detection of 4 mg/mL was
achieved for GS-Fe3O4. The sensitivity of GS-Fe3O4 and streptavidin were 2.79 and 1.80 mV/(mg/mL),
respectively. Moreover, the excellent stability and reproducibility of the sensor were confirmed by the
stable signal for over 30 s with relative signal deviation (RSD) ranges of 2e20% and 2e10% for MNPs and
streptavidin, respectively.

Item Type: Other
Uncontrolled Keywords: Classifier; Feature Combination; Multi-Layer Perceptron; Nutrient deficiency
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Mathematics and Natural Sciences > Physics Department
Depositing User: Masrumi Fathurrohmah
Date Deposited: 05 Jun 2024 07:44
Last Modified: 05 Jun 2024 07:44
URI: https://ir.lib.ugm.ac.id/id/eprint/2408

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