Design of Kretschmann-Surface Plasmon Resonance Sensor for glucose detection

Kasri, Mohd Ikhwan (2021) Design of Kretschmann-Surface Plasmon Resonance Sensor for glucose detection. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Surface plasmon resonance (SPR) sensors based on the Kretschmann configuration use chromium, gold and polymer nanofilms suitable for unlabeled biomedical sensing. The L9 Taguchi orthogonal array method was used in this study to improve the effect of the incident optical wavelength and thickness of chromium, gold and polymer nanofilms on the performance of Kretschmann -based surface plasmon resonance sensors. The control variables were changed at three levels for multi -response optimization of the Kretschmann -based surface plasmon resonance sensor for lowest reflection, full width at half maximum, and glucose detection sensitivity, carried out using the WINSPALL software method. Using the Taguchi method, the best control factor setting is A1B2C3D3, which corresponds to an optical wavelength of 633 nm for Larger-is-better, between 3 nm chromium, 50 nm gold layer thickness and 20 nm for polymer, with a minimum reflection of 0.0050 percent, full width at the maximum half of 2.7136, and the glucose sensing sensitivity for It was also found that the chromium nanofilm thickness of 0.5–3 nm, as well as the average surface roughness of its roots, had a small factor influence when compared to other control variables. The optical wavelength, followed by the layer thickness, determines the effect of the full width factor at half the maximum. The optical wavelength, as well as the thickness of the water and glucose layers, determine the sensitivity. Compared to a wavelength near 785 nm, the Kretschmann -based surface plasmon resonance glucose sensor with the best glucose sensing sensitivity is at an optical wavelength of 633 nm with a higher sensitivity value of 183.8463. Finally, the WINSPALL software and the Taguchi approach are suitable for the multi -response optimization of control and noise parameters in Kretschmann -based surface plasmon resonance sensors.

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