Multi-response optimization of chromium/gold-based nanofilm Kretschmann-based surface plasmon resonance glucose sensor using finite-difference time-domain and Taguchi method

Publication year: 2020
Authors: Najmiah Radiah Mohamad 1,2, Mohd Farhanulhakim Mohd Razip Wee 1, Mohd Ambri Mohamed 1, Azrul Azlan Hamzah 1, P Susthitha Menon 1

1 - Institute of Microengineering and Nanoelectronics (IMEN), Universiti Kebangsaan Malaysia (UKM), Selangor, Malaysia
2 - Centre for Telecommunication Research & Innovation (CeTRI), Fakulti Teknologi Kejuruteraan Elektrik dan Elektronik (FTKEE), Universiti Teknikal Malaysia Melaka (UTeM), Melaka, Malaysia

Published in: Nanomaterials and Nanotechnology, 2020, Vol. 10
doi: 10.1177/1847980420982119

Kretschmann-based surface plasmon resonance sensor utilizing chromium and gold nanofilms is ideal for label-free biomedical sensing. In this work, Taguchi’s L9 orthogonal array method was used to optimize the effects of three control factors and noise factor, which are the incident optical wavelength, chromium and gold nanofilm thicknesses, and their root-mean-square surface roughness, on the performance of the Kretschmann-based surface plasmon resonance sensor. The control factors were varied at three levels for a novel multi-response optimization of the Kretschmann-based surface plasmon resonance sensor for the minimum reflectivity, the full-width-at-half-maximum, and the sensitivity of 3% glucose detection, executed using Lumerical’s two-dimensional finite-difference time-domain method. Using Taguchi method, the best control factor setting in air was A3B2C2 corresponding to 785 nm optical wavelength, 0.5 nm chromium, and 50 nm gold layer thickness, respectively, with minimum reflectivity of 0.0017%, full-width-at-half-maximum of 0.4759°, and glucose-sensing sensitivity of 106.73°·RIU−1. The detection accuracy and quality factor were 0.01 and 224.26 RIU−1, respectively. It was also indicated that chromium nanofilm thickness of 0.5–3 nm and its root-mean-square surface roughness has a negligible factor effect compared to other control factors. Taguchi method’s factor effect analysis showed that for chromium layer thickness of 1–3 nm, the minimum reflectivity values are predominantly determined by the gold layer thickness with 75% factor effect, followed by optical wavelength with 11%. Factor effect of full-width-at-half-maximum is determined by optical wavelength (57%), followed by gold layer thickness (38%). Sensitivity is 88% determined by optical wavelength and 10% determined by gold layer thickness. The Kretschmann-based surface plasmon resonance glucose sensor with the best glucose-sensing sensitivity was at optical wavelength of 632.8 nm with a higher sensitivity value of 163.415°·RIU−1 but lower detection accuracy and quality factor values of 0.001 and 24.86 RIU−1, respectively, compared to near-infrared wavelength of 785 nm. In conclusion, finite-difference time-domain and Taguchi method is suitable for multi-response optimization of control and noise factors of Kretschmann-based surface plasmon resonance sensors.

MP-SPR keywords: Au sensor slide, biosensor development, sensitivity, signal-to-noise