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Related Experiment Video

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Demonstrating a Multi-drug Resistant Mycobacterium tuberculosis Amplification Microarray

Demonstrating a Multi-drug Resistant Mycobacterium tuberculosis Amplification Microarray

Published on: April 25, 2014

Optimized design of a surface plasmon resonance biosensor for Mycobacterium tuberculosis detection using the

Mithun Bepare¹, Kowshik Kumar Roy¹, Simanta Das¹

¹Electrical & Electronic Engineering, Ahsanullah University of Science and Technology, Tejgaon, Dhaka, 1208, Bangladesh.

Mikrochimica Acta

|November 4, 2025

Summary

This study introduces a novel multilayer surface plasmon resonance (SPR) biosensor for detecting Mycobacterium tuberculosis. Optimized using a differential evolution algorithm, it achieves high sensitivity and a wide detection range for label-free analyte identification.

Keywords:

Biosensor Differential evolution (DE) algorithm Finite element method (FEM)Surface plasmon resonance (SPR)Transfer matrix method (TMM)Tuberculosis (TB)

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Area of Science:

Biosensing
Nanotechnology
Optical Physics

Background:

Mycobacterium tuberculosis detection remains a critical challenge in public health.
Surface plasmon resonance (SPR) biosensors offer label-free detection capabilities.
Optimizing multilayer structures is key to enhancing SPR biosensor performance.

Purpose of the Study:

To develop and optimize a novel multilayer SPR biosensor for sensitive Mycobacterium tuberculosis detection.
To investigate the impact of material composition and structural parameters on sensor performance.
To achieve a high-quality factor and broad refractive index detection range for versatile analyte identification.

Main Methods:

Fabrication of a multilayer structure comprising CaF2 prism, TiO2/Ag/TiO2, and black phosphorus (BP).
Optical property analysis using the transfer matrix method (TMM) and validation via finite element method (FEM) simulations.
Optimization of structural dimensions using the differential evolution (DE) algorithm.

Main Results:

The proposed SPR biosensor demonstrated a maximum angular sensitivity of 638°/RIU, improved to 654°/RIU after DE optimization.
Achieved a high quality factor of 176.9 RIU⁻¹, a minimum FWHM of 3.55°, and a peak SNR of 1.19.
The sensor exhibited a wide refractive index detection range (1.25-1.35), enabling precise, label-free detection of various analytes.

Conclusions:

The developed multilayer SPR biosensor, optimized with the DE algorithm, offers superior sensitivity and a broad detection range.
This design provides a promising platform for the accurate, label-free identification of Mycobacterium tuberculosis and other analytes.
The integration of advanced materials and optimization algorithms paves the way for next-generation biosensing technologies.