Improved particle swarm optimization algorithm for high performance SPRsensor design
Lei Han, Chaoyu Xu, Tianye Huang, Xueyan Dang
Abstract
The surface plasmon resonance (SPR) sensor offers high sensitivity, good stability, simple structure, and is label-free. However, optimizing a multi-layered structure is quite time-consuming within the SPR sensor design process. Moreover, it is easy to overlook optimal design when using the conventional parameter sweeping method. In this paper, the improved particle swarm optimization (IPSO) algorithm with high global optimal solution convergence speed is applied for this purpose. Based on the IPSO algorithm, the SPR sensor with transition metal dichalcogenides (TMDCs) and graphene composite is proposed and optimized. The results show that the best Ag-ITO- <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:msub> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">W</mml:mi> <mml:mi mathvariant="normal">S</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msub> </mml:math> -graphene hybrid structure can be found by the IPSO algorithm, and the maximum sensitivity is 137.4°/RIU, and the figure of merit (FOM) is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mn>5.25</mml:mn> <mml:mspace width="thickmathspace"/> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:msup> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">R</mml:mi> <mml:mi mathvariant="normal">I</mml:mi> <mml:mi mathvariant="normal">U</mml:mi> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo>−</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> . Compared with the standard particle swarm optimization algorithm, the number of iterations can be reduced. The development of the SPR sensor provides an optimization platform, which enormously improves the development efficiency of the multi-layer SPR sensor.