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A Genetic Algorithm for Universal Optimization of Ultrasensitive Surface Plasmon Resonance Sensors with 2D Materials.

ABSTRACT: We present a general optimization technique for surface plasmon resonance, (SPR) yielding a range of ultrasensitive SPR sensors from a materials database with an enhancement of ∼100%. Applying the algorithm, we propose and demonstrate a novel dual-mode SPR structure coupling SPP and a waveguide mode within GeO₂ featuring an anticrossing behavior and an unprecedented sensitivity of 1364 deg/RIU. An SPR sensor operating at wavelengths of 633 nm having a bimetal Al/Ag structure sandwiched between hBN can achieve a sensitivity of 578 deg/RIU. For a wavelength of 785 nm, we optimized a sensor as a Ag layer sandwiched between hBN/MoS₂/hBN heterostructures achieving a sensitivity of 676 deg/RIU. Our work provides a guideline and general technique for the design and optimization of high sensitivity SPR sensors for various sensing applications in the future.

SUBMITTER: Sebek M

PROVIDER: S-EPMC10268016 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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A Genetic Algorithm for Universal Optimization of Ultrasensitive Surface Plasmon Resonance Sensors with 2D Materials.

Sebek Matej M Thanh Nguyen Thi Kim NTK Su Xiaodi X Teng Jinghua J

ACS omega 20230526 23

We present a general optimization technique for surface plasmon resonance, (SPR) yielding a range of ultrasensitive SPR sensors from a materials database with an enhancement of ∼100%. Applying the algorithm, we propose and demonstrate a novel dual-mode SPR structure coupling SPP and a waveguide mode within GeO<sub>2</sub> featuring an anticrossing behavior and an unprecedented sensitivity of 1364 deg/RIU. An SPR sensor operating at wavelengths of 633 nm having a bimetal Al/Ag structure sandwiche ...[more]

PMID: 37323412

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