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A Genetic Algorithm for Universal Optimization of Ultrasensitive Surface Plasmon Resonance Sensors with 2D Materials.
Sebek, Matej; Thanh, Nguyen Thi Kim; Su, Xiaodi; Teng, Jinghua.
Afiliación
  • Sebek M; Biophysics Group, Department of Physics and Astronomy, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
  • Thanh NTK; UCL Healthcare Biomagnetics and Nanomaterials Laboratories, 21 Albemarle Street, London W1S 4BS, United Kingdom.
  • Su X; Institute of Materials Research and Engineering, Agency for Science, Technology and Research, Innovis, Singapore 138634 Singapore.
  • Teng J; Biophysics Group, Department of Physics and Astronomy, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
ACS Omega ; 8(23): 20792-20800, 2023 Jun 13.
Article en En | MEDLINE | ID: mdl-37323412
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.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Omega Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Omega Año: 2023 Tipo del documento: Article País de afiliación: Reino Unido Pais de publicación: EEUU / ESTADOS UNIDOS / ESTADOS UNIDOS DA AMERICA / EUA / UNITED STATES / UNITED STATES OF AMERICA / US / USA