LSPR-susceptible metasurface platform for spectrometer-less and AI-empowered diagnostic biomolecule detection.

Journal: Analytica chimica acta
PMID:

Abstract

In response to the growing demand for biomolecular diagnostics, metasurface (MS) platforms based on high-Q resonators have demonstrated their capability to detect analytes with smart data processing and image analysis technologies. However, high-Q resonator meta-atom arrays are highly sensitive to the fabrication process and chemical surface functionalization. Thus, spectrum scanning systems are required to monitor the resonant wavelength changes at every step, from fabrication to practical sensing. In this study, we propose an innovative dielectric resonator-independent MS platform that enables spectrometer-less biomolecule detection using artificial intelligence (AI) at a visible wavelength. Functionalizing the focused vortex MS to capture gold nanoparticle (AuNP)-based sandwich immunoassays causes the resulting vortex beam profiles to be significantly affected by the localized surface plasmon resonance (LSPR) occurring between AuNPs and meta-atoms. The convolutional neural network algorithm was carefully trained to accurately classify the AuNP concentration-dependent focused vortex beam, facilitating the determination of the concentration of the targeted diagnostic biomolecule. Successful in situ identification of various biomolecule concentrations was achieved with over 99 % accuracy, indicating the potential of combining an LSPR-susceptible MS platform and AI for continuously tracking various chemical and biological compounds.

Authors

  • Jinke Li
    Guangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
  • Jin Tae Kim
    Quantum Technology Research Department, Electronics and Telecommunications Research Institute, Daejeon, 34129, Republic of Korea. Electronic address: jintae@etri.re.kr.
  • Hongliang Li
  • Hyo-Young Cho
    Digital Biomedical Research Division, Electronics and Telecommunications Research Institute, Daejeon, 34129, Republic of Korea.
  • Jin-Soo Kim
    Department of Chemistry, Seoul National University and Center for Genome Engineering, Institute for Basic Science, Seoul, South Korea. jskim01@snu.ac.kr.
  • Duk-Yong Choi
    Department of Quantum Science and Technology, Research School of Physics, Australian National University, Canberra, ACT, 2601, Australia.
  • Chenxi Wang
    Laboratory of Cell Engineering, Institute of Biotechnology, Research Unit of Cell Death Mechanism, Chinese Academy of Medical Science, 2021RU008, Beijing 100071, China.
  • Sang-Shin Lee
    Department of Electronic Engineering, Kwangwoon University, Seoul, 01897, Republic of Korea; Nano Device Application Center, Kwangwoon University, Seoul, 01897, Republic of Korea. Electronic address: slee@kw.ac.kr.