SpringerLink
Log in

Optical Biosensor Based on Surface Plasmon Resonance Nanostructure for the Detection of Mycobacterium Tuberculosis Bacteria with Ultra-High Efficiency and Detection Accuracy

  • RESEARCH
  • Published:
Plasmonics Aims and scope Submit manuscript

Abstract

Mycobacterium tuberculosis bacteria is an illness that affects many people worldwide. Early diagnosis is crucial for patient care and can lower the death rate. As a result, sensitive and rapid detection of mycobacterium tuberculosis bacteria in the blood is crucial. In this paper, a novel surface plasmon resonance (SPRE) sensor consisting of a coupling prism, silver (Ag), barium titanate (BaTiO3) and graphene (Gr) layers is presented. The transfer matrix (TM) technique is used for the analysis of the SPRE structure. The Ag and BaTiO3 thicknesses and the number of Gr sheets are optimized to get the highest sensitivity of the proposed SPRE biosensor. The full width at half maximum (FWHM), detection accuracy (DA) and figure of merit (FOM) are investigated. The best performance has been obtained with 65 nm (Ag), and 9 nm (BaTiO3). The number of Gr layers is investigated and optimized to two layers. The highest sensitivity of 300 deg./RIU has been obtained for the proposed SPRE biosensor when the optimized thicknesses are employed. Compared with existing SPRE biosensors in the literature, the proposed sensor exhibits greater sensitivity. The excellent performance makes this SPRE-based sensor promising to be used in numerous biosensing applications.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Availability of Data and Material

Detail about data has been provided in the article.

Code Availability

The used code can be obtained from the corresponding author upon request.

References

  1. World Health Organization (2022) Global Tuberculosis Report 2022. WHO, Geneva, Switzerland

    Google Scholar 

  2. Houben RMGJ, Dodd PJ (2016) The Global Burden of Latent Tuberculosis Infection: A Re-estimation Using Mathematical Modelling. PLoS Med 13:e1002152

    Article  PubMed  PubMed Central  Google Scholar 

  3. Hrizi O, Gasmi K, Ben Ltaifa I, Alshammari H, Karamti H, Krichen M, Ben Ammar L, Mahmood MA (2022) Tuberculosis Disease Diagnosis Based on an Optimized Machine Learning Model. J Healthc Eng 8950243

  4. Sahu S, Wandwalo E, Arinaminpathy N (2022) Exploring the Impact of the COVID-19 Pandemic on Tuberculosis Care and Prevention. J Pediatric Infect Dis Soc 11:S67–S71

    Article  PubMed  Google Scholar 

  5. Wang CH, Chang JR, Hung SC, Dou HY, Lee GB (2022) Rapid molecular diagnosis of live Mycobacterium tuberculosis on an integrated microfluidic system. Sensor Actuat B-Chem 365:131968

    Article  CAS  Google Scholar 

  6. Azadi D, Motallebirad T, Ghaffari K, Shojaei H (2018) Mycobacteriosis and Tuberculosis: Laboratory Diagnosis. Open Microbiol J 12:41–58

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Soini H, Musser JM (2001) Molecular diagnosis of mycobacteria. Clin Chem 47:809–814

    Article  CAS  PubMed  Google Scholar 

  8. Vilcheze C, Kremer L (2017) Acid-Fast Positive and Acid-Fast Negative Mycobacterium tuberculosis: The Koch Paradox. Microbiol Spectr 5:1–14

    Article  Google Scholar 

  9. Pande T, Cohen C, Pai M, Khan FA (2016) Computer-aided detection of pulmonary tuberculosis on digital chest radiographs: A systematic review. Int J Tuberc Lung D 20:1226–1230

    Article  CAS  Google Scholar 

  10. Mustafa F, Andreescu S (2018) Chemical and biological sensors for food-quality monitoring and smart packaging. J Food Sci Technol 49(4):383–406

    Google Scholar 

  11. Bhatia S, Jiang YC, Sun MJ, **ong RJ (2018) Development of a surface plasmon resonance acetone sensor for noninvasive screening and monitoring of diabetes. Mater Sci Eng 383:012024

    Google Scholar 

  12. Srivastava A, Prajapati YK (2019) Performance Analysis of Silicon and Blue Phosphorene / MoS 2 Hetero-Structure Based SPRE Sensor. Photonic Sens 9(3):284–292

    Article  CAS  Google Scholar 

  13. De Melo AA, Brito T, Fernanda M, Moreira S, Moreno R, Cruz S (2018) Theoretical analysis of sensitivity enhancement by graphene usage in optical Fiber surface plasmon resonance sensors. IEEE Trans Instrum Meas 68(5):1554–1560

    Article  Google Scholar 

  14. Pal A, Jha A (2021) A theoretical analysis on sensitivity improvement of an SPRE refractive index sensor with graphene and barium titanate nanosheets. Optik - International Journal for Light and Electron Optics 231:166378

    Article  CAS  Google Scholar 

  15. Bhardwaj S, Pathak NK, Ji A et al (2017) Tunable Properties of Surface Plasmon Resonance of Metal Nanospheroid: Graphene Plasmon Interaction. Plasmonics 12:193–201. https://doi.org/10.1007/s11468-016-0249-7

    Article  CAS  Google Scholar 

  16. Arsalani S, Ghodselahi T, Neishaboorynejad T et al (2019) DNA Detection Based on Localized Surface Plasmon Resonance Spectroscopy of Ag@Au Biocomposite Nanoparticles. Plasmonics 14:1419–1426. https://doi.org/10.1007/s11468-019-00937-6

    Article  CAS  Google Scholar 

  17. Alaguvibisha G et al (2020) Sensitivity enhancement of surface plasmon resonance sensor using hybrid configuration of 2D materials over bimetallic layer of Cu-Ni. Opt Commun 463:125337

    Article  CAS  Google Scholar 

  18. Vahedi A, Kouhi M (2020) Liquid crystal-based surface plasmon BiosensorResonance. Plasmonics 15:61–71

    Article  CAS  Google Scholar 

  19. Song B, Li D, Qi W, Elstner M, Fan C, Fang H (2010) Graphene on Au (111): A Highly Conductive Material with Excellent Adsorption Properties for High-Resolution Bio / Nanodetection and Identification. ChemPhysChem 19(111):585–589

    Article  Google Scholar 

  20. Papageorgiou DG, Kinloch IA, Young RJ (2017) Progress in Materials Science Mechanical properties of graphene and graphene-based nanocomposites. Prog Mater Sci 90:75–127

    Article  CAS  Google Scholar 

  21. Reina G, Gonz´ alez-Domínguez JM, Criado A, V´ azquez E, Bianco A, Prato M (2017) Promises, facts and challenges for graphene in biomedical applications. Chem Soc Rev 46(15):4400–4416

  22. Aksimsek S, Jussila H, Sun Z (2018) Graphene – MoS 2 – metal hybrid structures for plasmonic biosensors. Opt Commun 428:233–236

    Article  CAS  Google Scholar 

  23. Dai X, Liang Y, Zhao Y, Gan S, Jia Y, **ang Y (2019) Sensitivity enhancement of a surface plasmon resonance with tin selenide (SnSe) allotropes. Sensors 19(1):173

    Article  PubMed  PubMed Central  Google Scholar 

  24. Gan S, Zhao Y, Dai X, **ang Y (2019) Sensitivity enhancement of surface plasmon resonance sensors with 2D franckeite nanosheets. Results Phys 13:102320

    Article  Google Scholar 

  25. Nisha A, Maheswari P, Anbarasan PM, Rajesh KB, Jaroszewicz Z (2019) Sensitivity enhancement of surface plasmon resonance sensor with 2D material covered noble and magnetic material (Ni). Opt Quantum Electron 51(1)

  26. Singh Y, Raghuwanshi SK (2019) Electromagnetic wave sensors sensitivity enhancement of the surface plasmon resonance gas sensor with black phosphorus. IEEE Sensors Lett 3(12):1–4

    Article  CAS  Google Scholar 

  27. Pal S, Verma A, Saini JP, Prajapati YK (2019) Sensitivity enhancement using silicon-black phosphorus-TDMC coated surface plasmon resonance biosensor. IET Optoelectron 13(4):196–201

    Article  Google Scholar 

  28. Singh Y, Paswan MK, Raghuwanshi SK (2020) Sensitivity enhancement of SPRE sensor with the black phosphorus and graphene with Bi-layer of gold for chemical sensing. Plasmonics

  29. Ball JP, Mound BA, Nino JC, Allen JB (2014) Biocompatible evaluation of barium titanate foamed ceramic structures for orthopedic applications. J Biomed Mater Res - Part A 102(7):2089–2095

    Article  Google Scholar 

  30. Marino A et al (2019) Piezoelectric barium titanate nanostimulators for the treatment of glioblastoma multiforme. J Colloid Interface Sci 538:449–461

    Article  CAS  PubMed  Google Scholar 

  31. Mudgal N, Saharia A, Choure KK et al (2020) Sensitivity enhancement with anti-reflection coating of silicon nitride (Si3N4) layer in silver-based Surface Plasmon Resonance (SPR) sensor for sensing of DNA hybridization. Appl Phys A 126:946. https://doi.org/10.1007/s00339-020-04126-9

    Article  CAS  Google Scholar 

  32. Mudgal N, Yupapin P, Ali J et al (2020) BaTiO3-Graphene-Affinity Layer-Based Surface Plasmon Resonance (SPR) Biosensor for Pseudomonas Bacterial Detection. Plasmonics 15:1221–1229. https://doi.org/10.1007/s11468-020-01146-2

    Article  CAS  Google Scholar 

  33. Wang S, Zhang J, Liu N et al (2023) Sensitivity Improvement of Bimetallic Layer-Based SPR Biosensor Using ZnO and Black Phosphorus. Plasmonics. https://doi.org/10.1007/s11468-023-01889-8

    Article  Google Scholar 

  34. Lin Z, Jiang L, Wu L, Guo J, Dai X, **ang Y, Fan D (2016) Tuning and sensitivity enhancement of surface plasmon resonance biosensor with graphene covered Au MoS2-Au films. IEEE Photon J 8(6):1–8

    Article  Google Scholar 

  35. Sun P, Wang M, Liu L, Jiao L, Wei Du, **a F, Liu M, Kong W, Dong L, Yun M (2019) Sensitivity enhancement of surface plasmon resonance biosensor based on graphene and barium titanate layers. Appl Surf Sci 475:342–347

    Article  CAS  Google Scholar 

  36. Bruna M, Borini S (2009) Optical constants of graphene layers in the visible range. Appl Phys Lett 94(3):03190

    Article  Google Scholar 

  37. Reddy NM, Kothandan D, Lingam SC, Ahmad A (2012) A study on refractive index of plasma of blood of patients suffering from tuberculosis. Int J Technol Eng 8:23–25

    Google Scholar 

  38. Lin C, Chen S (2019) Design of high-performance Au-Ag-dielectric-graphene based surface plasmon resonance biosensors using genetic algorithm. J Appl Phys 125:113101

    Article  Google Scholar 

  39. Lin C, Chen S (2019) Sensitivity comparison of graphene based nearly guided-wave surface plasmon resonance biosensors with Au, Ag, Cu, and Al. J Nanophotonics 13:016006

    Article  CAS  Google Scholar 

  40. Maharana PK, Jha R (2012) Chalcogenide prism and graphene multilayer based surface plasmon resonance affinity biosensor for high performance. Sens Actuat B Chem 169:161–166

    Article  CAS  Google Scholar 

  41. Hossain MB, Mehedi IM, Moznuzzaman M, Abdulrazak LF, Hossain MA (2019) High performance refractive index SPRE sensor modeling employing graphene tri sheets, Vol. 15, Results in Physics, p. 102719

  42. Pal S, Prajapati YK, Saini JP (2020) Influence of grapheme’chemical potential on SPRE biosensor using ZnO for DNA hybridization, Vol. 27, Optical Review, pp. 57–64

  43. Singh S, Sharma AK, Lohia P, Dwivedi DK (2021) Theoritical analysis of sensitivity enhancement of surface plasmon resonance biosensor with zinc oxide and blue phosphorus/MoS2 heterostructure, Vol. 244, Optik, p. 167618

  44. Almawgani AHM, Daher MG, Taya SA, Olaimat MM, Alhawari ARH, Colak I (2022) Detection of blood plasma concentration theoretically using SPR-based biosensor employing black phosphor layers and different metals. Plasmonics 17(4):1751–1764

  45. Taya SA, Al-Ashi NE, Ramahi OM, Colak I, Amiri IS (2021) Surface plasmon resonance-based optical sensor using a thin layer of plasma. J Opt Soc Am B 38(8):2362–2367. https://doi.org/10.1364/JOSAB.420129

  46. Hsu SH, Lin YY, Lu SH, Tsai IF, Lu YT, Ho HT (2013) Mycobacterium tuberculosis DNA detection using surface plasmon resonance modulated by telecommunication wavelength. Sensors (Basel) 14(1):458–467. https://doi.org/10.3390/s140100458. PMID: 24379050; PMCID: PMC3926568

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Kaur B, Kumar S, Kaushik BK (2022) Antimonene, CNT and MoS2 Based SPR-Fiber-Optic Probe for Tuberculosis Detection. IEEE Sens J 22(15):14903–14910. https://doi.org/10.1109/JSEN.2022.3186995

Download references

Acknowledgements

The authors are thankful to the Deanship of Scientific Research at Najran University for funding this work under the Research Groups Funding program grant code (NU/RG/SERC/12/4).

Funding

Deanship of Scientific Research at Najran University.

Author information

Authors and Affiliations

  1. Physics Department, Islamic University of Gaza, P.O. Box 108, Gaza, Palestine

    Malek G. Daher & Sofyan A. Taya

  2. Electrical Engineering Department, College of Engineering, Najran University, Najran, Kingdom of Saudi Arabia

    Abdulkarem H. M. Almawgani & Ayman Taher Hindi

  3. Department of Electrical and Electronics Engineering, Nisantasi University, Istanbul, Turkey

    Ilhami Colak

  4. Department of Computer Engineering, Marwadi University, Rajkot-360003, India

    Shobhit K. Patel

Authors
  1. Malek G. Daher
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sofyan A. Taya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Abdulkarem H. M. Almawgani
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ayman Taher Hindi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ilhami Colak
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shobhit K. Patel
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The authors confirm their contribution to the paper as follows: study conception and design (Sofyan A. Taya and Malek G. Daher). Software (Abdulkarem H. M. Almawgani). Interpretation of results (Malek G. Daher and Ilhami Colak). Draft manuscript preparation (Ayman Taher Hindi and Malek G. Daher). Writing the final version (Shobhit K. Patel and Sofyan). Supervision (Sofyan A. Taya). All authors reviewed the results and approved the final version of the manuscript.

Corresponding author

Correspondence to Sofyan A. Taya.

Ethics declarations

Ethics Approval

This study does not require ethics approval.

Consent to Participate

No consent to participate is required for this study.

Consent for Publication

No consent for publication is required for this study.

Conflicts of Interest

The authors declare no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Daher, M.G., Taya, S.A., Almawgani, A.H.M. et al. Optical Biosensor Based on Surface Plasmon Resonance Nanostructure for the Detection of Mycobacterium Tuberculosis Bacteria with Ultra-High Efficiency and Detection Accuracy. Plasmonics 18, 2195–2204 (2023). https://doi.org/10.1007/s11468-023-01938-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11468-023-01938-2

Keywords

Search

Navigation