Applied Biochemistry and Biotechnology

, Volume 189, Issue 4, pp 1156–1166 | Cite as

Real-Time and Online Monitoring of Glucose Contents by Using Molecular Imprinted Polymer-Based IDEs Sensor

  • Nazia Asghar
  • Ghulam MustafaEmail author
  • Maimoona Yasinzai
  • Yaseen A. Al-Soud
  • Peter A. Lieberzeit
  • Usman LatifEmail author


A highly sensitive, selective, reversible, and reusable glucose sensor is developed by using molecularly imprinted polymer-based artificial receptors onto interdigital transducer. Sensor receptors were synthesized through bulk imprinting technology by using styrene as monomer, ethylene glycol dimethacrylate (EGDMA) as cross-linker, and AIBN as free radical initiator. Topography of the synthesized receptors was investigated by scanning electron microscopy (SEM). Fabricated sensor showed concentration-dependent linear and reversible response with lower limit of detection of 30 ppb and upper limit of detection ~ 500 ppm. Furthermore, newly fabricated sensor is highly selective towards its analyte of interest in the presence of other competing agents, and the regeneration of sensor response has been assessed with the percentage error of less than 2% under the period of 1 year at room temperature and pressure conditions. The reported sensor may have potential technological applications in the field of medical diagnostics, food, and pharmaceutical industry.


Molecular imprinted polymers Electrochemical sensors Glucose Sensitivity Selectivity Limit of detection 



Authors are thankful to Higher Education Commission of Pakistan, School of Materials Science and Engineering, University of Jinan (West Campus) Jinan, China and the Department of Chemistry, Al al-Bayt University Al-Mafraq, Jordan for their support in material testing.

Funding Statement

This work was supported financially by Higher Education Commission Pakistan, International Islamic University, Islamabad, Pakistan and OeAD Austria.

Data Availability Statement

The data used to support the findings of this study are included within the article.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.


  1. 1.
    Vargas, E., Ruiz, M. A., Campuzano, S., Reviejo, A. J., & Pingarrón, J. M. (2016). Noninvasive determination of glucose directly in raw fruits using a continuous flow system based on microdialysis sampling and amperometric detection at an integrated enzymatic biosensor. Analytica Chimica Acta, 914, 53–61.PubMedGoogle Scholar
  2. 2.
    Galant, A. L., Kaufman, R. C., & Wilson, J. D. (2015). Glucose: Detection and analysis. Food Chemistry, 188, 149–160.PubMedGoogle Scholar
  3. 3.
    Hong, X., Wang, J., & Qiu, S. (2014). Authenticating cherry tomato juices-discussion of different data standardization and fusion approaches based on electronic nose and tongue. Food Research International, 60, 173–179.Google Scholar
  4. 4.
    Vargas, E., Ruiz, M. A., Campuzano, S., Reviejo, A. J., & Pingarrón, J. M. (2016). Non-invasive determination of glucose directly in raw fruits using a continuous flow system based on microdialysis sampling and amperometric detection at an integrated enzymatic biosensor. Analytica Chimica Acta, 914, 53–61.PubMedGoogle Scholar
  5. 5.
    Shen, W., Sun, J., Seah, J. Y. H., Shi, L., Tang, S., & Lee, H. K. (2018). Needle-based sampling coupled with colorimetric reaction catalyzed by layered double hydroxide peroxidase mimic for rapid detection of the change of d-glucose levels with time in bananas. Analytica Chimica Acta, 1001, 32–39.PubMedGoogle Scholar
  6. 6.
    Surareungchai, W., Deepunya, W., & Tasakorn, P. (2001). Quadruple-pulsed amperometric detection for simultaneous flow injection determination of glucose and fructose. Analytica Chimica Acta, 448(1–2), 215–220.Google Scholar
  7. 7.
    Wu, Y., Wang, Q., Chen, M., Dong, C., Zhang, X., & Wang, S. (2016). An enzyme free potentiometric detection of reducing sugars based on a poly (3-hydroxyphenylboronic acid-co-phenol) molecularly imprinted polymer modified electrode. American Journal of Biomedical Sciences, 8.Google Scholar
  8. 8.
    Chen, X., Chen, J., Wang, F., Xiang, X., Luo, M., Ji, X., & He, Z. (2012). Determination of glucose and uric acid with bienzyme colorimetry on microfluidic paper-based analysis devices. Biosensors & Bioelectronics, 35(1), 363–368.Google Scholar
  9. 9.
    Gao, F., Luo, F., Chen, X., Yao, W., Yin, J., Yao, Z., & Wang, L. (2009). A novel nonenzymatic fluorescent sensor for glucose based on silica nanoparticles doped with europium coordination compound. Talanta, 80(1), 202–206.PubMedGoogle Scholar
  10. 10.
    Emran, M. Y., Mekawy, M., Akhtar, N., Shenashen, M. A., EL-Sewify, I. M., Faheem, A., & El-Safty, S. A. (2018). Broccoli-shaped biosensor hierarchy for electrochemical screening of noradrenaline in living cells. Biosens Bioelectrons, 100, 122–131.Google Scholar
  11. 11.
    Wahjudi, P. N., Patterson, M. E., Lim, S., Yee, J. K., Mao, C. S., & Lee, W.-N. P. (2010). Measurement of glucose and fructose in clinical samples using gas chromatography/mass spectrometry. Clinical Biochemistry, 43(1-2), 198–207.PubMedGoogle Scholar
  12. 12.
    Ma, C., Sun, Z., Chen, C., Zhang, L., & Zhu, S. (2014). Simultaneous separation and determination of fructose, sorbitol, glucose and sucrose in fruits by HPLC-ELSD. Food Chemistry, 145, 784–788.PubMedGoogle Scholar
  13. 13.
    Akhtar, N., El-Safty, S. A., Abdelsalam, M. E., Shenashen, M. A., & Kawarada, H. (2016). Radially oriented nanostrand electrodes to boost glucose sensing in mammalian blood. Biosens Bioelectrons, 77, 656–665.Google Scholar
  14. 14.
    Emran, M. Y., Khalifa, H., Gomaa, H., Shenashen, M. A., Akhtar, N., Mekawy, M., Faheem, A., & El-Safty, S. A. (2017). Hierarchical CN doped NiO with dual-head echinop flowers for ultrasensitive monitoring of epinephrine in human blood serum. Microchimica Acta, 184(11), 4553–4562.Google Scholar
  15. 15.
    Liao, S.-H., Lu, S.-Y., Bao, S.-J., Yu, Y.-N., & Wang, M.-Q. (2016). NiMoO4 nanofibres designed by electrospining technique for glucose electrocatalytic oxidation. Analytica Chimica Acta, 905, 72–78.PubMedGoogle Scholar
  16. 16.
    Cao, X., & Wang, N. (2011). A novel non-enzymatic glucose sensor modified with Fe2O3 nanowire arrays. Analyst, 136(20), 4241–4246.PubMedGoogle Scholar
  17. 17.
    Lu, W., Qin, X., Asiri, A. M., Al-Youbi, A. O., & Sun, X. (2013). Ni foam: a novel three dimensional porous sensing platform for sensitive and selective non enzymatic glucose detection. Analyst, 138(2), 417–420.PubMedGoogle Scholar
  18. 18.
    Choi, T., Kim, S. H., Lee, C. W., Kim, H., Choi, S.-K., Kim, S.-H., Kim, E., Park, J., & Kim, H. (2015). Synthesis of carbon nanotube-nickel nanocomposites using atomic layer deposition for high performance non-enzymatic glucose sensing. Biosensors and Bioelectronics, 63, 325–330.PubMedGoogle Scholar
  19. 19.
    Fischer, C., Fraiwan, A., & Choi, S. (2016). A 3D paper-based enzymatic fuel cell for self-powered, low-cost glucose monitoring. Biosensors and Bioelectronics, 79, 193–197.PubMedGoogle Scholar
  20. 20.
    Fathollahzadeh, M., Hosseini, M., Haghighi, B., Kolahdouz, M., & Fathipour, M. (2016). Fabrication of a liquid-gated enzyme field effect device for sensitive glucose detection. Analytica Chimica Acta, 924, 99–105.PubMedGoogle Scholar
  21. 21.
    Li, N., Hao, X., Kang, B. H., Xu, Z., Shi, Y., Li, N. B., & Luo, H. Q. (2016). Enzyme-free fluorescent biosensor for the detection of DNA based on core-shell Fe3O4 polydopamine nanoparticles and hybridization chain reaction amplification. Biosensors & Bioelectronics, 77, 525–529.Google Scholar
  22. 22.
    Kan, X., Li, C., Zhou, H., Zhu, A., Xing, Z., Zhao, Z., & Xu, G. (2012). Three dimensional ordered macroporous electrochemical sensor for dopamine recognition and detection. American Journal of Biomedical Sciences, 4, 184–193.Google Scholar
  23. 23.
    Hu, W., Fu, G., Kong, J., Zhou, S., Scafa, N., & Zhang, X. (2015). Advancement of nucleic acid biosensors based on Morpholino. American Journal of Biomedical Sciences, 7.Google Scholar
  24. 24.
    Kim, D.-M., Cho, S. J., Cho, C.-H., Kim, K. B., Kim, M.-Y., & Shim, Y.-B. (2016). Disposable allsolid state pH and glucose sensors based on conductive polymer covered hierarchical AuZn oxide. Biosensors & Bioelectronics, 79, 165–172.Google Scholar
  25. 25.
    Miao, F., Lu, X., Tao, B., Li, R., & Chu, P. K. (2016). Glucose oxidase immobilization platform based on ZnO nanowires supported by silicon nanowires for glucose biosensing. Microelectronic Engineering, 149, 153–158.Google Scholar
  26. 26.
    Myung, N., Kim, S., Lee, C., Kim, T., Rajeshwar, K. (2016). Facile synthesis of Pt-CuO Socie. 163, 180–184.Google Scholar
  27. 27.
    Thanh, T. D., Balamurugan, J., Hwang, J. Y., Kim, N. H., & Lee, J. H. (2016). In situ synthesis of graphene-encapsulated gold nanoparticle hybrid electrodes for non-enzymatic glucose sensing. Carbon, 98, 90–98.Google Scholar
  28. 28.
    Shackery, I., Patil, U., Pezeshki, A., Shinde, N. M., Kang, S., Im, S., & Jun, S. C. (2016). Copper hydroxide nanorods decorated porous graphene foam electrodes for non-enzymatic glucose sensing. Electrochimica Acta, 191, 954–961.Google Scholar
  29. 29.
    Wei, C., Cheng, C., Zhao, J., Wang, Z., Wu, H., Gu, K., Du, W., & Pang, H. (2015). Mesoporous ZnSNiS nanocomposites for nonenzymatic electrochemical glucose sensors. Chemistry Open, 4, 32–38.PubMedGoogle Scholar
  30. 30.
    Saraf, M., Natarajan, K., & Mobin, S. M. (2016). Non-enzymatic amperometric sensing of glucose by employing sucrose templated microspheres of copper oxide (CuO). Dalton Transactions, 45(13), 5833–5840.PubMedGoogle Scholar
  31. 31.
    Yang, T., Xu, J., Lu, L., Zhu, X., Gao, Y., Xing, H., Yu, Y., Ding, W., & Liu, Z. (2016). Copper nanoparticle/graphene oxide/single wall carbon nanotube hybrid materials as electrochemical sensing platform for nonenzymatic glucose detection. Journal of Electroanalytical Chemistry, 761, 118–124.Google Scholar
  32. 32.
    Syshchyk, O., Skryshevsky, V. A., Soldatkin, O. O., & Soldatkin, A. P. (2015). Enzyme biosensor systems based on porous silicon photoluminescence for detection of glucose, urea and heavy metals. Biosensors & Bioelectronics, 66, 89–94.Google Scholar
  33. 33.
    Joshi, N., Rawat, K., Solanki, P. R., & Bohidar, H. (2015). Enzyme-free and biocompatible nanocomposite based cholesterol sensor. Biochemical Engineering Journal, 102, 69–73.Google Scholar
  34. 34.
    Malitesta, C., Losito, I., & Zambonin, G. P. (1999). Molecularly imprinted electrosynthesized polymers: new materials for biomimetic sensors. Analytical Chemistry, 71(7), 13661370.Google Scholar
  35. 35.
    Farid, M. M., Goudini, L., Piri, F., Zamani, A., & Saadati, F. (2016). Molecular imprinting method for fabricating novel glucose sensor: Polyvinyl acetate electrode reinforced by MnO2/CuO loaded on graphene oxide nanoparticles. Food Chemistry, 194, 61–67.PubMedGoogle Scholar
  36. 36.
    Wu, G., & Zaman, M. H. (2015). Amperometric measurements of ethanol on paper with a glucometer. Talanta, 134, 194–199.PubMedGoogle Scholar
  37. 37.
    Zhuang, X., Tian, C., Luan, F., Wu, X., & Chen, L. (2016). One-step electrochemical fabrication of a nickel oxide nanoparticle/polyaniline nanowire/graphene oxide hybrid on a glassy carbon electrode for use as a non-enzymatic glucose biosensor. RSC Advances, 6, 9254192546.Google Scholar
  38. 38.
    Emran, M. Y., Shenashen, M. A., Morita, H., El-Safty, S. A. (2018). 3D-ridge stocked layers of nitrogen-doped mesoporous carbon nanosheets for ultrasensitive monitoring of dopamine released from PC12 cells under K+ stimulation. Advanced Healthcare Materials 1701459.Google Scholar
  39. 39.
    Kim, D. M., Moon, J. M., Lee, W. C., Yoon, J. H., Choi, C. S., & Shim, Y. B. (2017). A potentiometric non-enzymatic glucose sensor using a molecularly imprinted layer bonded on a conducting polymer. Biosensors & Bioelectronics, 91, 276–283.Google Scholar
  40. 40.
    Gupta, V. K., Yola, M. L., Özaltın, N., Atar, N., Üstündağ, Z., & Uzun, L. (2013). Molecular imprinted polypyrrole modified glassy carbon electrode for the determination of tobramycin. Electrochimica Acta, 112, 37–43.Google Scholar
  41. 41.
    Wen, T., Zhu, W., Xue, C., Wu, J., Han, Q., Wang, X., Zhou, X., & Jiang, H. (2014). Novel electrochemical sensing platform based on magnetic field-induced self-assembly of Fe3O4@ polyaniline nanoparticles for clinical detection of creatinine. Biosensors & Bioelectronics, 56, 180–185.Google Scholar
  42. 42.
    Zhu, W., Jiang, G., Xu, L., Li, B., Cai, Q., Jiang, H., & Zhou, X. (2015). Facile and controllable onestep fabrication of molecularly imprinted polymer membrane by magnetic field directed selfassembly for electrochemical sensing of glutathione. Analytica Chimica Acta, 886, 37–47.PubMedGoogle Scholar
  43. 43.
    Carrasco, S., Benito-Peña, E., Navarro-Villoslada, F., Langer, J., Sanz-Ortiz, M. N., Reguera, J., Liz-Marzán, L. M., & Moreno-Bondi, M. C. (2016). Multi-branched gold-mesoporous silica nanoparticles coated with molecularly imprinted polymer for label-free antibiotic SERS analysis. Chemistry of Materials, 28(21), 7947–7954.Google Scholar
  44. 44.
    Kupis-Rozmysłowicz, J., Wagner, M., Bobacka, J., Lewenstam, A., & Migdalski, J. (2016). Biomimetic membranes based on molecularly imprinted conducting polymers as a sensing element for determination of taurine. Electrochimica Acta, 188, 537–544.Google Scholar
  45. 45.
    Uzun, L., & Turner, A. P. (2016). Molecularly-imprinted polymer sensors: realising their potential. Biosensors and Bioelectronics, 76, 131–144.PubMedGoogle Scholar
  46. 46.
    Zhu, W., Xu, L., Zhu, C., Li, B., Xiao, H., Jiang, H., & Zhou, X. (2016). Magnetically controlled electrochemical sensing membrane based on multifunctional molecularly imprinted polymers for detection of insulin. Electrochimica Acta, 218, 91–100.Google Scholar
  47. 47.
    Ghani, N. T. A., El Nashar, R. M., Abdel-Haleem, F. M., Madbouly, A. (2016). Computational Design, Synthesis and application of a new selective molecularly imprinted polymer for electrochemical detection. Electroanalysis.Google Scholar
  48. 48.
    Cernat, A., Tertiș, M., Fritea, L., & Cristea, C. (2016). Graphene in sensors design. In Advanced 2D Materials (pp. 387-432). Scrivener Publishing and co-published with John Wiley & Sons USA.Google Scholar
  49. 49.
    Iqbal, N., Mustafa, G., & Lieberzeit, P. A. (2013). Mass sensitive multi-sensor platform for receptor screening and quantification purposes. Journal of the Chinese Advanced Materials Society, 1(3), 200–209.Google Scholar
  50. 50.
    Latif, U., Mujahid, A., Afzal, A., Sikorski, R., Lieberzeit, P. A., & Dickert, F. L. (2011). Dual and tetraelectrode QCMs using imprinted polymers as receptors for ions and neutral analytes. Analytical and Bioanalytical Chemistry, 400(8), 2507–2515.PubMedGoogle Scholar
  51. 51.
    Cheng, Z., Wang, E., & Yang, X. (2001). Capacitive detection of glucose using molecularly imprinted polymers. Biosensors and Bioelectronics, 16(3), 179–185.PubMedGoogle Scholar
  52. 52.
    Yang, Y., Yi, C., Luo, J., Liu, R., Liu, J., Jiang, J., & Liu, X. (2011). Glucose sensors based on electrodeposition of molecularly imprinted polymeric micelles: a novel strategy for MIP sensors. Biosensors and Bioelectronics, 26(5), 2607–2612.PubMedGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Sulaiman Bin Abdullah Aba Al-Khail Centre for Interdisciplinary Research in Basic Sciences (SA-CIRBS) Faculty of Basic and Applied SciencesInternational Islamic UniversityIslamabadPakistan
  2. 2.Department of Physical ChemistryUniversity of ViennaViennaAustria
  3. 3.Department of Chemistry, Faculty of ScienceAl al-Bayt UniversityAl-MafraqJordan
  4. 4.Interdisciplinary Research Centre in Biomedical MaterialsCOMSATS University IslamabadLahorePakistan

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