Trung-Tan Tran1,2, Gia-Tuyen Phan1,2, Tan-Dat Nguyen1,2, Hoang-Phat Nguyen1,2, Ha-Nhat-Nghi Pham1,2, Van Hoang Luan1,2, and Minh-Vien Le1,2This email address is being protected from spambots. You need JavaScript enabled to view it.

1Faculty of Chemical Engineering, Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City 700000, Vietnam

2Vietnam National University Ho Chi Minh City, Ho Chi Minh City 700000, Vietnam

 

 

Received: February 18, 2025
Accepted: March 31, 2025
Publication Date: April 30, 2025

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.6180/jase.202601_29(1).0004  


The shape and morphology of nanostructures play a crucial role in determining their electrochemical performance, offering a promising strategy for enhancing glucose sensing capabilities through structural optimization. In this study, a novel three-dimensional porous cobalt oxide (Co3O4) nanorod-like structure was synthesized via a facile hydrothermal method and investigated as an efficient catalyst for glucose detection. The influence of hydrothermal temperature on the morphology and electrochemical properties of the synthesized materials was systematically examined. Comprehensive characterization techniques were employed to analyze the composition and crystal structure of the samples. Electrochemical performance, particularly glucose oxidation activity, was assessed using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and amperometry. The optimized 3D porous Co3O4 nanorod-like structures exhibited outstanding glucose sensing performance, featuring a broad linear detection range from 0 to 2.0 mM , high sensitivity of 343 µA·mM−1· cm−2, and a low detection limit of 0.251 µM. These findings underscore the potential of the synthesized Co3O4 nanorods as highly sensitive materials for advanced electrochemical glucose detection applications.

 


Keywords: cobalt oxide; glucose sensor; nanocomposite; nanorods-like; non-enzymatic


  1. [1] K.V.Jarnda, D.Wang,R.Anaman,V.E.Johnson,G.P. Roberts, P. S. Johnson, B. W. Jallawide Jr, T. Kai, P. Ding, et al., (2023) “Recent advances in electrochemical non-enzymatic glucose sensor for the detection of glucose in tears and saliva: A Review" Sensors and Actuators A: Physical 363: 114778. DOI: 10.1016/j.sna.2023.114778.
  2. [2] M. Thomas, (2022) “The clustering of cardiovascular, renal, adipo-metabolic eye and liver disease with type 2 diabetes" Metabolism 128: 154961. DOI: 10.1016/j.metabol.2021.154961.
  3. [3] H. Liang, Y. Luo, Y. Xiao, R. Chen, L. Wang, and Y. Song, (2024) “Ni/NiO/carbon derived from covalent organic frameworks for enzymatic-free electrochemical glucose sensor" Ceramics International 50(1): 977–984. DOI: 10.1016/j.ceramint.2023.10.188.
  4. [4] H.Imanzadeh, M. Amiri, and M. Nozari-Asbemarz, (2024) “A novel NiO/C@ rGO nanocomposite derived from Ni (gallate): A non-enzymatic electrochemical glu cose sensor" Microchemical Journal 199: 110106. DOI: 10.1016/j.microc.2024.110106.
  5. [5] S. Yadav, N. Rani, and K. Saini, (2024) “Fabrication of α-Fe2O3/rGO nanocomposite and its study for electro chemical glucose sensor and supercapacitor application" Diamond and Related Materials 142: 110707. DOI: 10.1016/j.diamond.2023.110707.
  6. [6] H.Miao, Z.Yang, J. Lv, and C. Kong, (2024) “Development of Cu2O-Cu-ZnO ternary nanocomposites for high performance photoelectrochemical non-enzymatic glucose sensor" Surfaces and Interfaces 46: 104195. DOI: 10.1016/j.surfin.2024.104195.
  7. [7] J.Zhang, Q.Xiong, and J.Xu,(2024)“Researchprogress in non-precious metal oxide/compound-based electrodes for non-enzymatic electrochemical glucose sensor applications" Materials Science in Semiconductor Processing 181: 108643. DOI: 10.1016/j.mssp.2024.108643.
  8. [8] S. K. Godlaveeti, S. K. Arla, A. El-marghany, A. R. Somala, V. K. N. Boya, R.R.Nagireddy, and S.W.Joo, (2024) “Nanostructured 3-D nano-bricks shaped CuO 0-D particle shaped Co3O4 composite for superior photo electrochemical water splitting" International Journal of Hydrogen Energy 58: 1000–1008. DOI: 10.1016/j.ijhydene.2024.01.177.
  9. [9] R. Subagyo, A. Yudhowijoyo, N. A. Sholeha, S. S. Hutagalung, D. Prasetyoko, M. D. Birowosuto, A. Arramel, J. Jiang, and Y. Kusumawati, (2023) “Re cent advances of modification effect in Co3O4-based cata lyst towards highly efficient photocatalysis" Journal of Colloid and Interface Science 650: 1550–1590. DOI: 10.1016/j.jcis.2023.07.117.
  10. [10] S. L. Jadhav, A. L. Jadhav, P. B. Sarawade, B. K. Man dlekar, and A. V. Kadam, (2024) “Mo-doped porous Co3O4 nanoflakes as an electrode with the enhanced ca pacitive contribution for asymmetric supercapacitor ap plication" Journal of Energy Storage 82: 110540. DOI: 10.1016/j.est.2024.110540.
  11. [11] P.-P. Chen, H.-B. Guan, B.-H. Zhang, J.-T. Lei, Z.-A. Li, Y.-L. Hou, J.-Z. Chen, and D.-L. Zhao, (2024) “Graphene encapsulated NiO-Co3O4 open-ended hol low nanocube anode with enhanced performance for lithium/sodium ion batteries" Journal of Alloys and Compounds979: 173479. DOI: 10.1016/j.jallcom.2024. 173479.
  12. [12] J. Yi, X. Li, S. Lv, J. Zhu, Y. Zhang, X. Li, and Y. Cong, (2023) “MOF-derived CeO2/Co3O4–Fe2O3@ CC nanocomposites as highly sensitive electrochemical sensor for bisphenol A detection" Chemosphere 336: 139249. DOI: 10.1016/j.chemosphere.2023.139249.
  13. [13] M. Shandilya, R. Rai, and J. Singh, (2016) “Hy drothermal technology for smart materials" Advances in Applied Ceramics 115(6): 354–376. DOI: 10.1080/17436753.2016.1157131.
  14. [14] N.K. Yetim, (2021) “Hydrothermal synthesis of Co3O4 with different morphology: Investigation of magnetic and electrochemical properties" Journal of Molecular Structure 1226: 129414. DOI: 10.1016/j.molstruc.2020.129414.
  15. [15] X. Lin, Y. Wang, M. Zou, T. Lan, and Y. Ni, (2019) “Electrochemical non-enzymatic glucose sensors based on nano-composite of Co3O4 and multiwalled carbon nanotube" Chinese Chemical Letters 30(6): 1157–1160. DOI: 10.1016/j.cclet.2019.04.009.
  16. [16] V. Archana, Y. Xia, R. Fang, and G. Gnana Kumar, (2019) “Hierarchical CuO/NiO-carbon nanocomposite derived from metal organic framework on cello tape for the flexible and high performance nonenzymatic electro chemical glucose sensors" ACS Sustainable Chemistry & Engineering 7(7): 6707–6719. DOI: 10.1021/acssuschemeng.8b05980.
  17. [17] A. Mustafa, I. A. Alsafari, H. Somaily, S. Yousaf, M. I. Din, J. Rahman, M. Shahid, M. Ashraf, and M.F.Warsi,(2023)“Fabrication, characterization of NiO Co3O4/rGO based nanohybrid and application in the de velopment of non-enzymatic glucose sensor" Physica B: CondensedMatter648:414404. DOI:10.1016/j.physb.2022.414404.
  18. [18] B. A. Hussein, A. A. Tsegaye, G. Shifera, and A. M. Taddesse, (2023) “A sensitive non-enzymatic electro chemical glucose sensor based on a ZnO/Co3O4/reduced graphene oxide nanocomposite" Sensors & Diagnostics 2(2): 347–360. DOI: 10.1039/D2SD00183G.
  19. [19] I. Liaqat, N. Iqbal, M. Aslam, M. Nasir, A. Hayat, D. X. Han, L. Niu, and M. H. Nawaz, (2020) “Co3O4 nanocubes decorated single-walled carbon nanotubes for efficient electrochemical non-enzymatic glucose sensing" SN Applied Sciences 2: 1–12. DOI: 10.1007/s42452 020-03531-2.
  20. [20] T.Yuwen, D.Shu, H.Zou, X.Yang, S.Wang, S.Zhang, Q. Liu, X. Wang, G. Wang, Y. Zhang, et al., (2023) “Carbon nanotubes: a powerful bridge for conductivity and flexibility in electrochemical glucose sensors" Journal of Nanobiotechnology 21(1): 320. DOI: 10.1186/s12951 023-02088-7.
  21. [21] Y. Qiu and Y. Wang, (2022) “Controllable synthesis of porous Co3O4 nanorods and their ethanol-sensing performance" Ceramics International 48(20): 29659–29668. DOI: 10.1016/j.ceramint.2022.06.221.
  22. [22] X. Pan, F. Ji, Q. Xia, X. Chen, H. Pan, S. N. Khisro, S. Luo, M. Chen, and Y. Zhang, (2018) “High performance supercapacitors based on superior Co3O4 nanorods electrode for integrated energy harvesting storage system" Electrochimica Acta 282: 905–912. DOI: h10.1016/j.electacta.2018.06.127.
  23. [23] J. Zhang, Y. Sun, X. Li, and J. Xu, (2019) “Fabrication of porous NiMn2O4 nanosheet arrays on nickel foam as an advanced sensor material for non-enzymatic glucose detection" Scientific reports 9(1): 18121. DOI: 10.1038/s41598-019-54746-2.
  24. [24] J. Salamon, A. Simi, H. J. Prabu, A. F. Sahayaraj, I. Johnson, V. Snowlin, R. Gopi, and A. J. S. Kennedy, (2024) “Synthesis and characterization of graphene-doped Co3O4 nanotubes electrode material for supercapacitor application" Journal of Inorganic and Organometal licPolymers and Materials 34(6): 2555–2571. DOI: 10.1007/s10904-023-02995-0.
  25. [25] S. A. Makhlouf, Z. H. Bakr, K. I. Aly, and M. Moustafa, (2013) “Structural, electrical and optical properties of Co3O4 nanoparticles" Superlattices and Microstructures 64: 107–117. DOI: 10.1016/j.spmi.2013.09.023.
  26. [26] A.Diallo ,A.Beye, T.B.Doyle, E.Park, and M.Maaza, (2015) “Green synthesis of Co3O4 nanoparticles via Aspalathus linearis: physical properties" Green Chemistry Letters and Reviews 8(3-4): 30–36. DOI: 10.1080/17518253.2015.1082646.
  27. [27] A. Abdallah and R. Awad, (2020) “Study of the struc tural and physical properties of Co3O4 nanoparticles synthesized by co-precipitation method" Journal of Superconductivity and Novel Magnetism 33(5): 1395 1404. DOI: 10.1007/s10948-019-05296-1.
  28. [28] D. D. M.Prabaharan, K. Sadaiyandi, M. Mahendran, and S. Sagadevan, (2017) “Precipitation method and characterization of cobalt oxide nanoparticles" Applied Physics A 123: 1–6. DOI: 10.1007/s00339-017-0786-8.
  29. [29] Y. Ding, Y. Wang, L. Su, M. Bellagamba, H. Zhang, and Y. Lei, (2010) “Electrospun Co3O4 nanofibers for sensitive and selective glucose detection" Biosensors and Bioelectronics 26(2): 542–548. DOI: 10.1016/j.bios.2010.07.050.
  30. [30] L. Yang, J. Zhang, M. Lv, Y. Ruan, X. Weng, and J. Feng, (2022) “Dual-function glucose and hydrogen per oxide sensors based on Copper-embedded porous carbon composites" Journal of Electroanalytical Chemistry 924: 116881. DOI: 10.1016/j.jelechem.2022.116881.
  31. [31] D. D. Upadhyay, S. Singh, K. B. Singh, N. Gau tam, S. Shrivastava, and G. Pandey, (2023) “Biogeni cally produced Co3O4 nanoparticles and their application as micronutrient and antimicrobial agent foragro environmental sustainability" Inorganic Chemistry Communications 155: 110957. DOI: 10.1016/j.inoche.2023.110957.
  32. [32] A. Deshpande and S. G. Bansod, (2024) “Effect of sintering temperature on sol–gel synthesized NASICON type Li1.3Al0.3Ti1.7(PO4)3 ceramic solid electrolyte" Journal of Materials Science: Materials in Electronics 35(2): 138. DOI: 10.1007/s10854-023-11766-z.
  33. [33] J. Zhang, J. Feng, Y. Tian, Y. Wu, X. Liu, and Q. He, (2021) “Ultrasensitive electrochemical determination of tyrosine based on the α-Fe2O3@Co3O4-NRGO modified electrode" Microchemical Journal 171: 106867. DOI: 10.1016/j.microc.2021.106867.
  34. [34] K. Yang, S. Cheng, Z. Yao, S. Li, and Y. Yang, (2024) “Dumbbell shaped nanocomposite Co3O4/CeO2 derived from metal-organic frameworks (MOFs) as an excellent non-enzymatic glucose sensor" Solid State Sciences 150: 107498. DOI: 10.1016/j.solidstatesciences.2024.107498.
  35. [35] N.Elgrishi, K.J.Rountree, B.D.McCarthy, E.S.Roun tree, T. T. Eisenhart, and J. L. Dempsey, (2018) “A practical beginner’s guide to cyclic voltammetry" Journal of chemical education 95(2): 197–206. DOI: 10. 1021/acs.jchemed.7b00361.
  36. [36] Q. Dong, X. Wang, W. S. Willis, D. Song, Y. Huang, J. Zhao, B. Li, and Y. Lei, (2019) “Nitrogen-doped hollow Co3O4 nanofibers for both solid-state pH sensing and improved non-enzymatic glucose sensing" Electroanalysis 31(4): 678–687. DOI: 10.1002/elan.201800741.
  37. [37] J. Zhao, C. Zheng, J. Gao, J. Gui, L. Deng, Y. Wang, and R. Xu, (2021) “Co3O4 nanoparticles embedded in laser-induced graphene for a flexible and highly sensitive enzyme-free glucose biosensor" Sensors and Actuators B: Chemical 347: 130653. DOI: 10.1016/j.snb.2021.130653.
  38. [38] S. Ramesh, K. Karuppasamy, Y. Haldorai, A. Sivasamy, H.-S. Kim, and H. S. Kim, (2021) “Hexago nal nanostructured cobalt oxide@ nitrogen doped multi walled carbon nanotubes/polypyyrole composite for super capacitor and electrochemical glucose sensor" Colloids and Surfaces B: Biointerfaces 205: 111840. DOI: 10.1016/j.colsurfb.2021.111840.
  39. [39] C. Li, J. Xiong, C. Zheng, and J. Zhao, (2022) “Screen printing preparation of high-performance nonenzymatic glucose sensors based on Co3O4 nanoparticles-embedded N-doped laser-induced graphene" ACS Applied Nano Materials 5(11): 16655–16663. DOI: 10.1021/acsanm. 2c03694.
  40. [40] P. Balla, A. Sinha, L. Wu, X. Lu, D. Tan, J. Chen, et al., (2019) “Co3O4 nanoparticles supported mesoporous car bon framework interface for glucose biosensing" Talanta 203: 112–121. DOI: 10.1016/j.talanta.2019.05.056.
  41. [41] M.Kang, H.Zhou, N.Zhao, andB.Lv,(2020)“Porous Co3O4 nanoplates as an efficient electromaterial for non enzymatic glucose sensing" Cryst Eng Comm 22(1): 35 43. DOI: 10.1039/C9CE01396B.
  42. [42] M.A.Yassin, B. K. Shrestha, R. Ahmad, S. Shrestha, C. H.Park,andC.S.Kim,(2019)“Exfoliatednanosheets of Co3O4 webbed with polyaniline nanofibers: A novel composite electrode material for enzymeless glucose sens ing application" Journal of Industrial and Engineer ing Chemistry 73: 106–117. DOI: 10.1016/j.jiec.2019. 01.011.
  43. [43] S.-J. Kang and J. J. Pak, (2022) “Synthesis of Laser Induced Cobalt Oxide for Non-Enzymatic Electro chemical Glucose Sensors" ChemElectroChem 9(16): e202200328. DOI: 10.1002/celc.202200328.
  44. [44] M. Hilal, W. Xie, and W. Yang, (2022) “Straw-sheaf like Co3O4 for preparation of an electrochemical non enzymatic glucose sensor" Microchimica Acta 189(9): 364. DOI: 10.1007/s00604-022-05453-9.
  45. [45] L. Yan, D. Chu, X.-Q. Chu, D. Ge, and X. Chen, (2022) “Co/CoO nanoparticles armored by N-doped nanoporous carbon polyhedrons towards glucose oxidation in high performance non-enzymatic sensors" New Journal of Chemistry 46(31): 15071–15079. DOI: 10.1039/D2NJ02490J.
  46. [46] A. Mohammadpour-Haratbar, B. Mosallanejad, Y. Zare, K. Y. Rhee, and S.-J. Park, (2022) “Co3O4 nanoparticles embedded in electrospun carbon nanofibers as free-standing nanocomposite electrodes as highly sensitive enzyme-free glucose biosensors" Reviews on Advanced Materials Science 61(1): 744–755. DOI: 10.1515/rams-2022-0251.
  47. [47] F. Liaqat, I. ul Haq, F. Saira, and S. Qaisar, (2023) “Development of glucose sensor based on cobalt and nickel doped ceria nanostructures" Materials Science and Engineering: B 289: 116231. DOI: 10.1016/j.mseb.2022.116231.
  48. [48] G. Wang, L. Li, X. Han, W. Gao, and C. Wang, (2024) “Nickel foam-decorated hollow-Co3O4/GO nanocompos ites: A highly sensitive non-enzymatic electrochemical sensor for glucose detection" Microchemical Journal 206: 111398. DOI: 10.1016/j.microc.2024.111398.
  49. [49] J. H. Han, H. W. Kang, W. Lee, et al., (2019) “Ultra-sensitive non-enzymatic amperometric glucose sensors based on silver nanowire/graphene hybrid three dimensional nanostructures" Results in Physics 15: 102761. DOI: 10.1016/j.rinp.2019.102761.

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