Issue

Vol. 16 (2024)

Heterogeneous CuxO Nano-Skeletons from Waste Electronics for Enhanced Glucose Detection

https://doi.org/10.1007/s40820-024-01467-5
Yexin Pan
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China
Ruohan Yu
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China
Yalong Jiang
State Key Laboratory of New Textile Materials and Advanced Processing Technologies, Wuhan Textile University, Wuhan 430200, People’s Republic of China
Haosong Zhong
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China
Qiaoyaxiao Yuan
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China
Connie Kong Wai Lee
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China
Rongliang Yang
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China
Siyu Chen
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China
Yi Chen
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China
Wing Yan Poon
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China
Mitch Guijun Li
Center on Smart Manufacturing, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong SAR 999077, People’s Republic of China

Corresponding Author: Mitch Guijun Li

mitchli@ust.hk

Nano-Micro Letters, Vol. 16 (2024), Article Number: 249

Abstract

Electronic waste (e-waste) and diabetes are global challenges to modern societies. However, solving these two challenges together has been challenging until now. Herein, we propose a laser-induced transfer method to fabricate portable glucose sensors by recycling copper from e-waste. We bring up a laser-induced full-automatic fabrication method for synthesizing continuous heterogeneous CuxO (h-CuxO) nano-skeletons electrode for glucose sensing, offering rapid (< 1 min), clean, air-compatible, and continuous fabrication, applicable to a wide range of Cu-containing substrates. Leveraging this approach, h-CuxO nano-skeletons, with an inner core predominantly composed of Cu2O with lower oxygen content, juxtaposed with an outer layer rich in amorphous CuxO (a-CuxO) with higher oxygen content, are derived from discarded printed circuit boards. When employed in glucose detection, the h-CuxO nano-skeletons undergo a structural evolution process, transitioning into rigid Cu2O@CuO nano-skeletons prompted by electrochemical activation. This transformation yields exceptional glucose-sensing performance (sensitivity: 9.893 mA mM−1 cm−2; detection limit: 0.34 μM), outperforming most previously reported glucose sensors. Density functional theory analysis elucidates that the heterogeneous structure facilitates gluconolactone desorption. This glucose detection device has also been downsized to optimize its scalability and portability for convenient integration into people’s everyday lives.


Highlights:
1 Novel laser-induced transfer method for fabricating glucose sensors from recycled e-waste copper, offering a sustainable and cost-effective solution.
2 Unique heterogeneous CuxO nano-skeletons derived from discarded printed circuit boards exhibiting exceptional glucose-sensing performance (sensitivity: 9.893 mA mM−1 cm−2, detection limit: 0.34 μM).
3 Miniaturized glucose detection device, optimized for scalability and portability, revolutionizing diabetes management and patient care.

Keywords

Copper oxide Electron 3D tomography E-waste Glucose detection Electrochemical activation
Pan, Yexin, Ruohan Yu, Yalong Jiang, Haosong Zhong, Qiaoyaxiao Yuan, Connie Kong Wai Lee, Rongliang Yang, Siyu Chen, Yi Chen, Wing Yan Poon, and Mitch Guijun Li. 2024. “Heterogeneous CuxO Nano-Skeletons from Waste Electronics for Enhanced Glucose Detection”. Nano-Micro Letters 16 (July):249. https://doi.org/10.1007/s40820-024-01467-5.
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
References
  1. F. Imre-Lucaci, S. Fogarasi, P. Ilea, M. Tamasan, Copper recovery from real samples of WPCBs by anodic dissolution. Environ. Eng. Manag. J. 11, 1439–1444 (2012). https://doi.org/10.30638/eemj.2012.179
  2. Z. Wang, B. Zhang, D. Guan, Take responsibility for electronic-waste disposal. Nature 536, 23–25 (2016). https://doi.org/10.1038/536023a
  3. D. Dutta, R. Rautela, L.K.S. Gujjala, D. Kundu, P. Sharma et al., A review on recovery processes of metals from E-waste: a green perspective. Sci. Total. Environ. 859, 160391 (2023). https://doi.org/10.1016/j.scitotenv.2022.160391
  4. J. Li, H. Lu, J. Guo, Z. Xu, Y. Zhou, Recycle technology for recovering resources and products from waste printed circuit boards. Environ. Sci. Technol. 41, 1995–2000 (2007). https://doi.org/10.1021/es0618245
  5. Q. Tan, L. Liu, M. Yu, J. Li, An innovative method of recycling metals in printed circuit board (PCB) using solutions from PCB production. J. Hazard. Mater. 390, 121892 (2020). https://doi.org/10.1016/j.jhazmat.2019.121892
  6. A. Chagnes, G. Cote, C. Ekberg, M. Nilsson, T. Retegan, WEEE recycling: Research, development, and policies (Elsevier, Amsterdam, 2016), pp.55–68
  7. S. Kanta Das, G. Ellamparuthy, T. Kundu, S.I. Angadi, S.S. Rath, A comprehensive review of the mechanical separation of waste printed circuit boards. Process. Saf. Environ. Prot. 187, 221–239 (2024). https://doi.org/10.1016/j.psep.2024.04.090
  8. K. Huang, J. Guo, Z. Xu, Recycling of waste printed circuit boards: a review of current technologies and treatment status in China. J. Hazard. Mater. 164, 399–408 (2009). https://doi.org/10.1016/j.jhazmat.2008.08.051
  9. A. Berbardes, I. Bohlinger, D. Rodriguez, H. Milbrandt, W. Wuth, Recycling of printed circuit boards by melting with oxidising/reducing top blowing process. EPD Congress 1997, 363–375 (1997)
  10. F. Li, K. Cai, Q. Huang, M. Zhong, L. Wang et al., Recovery of Au and Cu from waste memory modules by electrolysis with hydrochloric acid-hydrogen peroxide system. Sep. Purif. Technol. 308, 122872 (2023). https://doi.org/10.1016/j.seppur.2022.122872
  11. B. Niu, E. Shanshan, Z. Xu, J. Guo, How to efficient and high-value recycling of electronic components mounted on waste printed circuit boards: recent progress, challenge, and future perspectives. J. Clean. Prod. 415, 137815 (2023). https://doi.org/10.1016/j.jclepro.2023.137815
  12. Z. Chen, C. Song, X. Lian, B. Xu, Y. Wang, Dynamic ionic liquids-based conductive coatings for customizable, integrated and recyclable printed circuit boards. Adv. Funct. Mater. (2024). https://doi.org/10.1002/adfm.202400829
  13. M.P. Raele, L.R. De Pretto, D.M. Zezell, Soldering mask laser removal from printed circuit boards aiming copper recycling. Waste Manag. 68, 475–481 (2017). https://doi.org/10.1016/j.wasman.2017.07.019
  14. Z. Ur Rehman, F. Yang, M. Wang, T. Zhu, Fundamentals and advances in laser-induced transfer. Opt. Laser Technol. 160, 109065 (2023). https://doi.org/10.1016/j.optlastec.2022.109065
  15. L. Lipani, B.G.R. Dupont, F. Doungmene, F. Marken, R.M. Tyrrell et al., Non-invasive, transdermal, path-selective and specific glucose monitoring via a graphene-based platform. Nat. Nanotechnol. 13, 504–511 (2018). https://doi.org/10.1038/s41565-018-0112-4
  16. H. Lee, Y.J. Hong, S. Baik, T. Hyeon, D.H. Kim, Enzyme-based glucose sensor: from invasive to wearable device. Adv. Healthc. Mater. 7, e1701150 (2018). https://doi.org/10.1002/adhm.201701150
  17. F. Lorestani, X. Zhang, A.M. Abdullah, X. Xin, Y. Liu et al., A highly sensitive and long-term stable wearable patch for continuous analysis of biomarkers in sweat. Adv. Funct. Mater. 33, 2306117 (2023). https://doi.org/10.1002/adfm.202306117
  18. M. Wei, Y. Qiao, H. Zhao, J. Liang, T. Li et al., Electrochemical non-enzymatic glucose sensors: recent progress and perspectives. Chem. Commun. 56, 14553–14569 (2020). https://doi.org/10.1039/D0CC05650B
  19. Y. Qiao, Q. Liu, S. Lu, G. Chen, S. Gao et al., High-performance non-enzymatic glucose detection: using a conductive Ni-MOF as an electrocatalyst. J. Mater. Chem. B 8, 5411–5415 (2020). https://doi.org/10.1039/d0tb00131g
  20. J. Heikenfeld, Technological leap for sweat sensing. Nature 529, 475–476 (2016). https://doi.org/10.1038/529475a
  21. S. Emaminejad, W. Gao, E. Wu, Z.A. Davies, H. Yin Yin Nyein et al., Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform. Proc. Natl. Acad. Sci. 114, 4625–4630 (2017). https://doi.org/10.1073/pnas.1701740114
  22. H. Lee, C. Song, Y.S. Hong, M. Kim, H.R. Cho et al., Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module. Sci. Adv. 3, e1601314 (2017). https://doi.org/10.1126/sciadv.1601314
  23. H. Lee, T.K. Choi, Y.B. Lee, H.R. Cho, R. Ghaffari et al., A graphene-based electrochemical device with thermoresponsive microneedles for diabetes monitoring and therapy. Nat. Nanotechnol. 11, 566–572 (2016). https://doi.org/10.1038/nnano.2016.38
  24. W. Liang, P. Wied, F. Carraro, C.J. Sumby, B. Nidetzky et al., Metal–organic framework-based enzyme biocomposites. Chem. Rev. 121, 1077–1129 (2021). https://doi.org/10.1021/acs.chemrev.0c01029
  25. J. Zhu, S. Liu, Z. Hu, X. Zhang, N. Yi et al., Laser-induced graphene non-enzymatic glucose sensors for on-body measurements. Biosens. Bioelectron. 193, 113606 (2021). https://doi.org/10.1016/j.bios.2021.113606
  26. S. Bag, A. Baksi, S.H. Nandam, D. Wang, X. Ye et al., Nonenzymatic glucose sensing using Ni60 Nb40 nanoglass. ACS Nano 14, 5543–5552 (2020). https://doi.org/10.1021/acsnano.9b09778
  27. T. Liu, Y. Guo, Z. Zhang, Z. Miao, X. Zhang et al., Fabrication of hollow CuO/PANI hybrid nanofibers for non-enzymatic electrochemical detection of H2O2 and glucose. Sens. Actuat. B Chem. 286, 370–376 (2019). https://doi.org/10.1016/j.snb.2019.02.006
  28. Z. Zhai, B. Leng, N. Yang, B. Yang, L. Liu et al., Rational construction of 3D-networked carbon nanowalls/diamond supporting CuO architecture for high-performance electrochemical biosensors. Small 15, e1901527 (2019). https://doi.org/10.1002/smll.201901527
  29. P. Chakraborty, S. Dhar, N. Deka, K. Debnath, S.P. Mondal, Non-enzymatic salivary glucose detection using porous CuO nanostructures. Sens. Actuat. B Chem. 302, 127134 (2020). https://doi.org/10.1016/j.snb.2019.127134
  30. L. Fang, Y. Cai, B. Huang, Q. Cao, Q. Zhu et al., A highly sensitive nonenzymatic glucose sensor based on Cu/Cu2O composite nanops decorated single carbon fiber. J. Electroanal. Chem. 880, 114888 (2021). https://doi.org/10.1016/j.jelechem.2020.114888
  31. E.R. Mamleyev, P.G. Weidler, A. Nefedov, D.V. Szabó, M. Islam et al., Nano- and microstructured copper/copper oxide composites on laser-induced carbon for enzyme-free glucose sensors. ACS Appl. Nano Mater. 4, 13747–13760 (2021). https://doi.org/10.1021/acsanm.1c03149
  32. Y. Gao, F. Yang, Q. Yu, R. Fan, M. Yang et al., Three-dimensional porous Cu@Cu2O aerogels for direct voltammetric sensing of glucose. Microchim. Acta 186, 192 (2019). https://doi.org/10.1007/s00604-019-3263-6
  33. S. Zhang, J. Yuan, S. Wang, Y. Li, Y. Xu et al., Synergistic multilevel sieving membranes: integrating cellular graphene skeleton with continuous MOFs nanolayer for superior multiphase water separation. Adv. Funct. Mater. 34, 2307571 (2024). https://doi.org/10.1002/adfm.202307571
  34. V. Selvamani, A. Zareei, A. Elkashif, M.K. Maruthamuthu, S. Chittiboyina et al., Hierarchical micro/mesoporous copper structure with enhanced antimicrobial property via laser surface texturing. Adv. Mater. Interfaces 7, 1901890 (2020). https://doi.org/10.1002/admi.201901890
  35. R. Molina, M. Ertuğrul, Á. Larrea, R. Navarro, V. Rico et al., Laser-induced scanning transfer deposition of silver electrodes on glass surfaces: a green and scalable technology. Appl. Surf. Sci. 556, 149673 (2021). https://doi.org/10.1016/j.apsusc.2021.149673
  36. G. Kresse, J. Furthmüller, Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B Condens. Matter 54, 11169–11186 (1996). https://doi.org/10.1103/physrevb.54.11169
  37. G. Kresse, J. Furthmüller, Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996). https://doi.org/10.1016/0927-0256(96)00008-0
  38. G. Kresse, D. Joubert, From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758 (1999). https://doi.org/10.1103/PhysRevB.59.1758
  39. J.P. Perdew, K. Burke, M. Ernzerhof, Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996). https://doi.org/10.1103/physrevlett.77.3865
  40. L. Xu, Y. Yang, Z.-W. Hu, S.-H. Yu, Comparison study on the stability of copper nanowires and their oxidation kinetics in gas and liquid. ACS Nano 10, 3823–3834 (2016). https://doi.org/10.1021/acsnano.6b00704
  41. L. Martin, H. Martinez, D. Poinot, B. Pecquenard, F. Le Cras, Comprehensive X-ray photoelectron spectroscopy study of the conversion reaction mechanism of CuO in lithiated thin film electrodes. J. Phys. Chem. C 117, 4421–4430 (2013). https://doi.org/10.1021/jp3119633
  42. S. Menkin, C.A. O’Keefe, A.B. Gunnarsdóttir, S. Dey, F.M. Pesci et al., Toward an understanding of SEI formation and lithium plating on copper in anode-free batteries. J. Phys. Chem. C 125, 16719–16732 (2021). https://doi.org/10.1021/acs.jpcc.1c03877
  43. R. Kumar, P. Rai, A. Sharma, Facile synthesis of Cu2O microstructures and their morphology dependent electrochemical supercapacitor properties. RSC Adv. 6, 3815–3822 (2016). https://doi.org/10.1039/C5RA20331G
  44. D. Ye, G. Liang, H. Li, J. Luo, S. Zhang et al., A novel nonenzymatic sensor based on CuO nanoneedle/graphene/carbon nanofiber modified electrode for probing glucose in saliva. Talanta 116, 223–230 (2013). https://doi.org/10.1016/j.talanta.2013.04.008
  45. Y. Zhang, L. Su, D. Manuzzi, H.V.E. de los Monteros, W. Jia et al., Ultrasensitive and selective non-enzymatic glucose detection using copper nanowires. Biosens. Bioelectron. 31, 426–432 (2012). https://doi.org/10.1016/j.bios.2011.11.006
  46. L.-Y. Lin, B.B. Karakocak, S. Kavadiya, T. Soundappan, P. Biswas, A highly sensitive non-enzymatic glucose sensor based on Cu/Cu2O/CuO ternary composite hollow spheres prepared in a furnace aerosol reactor. Sens. Actuat. B Chem. 259, 745–752 (2018). https://doi.org/10.1016/j.snb.2017.12.035
  47. L. Laffont, M.Y. Wu, F. Chevallier, P. Poizot, M. Morcrette et al., High resolution EELS of Cu–V oxides: application to batteries materials. Micron 37, 459–464 (2006). https://doi.org/10.1016/j.micron.2005.11.007
  48. Y. Duan, Z.-Y. Yu, S.-J. Hu, X.-S. Zheng, C.-T. Zhang et al., Scaled-up synthesis of amorphous NiFeMo oxides and their rapid surface reconstruction for superior oxygen evolution catalysis. Angew. Chem. Int. Ed. 58, 15772–15777 (2019). https://doi.org/10.1002/anie.201909939
Read More
Author biographies are not available.
Statistic
Read Counter : 4406 Download : 3137

Most read articles by the same author(s)