Skip to main content
SpringerLink
Log in

Viscosity, thermal conductivity and density of carbon quantum dots nanofluids: an experimental investigation and development of new correlation function and ANN modeling

  • Published:
Journal of Thermal Analysis and Calorimetry Aims and scope Submit manuscript

Abstract

This paper reports an experimental investigation on the viscosity, thermal conductivity and density of water, ethylene glycol, and water–ethylene glycol mixture (60:40 vol%)-based carbon quantum dots (CQDs) nanofluids. Stable nanofluids were prepared by two-step technique at room temperature, and the thermophysical properties of them were measured at various temperatures and volume fractions (0.2–1 vol%). The presence of CQDs enhances the viscosity and thermal conductivity of nanofluids noticeably. The maximum thermal conductivity enhancement reaches up to 8.2%, 25.1%, and 13.3% for the nanofluid containing 1% CQDs at 50 °C in ethylene glycol, water, and water–ethylene glycol mixture (60:40) as base fluids, respectively. In addition, the viscosity of each solution was measured, and the results show that it increases with increasing volume fractions of CQDs nanoparticles and decreased with increasing temperature. Additionally, to correlate viscosity, thermal conductivity, and density of nanofluids, some new empirical equations are derived and compared with experimental data and other theoretical models. Besides, three artificial neural network models are applied to predict the viscosity, thermal conductivity, and density of nanofluids and they are in excellent agreement with experimental data with the AAD = 1.29% and R2 = 0.99994 for viscosity, AAD = 0.85% and R2 = 0.99867 for thermal conductivity, and AAD = 0.01% and R2 = 0.99999 for density of nanofluids.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

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
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Zyła G, Fal J. Experimental studies on viscosity, thermal and electrical conductivity of aluminum nitride–ethylene glycol (AlN–EG) nanofluids. Thermochim Acta. 2016;637:11–6.

    Article  Google Scholar 

  2. Hwang Y, Lee JK, Lee CH, Jung YM, Cheong SI, Lee CG, Ku BC, Jang SP. Stability and thermal conductivity characteristics of nanofluids. Thermochim Acta. 2007;455(1–2):70–4.

    Article  CAS  Google Scholar 

  3. Shanbedi M, Zeinali Heris S, Amiri A, Adyani S, Alizadeh M, Baniadam M. Optimization of the thermal efficiency of a two-phase closed thermosyphon using active learning on the human algorithm interaction. Numer Heat Transf A Appl. 2014;66(8):947–62.

    Article  Google Scholar 

  4. Baghbanzadeh M, Rashidi A, Rashtchian D, Lotfi R, Amrollahi A. Synthesis of spherical silica/multiwall carbon nanotubes hybrid nanostructures and investigation of thermal conductivity of related nanofluids. Thermochim Acta. 2012;549:87–94.

    Article  CAS  Google Scholar 

  5. Agresti F, Ferrario A, Boldrini S, Miozzo A, Montagner F, Barison S, Pagura C, Fabrizio M. Temperature controlled photoacoustic device for thermal diffusivity measurements of liquids and nanofluids. Thermochim Acta. 2015;619:48–52.

    Article  CAS  Google Scholar 

  6. Moghaddari M, Yousefi F. Syntheses, characterization, measurement and modeling viscosity of nanofluids containing OH-functionalized MWCNTs and their composites with soft metal (Ag, Au and Pd) in water, ethylene glycol and water/ethylene glycol mixture. J Therm Anal Calorim. 2018. https://doi.org/10.1007/s10973-018-7150-x.

    Article  Google Scholar 

  7. Omrani AN, Esmaeilzadeh E, Jafari M, Behzadmehr A. Effects of multi-walled carbon nanotubes shape and size on thermal conductivity and viscosity of nanofluids. Diam Relat Mater. 2019;93:96–104.

    Article  CAS  Google Scholar 

  8. Sedaghat F, Yousefi F. Synthesizes, characterization, measurements and modeling thermal conductivity and viscosity of graphene quantum dots nanofluids. J Mol Liq. 2019;278:299–308.

    Article  CAS  Google Scholar 

  9. Goharshadi EK, Niyazi Z, Shafaee M, Moghaddam MB, Ludwig R, Namayandeh-Jorabchi M. Transport properties of graphene quantum dots in glycerol and distilled water. J Mol Liq. 2017;241:831–8.

    Article  CAS  Google Scholar 

  10. Soleymaniha M, Amiri A, Shanbedi M, Teng CB, Wongwises S. Water-based graphene quantum dots dispersion as a high-performance long- term stable nanofluid for two-phased closed thermosyphons. Int Commun Heat Mass Transfer. 2018;95:147–54.

    Article  CAS  Google Scholar 

  11. Amiri A, Shanbedi M, Dashti H. Thermophysical and rheological properties of water-based graphene quantum dots nanofluids. J Taiwan Inst Chem Eng. 2017;76:132–40.

    Article  CAS  Google Scholar 

  12. Rabbani Esfahani M, Mohseni Languri E, Rao Nunna M. Effect of particle size and viscosity on thermal conductivity enhancement of graphene oxide nanofluid. Int Commun Heat Mass Transfer. 2016;76:308–15.

    Article  Google Scholar 

  13. Yousefi F, Karimi H, Mohammadiyan S. Viscosity of carbon nanotube suspension using artificial neural networks with principal component analysis. Heat Mass Transf. 2016;52:2345–55.

    Article  CAS  Google Scholar 

  14. Yousefi F, Sedaghat F. Experimental investigation and modeling of S, N-GQDs nanofluid density using new equation of state and artificial neural network. Heat Mass Transf. 2018;54:276–90.

    Google Scholar 

  15. Zolfaghari H, Yousefi F. Thermodynamic properties of lubricant/refrigerant mixtures using statistical mechanics and artificial intelligence. Int J Refrig. 2017;80:130–44.

    Article  CAS  Google Scholar 

  16. Yousefi F, Mohammadiyan S, Karimi H. Application of artificial neural network and PCA to predict the thermal conductivities of nanofluids. Heat Mass Transf. 2016;52:2141–54.

    Article  CAS  Google Scholar 

  17. Li H, Kang Z, Liu Y, Lee ST. Carbon nanodots: synthesis, properties and applications. J Mater Chem. 2012;22:24230–53.

    Article  CAS  Google Scholar 

  18. Baker SN, Baker GA. Luminescent carbon nanodots: emergent nanolights. Angew Chem Int Ed. 2010;49:6726–44.

    Article  CAS  Google Scholar 

  19. Liu HP, Ye T, Mao CD. Fluorescent carbon nanoparticles derived from candle soot. Angew Chem Int Ed. 2007;46:6473–5.

    Article  CAS  Google Scholar 

  20. Luo PG, Sahu S, Yang ST, Sonkar SK, Wang JP, Wang HF, Le Croy GE, Cao L, Sun YP. Carbon “quantum” dots for optical bioimaging. J Mater Chem B. 2013;1:2116–27.

    Article  CAS  PubMed  Google Scholar 

  21. Li H, He X, Kang Zh, Huang H, Liu Y, Liu J, Lian S, Tsang CHA, Yang X, Lee ST. Water-soluble fluorescent carbon quantum dots and photocatalyst design. Angew Chem Int Ed. 2010;49:4430–4.

    Article  CAS  Google Scholar 

  22. Roy P, Chen PC, Periasamy AP, Chen YN, Chang HT. Photoluminescent carbon nanodots: synthesis, physicochemical properties and analytical applications. Mater Today. 2015;18:447–58.

    Article  CAS  Google Scholar 

  23. da Silva JCGE, Gonçalves MR. Investigation on the electronic and optical properties of short oxidized multiwalled carbon nanotubes. Trends Anal Chem. 2011;30:1327–36.

    Article  Google Scholar 

  24. Liu M, Li J. Cobalt phosphide hollow polyhedron as efficient bifunctional electrocatalysts for the evolution reaction of hydrogen and oxygen. ACS Appl Mater Interfaces. 2016;8:2158–65.

    Article  CAS  PubMed  Google Scholar 

  25. Wang Y, Hu A. Carbon quantum dots: synthesis, properties and applications. J Mater Chem C. 2014;2:6921–39.

    Article  CAS  Google Scholar 

  26. Daneshfar A, Khezeli T. Headspace solid phase microextraction of nicotine using thin layer chromatography plates modified with carbon dots. Microchim Acta. 2015;182:209–16.

    Article  CAS  Google Scholar 

  27. Afrand M, Najafabadi KN, Akbari M. Effects of temperature and solid volume fraction on viscosity of SiO2-MWCNTs/SAE40 hybrid nanofluid as a coolant and lubricant in heat engines. Appl Therm Eng. 2016;102:45–54.

    Article  CAS  Google Scholar 

  28. Zadkhast M, Toghraie D, Karimipour A. Developing a new correlation to estimate the thermal conductivity of MWCNT-CuO/water hybrid nanofluid via an experimental investigation. J Therm Anal Calorim. 2017;129:859–67.

    Article  CAS  Google Scholar 

  29. Wen D, Ding Y. Effective thermal conductivity of aqueous suspensions of carbon nanotubes (carbon nanotube nanofluids. J Thermophys Heat Transf. 2004;18:481–5.

    Article  CAS  Google Scholar 

  30. Soltanimehr M, Afrand M. Thermal conductivity enhancement of COOH- functionalized MWCNTs/ethylene glycol–water nanofluid for application in heating and cooling systems. Appl Therm Eng. 2016;105:716–23.

    Article  CAS  Google Scholar 

  31. Zadeh AD, Toghraie D. Experimental investigation for developing a new model for the dynamic viscosity of silver/ethylene glycol nanofluid at different temperatures and solid volume fractions. J Therm Anal Calorim. 2018;131:1449–61.

    Article  CAS  Google Scholar 

  32. Keblinski P, Phillpot SR, Choi SUS, Eastman JA. Mechanisms of heat flow in suspensions of nano-sized particles (nanofluids). Int J Heat Mass Transfer. 2002;45:855–63.

    Article  CAS  Google Scholar 

  33. Eastman JA, Phillpot SR, Choi SUS, Keblinski P. Thermal transport in nanofluids. Ann Rev Mater Res. 2004;34:219–46.

    Article  CAS  Google Scholar 

  34. Wang X, Xu X, Choi SUS. Thermal conductivity of nanoparticle-fluid mixture. J Thermophys Heat Transfer. 1999;13:474–80.

    Article  CAS  Google Scholar 

  35. Koo J, Kleinstreue C. Impact analysis of nanoparticle motion mechanisms on the thermal conductivity of nanofluids. Int Commun Heat Mass Transfer. 2005;32:1111–8.

    Article  CAS  Google Scholar 

  36. Maxwell JC. A treatise on electricity and magnetism. Oxford: Clarendon; 1891.

    Google Scholar 

  37. Li C, Peterson GP. Experimental investigation of temperature and volume fraction variations on the effective thermal conductivity of nanoparticle suspensions (nanofluids). J Appl Phys. 2006;99:084314.

    Article  Google Scholar 

  38. Murshed S, Leong K, Yang C. Enhanced thermal conductivity of TiO2—water based nanofluids. Int J Therm Sci. 2005;74:367–73.

    Article  Google Scholar 

  39. Shakeri S, Ghassemi A, Hassani M, Hajian A. Investigation of material removal rate and surface roughness in wire electrical discharge machining process for cementation alloy steel using artificial neural network. Int J Adv Manuf Technol. 2016;582:549–57.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Chemistry Department, Yasouj University, Yasouj, 75918-74831, Iran

    A. M. Mirsaeidi & F. Yousefi

Authors
  1. A. M. Mirsaeidi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. F. Yousefi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to F. Yousefi.

Additional information

Publisher's Note

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

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mirsaeidi, A.M., Yousefi, F. Viscosity, thermal conductivity and density of carbon quantum dots nanofluids: an experimental investigation and development of new correlation function and ANN modeling. J Therm Anal Calorim 143, 351–361 (2021). https://doi.org/10.1007/s10973-019-09138-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10973-019-09138-z

Keywords

Search

Navigation