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Synthesis, Characterization and Physicochemical Properties of Cupric Oxide Nanoparticles and their Nanofluids
Available online at www.sciencedirect.com
ScienceDirect Materials Today: Proceedings 18 (2019) 1176–1184
www.materialstoday.com/proceedings
ICN3I-2017
Synthesis, Characterization and Physicochemical Properties of Cupric Oxide Nanoparticles and Their Nanofluids Miracle Warjria, Jyoti Narayanb* a
Department of Basic Sciences and Social Sciences,(Chemistry Division),School of Technology, North-Eastern Hill University, Shillong, 793022, India b Department of Basic Sciences and Social Sciences,(Chemistry Division),School of Technology, North-Eastern Hill University, Shillong, 793022, India
Abstract
Nanofluids, which are suspension of nanoparticles in base fluids, have been found to enhance the properties of the conventional fluids for heat transfer applications. Research reveals that the greater thermal conduction effect of the selected base fluids has become enormously dominant when nanoparticles of metals, metal oxides and their hybrids are added to these base fluids. The possible reason behind this drastic change can be attributed to the large surface to volume ratio and high physicochemical properties viz.: thermal conductivity, rheology, viscosity, electrical conductivity and molar densities of the dispersed nanoparticles. Keeping this novel application in mind, the present research work reports the preparation of copper oxide nanofluids (CuONF) for heat transfer application using twostep method. At first, the copper oxide nanoparticles (CuONP) were synthesized using wet chemical (precipitation) method. Purified CuONP was characterised using UV-visible spectrophotometer (350 nm), High Resolution Transmission Electron Microscopy revealed the rod-shaped and polycrystalline nature of the nanoparticles (6nm to 15 nm sizes). Pure Monoclinic phase of CuONP was observed from Powder X-ray Diffraction studies with average grain size of 10 nm. Fourier Transformed-Infrared spectroscopy also revealed the presence of pure monoclinic phase of CuONP with bands at 538 cm-1 and 595 cm-1. In the second step, the tested CuONP was dispersed in ethylene glycol as base fluid at variable concentrations. Electrical, rheological, viscometric and density properties of CuONP nanofluids were studied at variable temperature and pH conditions. Conductivity studies showed the increase in conductivity of CuONP nanofluids with increase in temperature and volume concentrations. Rheological studies revealed the Newtonian behaviour of the prepared CuONP nanofluids. Thermophysical properties, viscosity and density increased with increase in volume concentration (0.01%-0.1%) and decreased with increase in temperature (250C-650C). Data validation was done using theoretical models.
* Corresponding author. Tel.: +91 9862261878 E-mail address:[email protected]
2214-7853© 2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Nanotechnology: Ideas, Innovations & Initiatives-2017 (ICN:3i2017).
M. Warjri and J. Narayan / Materials Today: Proceedings 18 (2019) 1176–1184
1177
© 2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Nanotechnology: Ideas, Innovations & Initiatives-2017 (ICN:3i2017). Keywords:Metal oxide nanoparticles; Nanofluids; Conductivity Properties; Rheology.
Nomenclature TG gm µl RPM Å D k λ β θ wnp ρnp wbf ρbf ρnf ø µnf µbf HEG
1.
thioglycerol gram micro litre rotation per minute angstrom crystallite size (eqn. 1) shape factor (eqn. 1) radiation wavelength (eqn. 1) full width at half maximum (eqn. 1) Bragg diffraction angle at peak position in degrees (eqn. 1) weight of nanoparticles (eqn. 2) density of nanoparticles (eqn. 2, 3) weight of base fluid (eqn. 2) density of base fluid (eqn. 2, 3) density of nanofluid (eqn. 3) volume fraction of nanoparticles (eqn. 4, 5, 6) viscosity of nanofluid (eqn. 4, 5, 6) viscosity of base fluid (eqn. 4, 5, 6) hydrogen induced exfoliated graphene
Introduction
Nanofluids are smart fluids where nanoparticles less than 100 nm are dispersed homogeneously in a base fluid. This results in significant enhancement of physicochemical properties of nanofluids at specific nanoparticles concentrations as compared to its base fluid. These fluids have potential applications in the field, where straight heat transfer enhancement are of major significance viz. transportation, nuclear reactors, biomedicines, food industry and electronics industry. Heat transfer can be reduced or enhanced as per the requirement of the transport industry in these smart fluids. Literature reveals that nanofluids has been found to possess enhanced physico-chemical properties such as thermal conductivity [1, 2], viscosity [3], density [4] and thermal diffusivity [5]thereby enhancing heat transfer coefficients [6, 7] as compared to base fluids. But the experimental studies show lack of consistency in the results reported by various research groups [8, 9].Some studies showed a Newtonian behavior [10, 11] while others, showed non-Newtonian behavior [12, 13] of the nanofluids. Correlation of thermal conductivity with rheology [14, 15], effect of temperature and volume fraction of nanoparticles [16, 17], correlation of viscosity with increasing temperature and volume fraction [18, 19] have been studied for some metal oxide nanofluids. However, literature reports scanty data on density, rheology and electrical conductivity correlation of nanofluids [20, 21]. This warrants a systematic research in order to ascertain in detail, the effects of the factors like size, shape, clustering of particles, type of surfactants, solvents, pH on physico-chemical properties of wide range of nanofluids. Present work reports the preparation of copper oxide nanofluids (CuONF) for heat transfer application using wet chemical (precipitation) method. Purified CuONP were characterized using various spectroscopic and microscopic techniques. Nanofluids of variable compositions were prepared to study the variation of physicochemical properties viz. density, rheology and electrical conductivity at different temperatures.
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Experimental
Copper sulphate pentahydrate (CuSO4.5H2O) (99.5% purity, sd-fine), 3-Mercaptopropane-1, 2-diol (TG) (97 % purity, Sigma Aldrich) and sodium hydroxide (97% purity, Fisher Scientific) were used without further purification. Firstly 0.4M (0.9987 gm) CuSO4.5H2O was dissolved in double distilled water and to it 1 µl TG was added and stirred while increasing the temperature to 60ºC till it become completely soluble. During this process, the solution turned from blue to light green color. 4M (1.6 gm) NaOH was added drop wise to the above solution and continued stirring and heating for one hour. The solution turned from light green to brownish-black solution. The solution was centrifuged at 15000 RPM for 3 minutes to obtain the precipitated nanoparticles. The obtained nanoparticles were then washed with water and ethanol three times each to remove the impurities and dried overnight at room temperature. The product was further dried at 100ºC for one hour to remove water.
3. Characterization The purified nanoparticles were characterised using spectroscopic and microscopic techniques. The absorption spectrum was carried out using Ocean Optics UV-visible-NIR Spectroscopy (DH-2000-BAL). Perkin Elmer Fourier Transformed Infrared Spectroscopy [(FTIR) (Spectrum-400)] was used to understand the chemical structure of the CuO nanoparticles. The nanoparticles were characterised using Bruker D8 advance X-ray powder diffractometer (powder XRD, X-ray wavelength = 1.5405 Å) to analyse the phase and average grain size of the CuO nanoparticles. High Resolution Transmission Electron Microscopy [(HR-TEM) (JEOL JEM 2100 at 200 kV)] was carried out to analyse the size, shape and crystalline nature of the nanoparticles. 4. Results and Discussions 4.1. Spectroscopic Analysis The UV-visible spectroscopy of CuO nanoparticles was taken immediately by dispersing in water through sonication. It shows a broad absorption band centred at 350 nm (fig.1a). The presence of broad band from 350 nm to 500 nm may be due to non-spherical structure i.e. flowering like structure [22] of the obtained nanoparticles which was also confirmed from HR-TEM. FTIR spectra show bands at 595 cm-1 and 538 cm-1 which signifies the presence of Cu-O bonds (fig. 1b). The absence of bands between 600-700 cm-1 shows the absence of cuprous oxide (Cu-O vibrations in Cu2O) nanoparticles [23] and formation of pure monoclinic cupric oxide (presence of stretching in CuO in CuO) nanoparticles [24,25]. The bands at 3434 cm-1 and 1632 cm-1 show the presence of O-H and H-O-H bonds which may be due to the hygroscopic nature of the sample. Bands at 1475 cm-1 and 1384 cm-1 corresponds to C-H bond, 1107 cm-1 and 1051 cm-1 corresponds to C-O bond and 927 cm-1 corresponds to C-S bond of the surfactant used.
Fig. 1. (a) UV-visible spectroscopy of CuO nanoparticle; (b) FTIR spectrum of the synthesized CuO nanoparticles.
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4.2. Structural Analysis From powder XRD pattern (fig. 2), the peaks show pure monoclinic structure of the CuO nanoparticles. No other peaks of Cu2O or Cu(OH)2 are observed. We observed two prominent peaks at 2Ɵ = 34.7º and 37.9º which corresponds to 110 and (111) planes of the monoclinic phase. The details of the peaks obtained are shown in table 1. The observed diffraction peak patterns were compared with Joint Committee on Powder Diffraction Standards (JCPDS) standard values (CAS no. 89-5895). The average grain size was calculated using Debye-Scherrer formula (eqn1) where k is Scherrer constant, which accounts for the shape of the particle whose value is taken as 0.9, β is full width at half maximum, values calculated are reported in table 1, λ is the Radiation Wavelength (1.5405 Å). The various XRD properties calculated for synthesised CuO nanoparticles are reported in table 1. The average grain size was calculated to be 10 nm.
D
k cos
(1)
HR-TEM images show the formation of rod-like cupric oxide nanoparticles of sizes 6-15 nm which is in concordance with XRD results (fig. 3a). The length of the nanoparticles is in the range 25 nm to 50 nm. A d-spacing of 0.25 nm and 0.23 nm was observed which corresponds to 110 and (111) planes of monoclinic structure (fig. 3b). The selected area electron diffraction (SAED) pattern clearly shows the polycrystalline nature of the nanoparticles (fig. 3c).
Fig. 2. XRD of CuO nanoparticles. Table.1: Detailed specifications of XRD peaks. 2Ɵ
d spacing
FWHM
hkl
Lattice constant
Crystallite size
31.8257
2.808
0.502
110
3.974
16
34.7954
2.575
0.794
110
3.642
10
37.9345
2.369
1.012
111
4.103
8
48.265
1.883
0.842
202
5.338
10
57.454
1.602
0.637
202
4.532
12
60.9356
1.518
0.735
113
5.037
11
65.5016
1.423
1.385
311
4.721
6
67.2709
1.39
0.883
220
3.93
9
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Fig. 3. (a) TEM results showing rodlike nanostructure of CuO nanoparticles; (b) Allignment showing a d-spacing of 0.25nm and 0.23nm; (c) SAED pattern of CuO nanoparticles; (d) shows the size of the nanorods.
5. Preparation of Nanofluids The nanofluids were prepared by weighing (0.0284 - 0.1136 gm) the characterized CuO nanoparticles and dispersing them in ethylene glycol base fluid (0.02% - 0.08% volume concentration, vol. %), using the law of mixtures (eqn. 2). The specifications of variables are reported under nomenclature. 3
The density of CuO
3
nanoparticles (6.3 gm/cm ) and that of base fluid (1.11 gm/cm ) was taken to calculate the vol. % of the dispersed nanofluids (25 ml).
wnp vol %
np wnp
np
wbf
(2)
bf
The pH of the CuONF without manipulating the medium was 9 (alkaline). The nanofluid was adjusted to pH 5 and 11 using HCl and NaOH to check stability and observed a more stable suspension in the acidic medium i.e. at a pH of 5. Where at pH 5 the CuONF is stable for four days and pH 9 and pH 11 are stable only for a day. 5. 1. Physicochemical Properties Studies 5.1.1. Density Density was measured using specific gravity bottle and water bath was used for adjusting temperatures. Density of the CuONF was observed to increase with addition of nanoparticles and decreasing with increment in temperature. The experimental data was correlated with the Pak and Cho model (eqn. 3) and an agreement was
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observed for low volume fractions of the nanofluids but deviating to a higher density for higher volume fraction nanofluids (fig. 4(a-d)). At acidic pH, the density of CuO nanofluids was found to remain constant on addition of nanoparticles to the base fluid.
nf np 1 bf
(3)
Fig. 4. (a) Density plot showing an increase in density with increase in volume concentration at pH 9; (b) density plots with Pak and Cho model; (c) density decreases with increase in temperature; (d) pH 9 nanofluid shows higher viscosity compared to pH 5 nanofluid; (e) density at pH 5.
5.1.2. Rheology The rheological behaviour of the nanofluids was measured using Rheolabqc (Anton Paar) which is attached to a water bath for adjusting temperatures. A viscosity of 0.0169 Pa.s at 250C was obtained for the base fluid pure ethylene glycol which is in correlation with the literature data. The viscosity data was therefore analysed for the variable volume fraction of the CuONF. From the rheology analysis, a linear relationship was observed between shear rate and shear stress suggesting the Newtonian behaviour of the CuO nanofluids (fig. 5a). A decrease in viscosity was observed with the increase in temperature. An increase in viscosity was observed from 0.02% to 0.06% but decreases in the 0.08% volume concentration which may be due to overloading of nanoparticles leading to agglomeration at a higher rate thereby induce higher rate of sedimentation (fig. 5b). A plot between viscosity and shear rate shows that viscosity is independent of shear rate which also proves the Newtonian behaviour of the
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CuONF (fig. 5c). The viscosity of the nanofluid was observed to be higher at pH 5 than pH 9 and pH 11 of the sample loaded at 0.06% (fig. 5d). The higher viscosity of the CuONF in the acidic medium might lead to high pumping power and reduce the efficiency of the nanofluid. Viscosity of CuONF at acidic medium was observed to remain almost constant on addition of nanoparticles (fig. 5e) which is also the case for density. This behaviour was also observed by Zhao et al. [26] for silicon dioxide nanofluids of particles size less than 20 nm. Models (Einstein (eqn. 4), Batchelor (eqn. 5) and Wang (eqn. 6)) were applied for the present experimental data and observed that the classical models are unable to predict the viscosity of CuO nanorods-ethylene glycol based nanofluids (fig. 5f).
nf bf 1 2.5
nf bf 1 2.5 6.2
nf bf
1 7.3 123
(4)
2
(5)
2
(6)
Fig. 5. (a) Shear stress vs shear rate plot showing linear relationship; (b) plot between viscosity and volume concentration showing increase with increase volume concentration till 0.06% and decrease with increasing temperature at pH 9; (c) linear relationship plot between viscosity and shear rate; (d) viscosity plot at different pH; (e) viscosity at pH 5; (f) correlation of the experimental data with theoretical models.
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5.1.3. Electrical Conductivity Electrical Conductivity was measured using microprocessor based conductivity meter. Few studies have been done on the electrical properties of nanofluids. Baby et. al. [27] studied on the electrical conductivity of CuO and copper oxide decorated graphene (CuO/HEG) and found an increment with the volume fraction and temperature. In this study we also observed the same behaviour where electrical conductivity was increased on the addition of nanoparticles to the base fluids and with increase in the temperature (fig. 6a & 6b). This shows correlation behaviour between electrical conductivity and density of the CuONF, where at higher volume fraction density increases which may increase the number of ions present thereby increase the electrical conductivity. Acidic nature of the CuONF possesses higher electrical conductivity compared to basic nature which clearly shows that acidic medium is more applicable as coolants in electronic devices (fig. 6c). Electrical conductivity was found to be highest at volume concentration 0.06% in acidic medium (fig. 6d).
Fig. 6. (a) Electrical conductivity plot against volume concentration showing increment on addition of nanoparticles at pH 9; (b) electrical conductivity plot against temperature showing increment with increase in temperature; (c) plot showing higher electrical conductivity for acidic medium rather than basic medium; (d) electrical conductivity at pH 5. 6. Conclusion The CuONF is more stable in acidic medium compared to basic medium. Density of CuONF increases with increase in volume concentration and decreases with increase in temperature. But the experimental viscosity values do not show a linear trend with volume fraction of the nanoparticles. The nanofluids show a Newtonian behaviour. The electrical conductivity of the nanofluids is proportional to volume fraction and temperature. The electrical conductivity and density experimental value correlates with each other but disparity behaviour was observed with viscosity experimental values on altering volume fraction. In acidic medium both density and viscosity remain constant on nanoparticles addition. More work should be done to understand the correlation between these physicochemical properties. The Pak and Cho density model correlates with the experimental results at lower volume fraction of the nanoparticles. But viscosity classical models contradict the experimental results. Therefore, the effect of all entity in nanofluids should be engaged to predict theoretically the behaviour of nanofluids.
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Acknowledgement The authors are highly grateful to SAIF, NEHU, Shillong and Tezpur University, Assam for providing the facility of HRTEM and Powder XRD respectively and Department of Chemistry, NEHU, Shillong for FTIR. The authors are grateful to UGC, India for financial support. References [1] L. Zhang, W. Yu,D. Zhu, H. Xie,G. Huang, J. of Nanomaterials 2017 (2017) 5802016. [2] S. Bhanushali, N. N. Jason, P. Ghosh, A. Ganesh,G. P Simon, W. Cheng, ACS Appl. Mater. Interfaces 9 (2017) 18925−18935. [3] J. Garg, B. Poudel, M. Chiesa, J. B. Gordon, J. J. Ma, J. B. Wang, Z. F. Ren, Y. T. Kang, H. Ohtani, J. Nanda, G. H. McKinley, G. Chen, J. App. Phy.103 (2008) 074301. [4] N. S. Nagulkar, S. M. Lawankar, Inter. Res. J. Eng. and Tech. 4 (2017) 2584-2588. [5] S. Kim, H. C. Kwon, D. Lee, H. S. Lee, Met. Mater. Int. 23 (2017) 1144-1149. [6] R. Dharmalingama, K. K.Sivagnanaprabhub, B. S. Kumar, R. Thirumalaid, Procedia Eng. 97 (2014) 1434 – 1441. [7] N. Sandeep, R. P. Sharma, M. Ferdows, J. Molecular Liq. 234 (2017) 437–443. [8] S. M. S. Murshed, S. H. Tan, N. T. Nguyen, J. Phy. D 41 (2008) 085502. [9] K. F. V. Wong, T. Kurma, Nanotechn. 19 (2008) 345702. [10] H. Chen, Y. Ding, Y. He, C. Tan, Chem. Phys. Lett. 444 (2007) 333–337. [11] M. T. Jamal-Abad, M. Dehghan, S. Saedodin, M. S.Valipour, A. Zamzamian, J. Heat and Mass Trans. Res. 1 (2014) 17-23. [12] M. J. Pastoriza-Gallego, L. Lugo, J. L. Legido, M. M. Piñeiro, Nanoscale Res. Lett. 6 (2011) 560. [13] R. Sadri, K. Z. Kamali, M. Hosseini, N. Zubir, S. N. Kazi, G. Ahmadi, M. Dahari, N. M. Huang, A. M. Golsheikh, J. Dispersion Sci. and Tech. 38 (2017) 1302–1310. [14] S. K. Das, N. Putra, W. Roetzel, Inter. J. Heat and Mass Trans. 46 (2003) 851–862. [15] M. J. Pastoriza-Gallego, L. Lugo, J. L. Legido, M. M. Piñeiro, Nanoscale Res. Lett. 6 (2011) 221. [16] D. P. Kularni, D. K. Das, S. L. Patil, J. Nanosci. and Nanotech. 7 (2007) 2318-2322. [17] D. P. Kulkarni, D. K. Das, G. A. Chukwu, J. Nanosci. and Nanotech. 6 (2006) 1–5. [18] P. K. Namburu, D. P. Kulkarni, D. Misra, D. K. Das, Exp. Therm. Fluid Sci. 32 (2007) 397–402. [19] S. Kumar, G.S. Sokhal, J. Singh, J. Eng. Res. Appl. 4 (2014) 28-37. [20] S. N. Shoghl , J. Jamali , M. K. Moraveji, Exp. Ther. and Fluid Sci. 74 (2016) 339-346. [21] M. T. Naik, G. R. Janardhana, K. V. K. Reddy, B. S. Reddy, J. Eng. Appl. Sci. 5 (2010) 29–34. [22] L. Chen, Y. Zhang, P. Zhu, F. Zhou, W. Zeng, D. D. Lu, R. Sun, C. Wong, Sci. Rep. 5 (2015) 1-7. [23] D. Guo, L. Wang, Y. Du, Z. Ma, L. Shen, Mater. Lett. 160 (2015) 541-543. [24] V. V. T. Padil, M. Cerník, Int. J. Nanomedicine 8 (2013) 889-898. [25] M. Gopalakrishnan, A. K. S. Jeevaraj, Mat. Sci. Semiconductor Processing 26 (2014) 512–515. [26] Z. Jia-Fei, L. Zhong-Yang, N. Ming-Jiang, C. Ke-Fa. Chin, Phy. Lett. 26 (2009) 066202. [27] T. T. Baby, R. Sundara, J. Phys. Chem. C 115 (2011) 8527–8533.
ScienceDirect Materials Today: Proceedings 18 (2019) 1176–1184
www.materialstoday.com/proceedings
ICN3I-2017
Synthesis, Characterization and Physicochemical Properties of Cupric Oxide Nanoparticles and Their Nanofluids Miracle Warjria, Jyoti Narayanb* a
Department of Basic Sciences and Social Sciences,(Chemistry Division),School of Technology, North-Eastern Hill University, Shillong, 793022, India b Department of Basic Sciences and Social Sciences,(Chemistry Division),School of Technology, North-Eastern Hill University, Shillong, 793022, India
Abstract
Nanofluids, which are suspension of nanoparticles in base fluids, have been found to enhance the properties of the conventional fluids for heat transfer applications. Research reveals that the greater thermal conduction effect of the selected base fluids has become enormously dominant when nanoparticles of metals, metal oxides and their hybrids are added to these base fluids. The possible reason behind this drastic change can be attributed to the large surface to volume ratio and high physicochemical properties viz.: thermal conductivity, rheology, viscosity, electrical conductivity and molar densities of the dispersed nanoparticles. Keeping this novel application in mind, the present research work reports the preparation of copper oxide nanofluids (CuONF) for heat transfer application using twostep method. At first, the copper oxide nanoparticles (CuONP) were synthesized using wet chemical (precipitation) method. Purified CuONP was characterised using UV-visible spectrophotometer (350 nm), High Resolution Transmission Electron Microscopy revealed the rod-shaped and polycrystalline nature of the nanoparticles (6nm to 15 nm sizes). Pure Monoclinic phase of CuONP was observed from Powder X-ray Diffraction studies with average grain size of 10 nm. Fourier Transformed-Infrared spectroscopy also revealed the presence of pure monoclinic phase of CuONP with bands at 538 cm-1 and 595 cm-1. In the second step, the tested CuONP was dispersed in ethylene glycol as base fluid at variable concentrations. Electrical, rheological, viscometric and density properties of CuONP nanofluids were studied at variable temperature and pH conditions. Conductivity studies showed the increase in conductivity of CuONP nanofluids with increase in temperature and volume concentrations. Rheological studies revealed the Newtonian behaviour of the prepared CuONP nanofluids. Thermophysical properties, viscosity and density increased with increase in volume concentration (0.01%-0.1%) and decreased with increase in temperature (250C-650C). Data validation was done using theoretical models.
* Corresponding author. Tel.: +91 9862261878 E-mail address:[email protected]
2214-7853© 2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Nanotechnology: Ideas, Innovations & Initiatives-2017 (ICN:3i2017).
M. Warjri and J. Narayan / Materials Today: Proceedings 18 (2019) 1176–1184
1177
© 2019 Elsevier Ltd. All rights reserved. Selection and/or Peer-review under responsibility of International Conference on Nanotechnology: Ideas, Innovations & Initiatives-2017 (ICN:3i2017). Keywords:Metal oxide nanoparticles; Nanofluids; Conductivity Properties; Rheology.
Nomenclature TG gm µl RPM Å D k λ β θ wnp ρnp wbf ρbf ρnf ø µnf µbf HEG
1.
thioglycerol gram micro litre rotation per minute angstrom crystallite size (eqn. 1) shape factor (eqn. 1) radiation wavelength (eqn. 1) full width at half maximum (eqn. 1) Bragg diffraction angle at peak position in degrees (eqn. 1) weight of nanoparticles (eqn. 2) density of nanoparticles (eqn. 2, 3) weight of base fluid (eqn. 2) density of base fluid (eqn. 2, 3) density of nanofluid (eqn. 3) volume fraction of nanoparticles (eqn. 4, 5, 6) viscosity of nanofluid (eqn. 4, 5, 6) viscosity of base fluid (eqn. 4, 5, 6) hydrogen induced exfoliated graphene
Introduction
Nanofluids are smart fluids where nanoparticles less than 100 nm are dispersed homogeneously in a base fluid. This results in significant enhancement of physicochemical properties of nanofluids at specific nanoparticles concentrations as compared to its base fluid. These fluids have potential applications in the field, where straight heat transfer enhancement are of major significance viz. transportation, nuclear reactors, biomedicines, food industry and electronics industry. Heat transfer can be reduced or enhanced as per the requirement of the transport industry in these smart fluids. Literature reveals that nanofluids has been found to possess enhanced physico-chemical properties such as thermal conductivity [1, 2], viscosity [3], density [4] and thermal diffusivity [5]thereby enhancing heat transfer coefficients [6, 7] as compared to base fluids. But the experimental studies show lack of consistency in the results reported by various research groups [8, 9].Some studies showed a Newtonian behavior [10, 11] while others, showed non-Newtonian behavior [12, 13] of the nanofluids. Correlation of thermal conductivity with rheology [14, 15], effect of temperature and volume fraction of nanoparticles [16, 17], correlation of viscosity with increasing temperature and volume fraction [18, 19] have been studied for some metal oxide nanofluids. However, literature reports scanty data on density, rheology and electrical conductivity correlation of nanofluids [20, 21]. This warrants a systematic research in order to ascertain in detail, the effects of the factors like size, shape, clustering of particles, type of surfactants, solvents, pH on physico-chemical properties of wide range of nanofluids. Present work reports the preparation of copper oxide nanofluids (CuONF) for heat transfer application using wet chemical (precipitation) method. Purified CuONP were characterized using various spectroscopic and microscopic techniques. Nanofluids of variable compositions were prepared to study the variation of physicochemical properties viz. density, rheology and electrical conductivity at different temperatures.
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Experimental
Copper sulphate pentahydrate (CuSO4.5H2O) (99.5% purity, sd-fine), 3-Mercaptopropane-1, 2-diol (TG) (97 % purity, Sigma Aldrich) and sodium hydroxide (97% purity, Fisher Scientific) were used without further purification. Firstly 0.4M (0.9987 gm) CuSO4.5H2O was dissolved in double distilled water and to it 1 µl TG was added and stirred while increasing the temperature to 60ºC till it become completely soluble. During this process, the solution turned from blue to light green color. 4M (1.6 gm) NaOH was added drop wise to the above solution and continued stirring and heating for one hour. The solution turned from light green to brownish-black solution. The solution was centrifuged at 15000 RPM for 3 minutes to obtain the precipitated nanoparticles. The obtained nanoparticles were then washed with water and ethanol three times each to remove the impurities and dried overnight at room temperature. The product was further dried at 100ºC for one hour to remove water.
3. Characterization The purified nanoparticles were characterised using spectroscopic and microscopic techniques. The absorption spectrum was carried out using Ocean Optics UV-visible-NIR Spectroscopy (DH-2000-BAL). Perkin Elmer Fourier Transformed Infrared Spectroscopy [(FTIR) (Spectrum-400)] was used to understand the chemical structure of the CuO nanoparticles. The nanoparticles were characterised using Bruker D8 advance X-ray powder diffractometer (powder XRD, X-ray wavelength = 1.5405 Å) to analyse the phase and average grain size of the CuO nanoparticles. High Resolution Transmission Electron Microscopy [(HR-TEM) (JEOL JEM 2100 at 200 kV)] was carried out to analyse the size, shape and crystalline nature of the nanoparticles. 4. Results and Discussions 4.1. Spectroscopic Analysis The UV-visible spectroscopy of CuO nanoparticles was taken immediately by dispersing in water through sonication. It shows a broad absorption band centred at 350 nm (fig.1a). The presence of broad band from 350 nm to 500 nm may be due to non-spherical structure i.e. flowering like structure [22] of the obtained nanoparticles which was also confirmed from HR-TEM. FTIR spectra show bands at 595 cm-1 and 538 cm-1 which signifies the presence of Cu-O bonds (fig. 1b). The absence of bands between 600-700 cm-1 shows the absence of cuprous oxide (Cu-O vibrations in Cu2O) nanoparticles [23] and formation of pure monoclinic cupric oxide (presence of stretching in CuO in CuO) nanoparticles [24,25]. The bands at 3434 cm-1 and 1632 cm-1 show the presence of O-H and H-O-H bonds which may be due to the hygroscopic nature of the sample. Bands at 1475 cm-1 and 1384 cm-1 corresponds to C-H bond, 1107 cm-1 and 1051 cm-1 corresponds to C-O bond and 927 cm-1 corresponds to C-S bond of the surfactant used.
Fig. 1. (a) UV-visible spectroscopy of CuO nanoparticle; (b) FTIR spectrum of the synthesized CuO nanoparticles.
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4.2. Structural Analysis From powder XRD pattern (fig. 2), the peaks show pure monoclinic structure of the CuO nanoparticles. No other peaks of Cu2O or Cu(OH)2 are observed. We observed two prominent peaks at 2Ɵ = 34.7º and 37.9º which corresponds to 110 and (111) planes of the monoclinic phase. The details of the peaks obtained are shown in table 1. The observed diffraction peak patterns were compared with Joint Committee on Powder Diffraction Standards (JCPDS) standard values (CAS no. 89-5895). The average grain size was calculated using Debye-Scherrer formula (eqn1) where k is Scherrer constant, which accounts for the shape of the particle whose value is taken as 0.9, β is full width at half maximum, values calculated are reported in table 1, λ is the Radiation Wavelength (1.5405 Å). The various XRD properties calculated for synthesised CuO nanoparticles are reported in table 1. The average grain size was calculated to be 10 nm.
D
k cos
(1)
HR-TEM images show the formation of rod-like cupric oxide nanoparticles of sizes 6-15 nm which is in concordance with XRD results (fig. 3a). The length of the nanoparticles is in the range 25 nm to 50 nm. A d-spacing of 0.25 nm and 0.23 nm was observed which corresponds to 110 and (111) planes of monoclinic structure (fig. 3b). The selected area electron diffraction (SAED) pattern clearly shows the polycrystalline nature of the nanoparticles (fig. 3c).
Fig. 2. XRD of CuO nanoparticles. Table.1: Detailed specifications of XRD peaks. 2Ɵ
d spacing
FWHM
hkl
Lattice constant
Crystallite size
31.8257
2.808
0.502
110
3.974
16
34.7954
2.575
0.794
110
3.642
10
37.9345
2.369
1.012
111
4.103
8
48.265
1.883
0.842
202
5.338
10
57.454
1.602
0.637
202
4.532
12
60.9356
1.518
0.735
113
5.037
11
65.5016
1.423
1.385
311
4.721
6
67.2709
1.39
0.883
220
3.93
9
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Fig. 3. (a) TEM results showing rodlike nanostructure of CuO nanoparticles; (b) Allignment showing a d-spacing of 0.25nm and 0.23nm; (c) SAED pattern of CuO nanoparticles; (d) shows the size of the nanorods.
5. Preparation of Nanofluids The nanofluids were prepared by weighing (0.0284 - 0.1136 gm) the characterized CuO nanoparticles and dispersing them in ethylene glycol base fluid (0.02% - 0.08% volume concentration, vol. %), using the law of mixtures (eqn. 2). The specifications of variables are reported under nomenclature. 3
The density of CuO
3
nanoparticles (6.3 gm/cm ) and that of base fluid (1.11 gm/cm ) was taken to calculate the vol. % of the dispersed nanofluids (25 ml).
wnp vol %
np wnp
np
wbf
(2)
bf
The pH of the CuONF without manipulating the medium was 9 (alkaline). The nanofluid was adjusted to pH 5 and 11 using HCl and NaOH to check stability and observed a more stable suspension in the acidic medium i.e. at a pH of 5. Where at pH 5 the CuONF is stable for four days and pH 9 and pH 11 are stable only for a day. 5. 1. Physicochemical Properties Studies 5.1.1. Density Density was measured using specific gravity bottle and water bath was used for adjusting temperatures. Density of the CuONF was observed to increase with addition of nanoparticles and decreasing with increment in temperature. The experimental data was correlated with the Pak and Cho model (eqn. 3) and an agreement was
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observed for low volume fractions of the nanofluids but deviating to a higher density for higher volume fraction nanofluids (fig. 4(a-d)). At acidic pH, the density of CuO nanofluids was found to remain constant on addition of nanoparticles to the base fluid.
nf np 1 bf
(3)
Fig. 4. (a) Density plot showing an increase in density with increase in volume concentration at pH 9; (b) density plots with Pak and Cho model; (c) density decreases with increase in temperature; (d) pH 9 nanofluid shows higher viscosity compared to pH 5 nanofluid; (e) density at pH 5.
5.1.2. Rheology The rheological behaviour of the nanofluids was measured using Rheolabqc (Anton Paar) which is attached to a water bath for adjusting temperatures. A viscosity of 0.0169 Pa.s at 250C was obtained for the base fluid pure ethylene glycol which is in correlation with the literature data. The viscosity data was therefore analysed for the variable volume fraction of the CuONF. From the rheology analysis, a linear relationship was observed between shear rate and shear stress suggesting the Newtonian behaviour of the CuO nanofluids (fig. 5a). A decrease in viscosity was observed with the increase in temperature. An increase in viscosity was observed from 0.02% to 0.06% but decreases in the 0.08% volume concentration which may be due to overloading of nanoparticles leading to agglomeration at a higher rate thereby induce higher rate of sedimentation (fig. 5b). A plot between viscosity and shear rate shows that viscosity is independent of shear rate which also proves the Newtonian behaviour of the
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CuONF (fig. 5c). The viscosity of the nanofluid was observed to be higher at pH 5 than pH 9 and pH 11 of the sample loaded at 0.06% (fig. 5d). The higher viscosity of the CuONF in the acidic medium might lead to high pumping power and reduce the efficiency of the nanofluid. Viscosity of CuONF at acidic medium was observed to remain almost constant on addition of nanoparticles (fig. 5e) which is also the case for density. This behaviour was also observed by Zhao et al. [26] for silicon dioxide nanofluids of particles size less than 20 nm. Models (Einstein (eqn. 4), Batchelor (eqn. 5) and Wang (eqn. 6)) were applied for the present experimental data and observed that the classical models are unable to predict the viscosity of CuO nanorods-ethylene glycol based nanofluids (fig. 5f).
nf bf 1 2.5
nf bf 1 2.5 6.2
nf bf
1 7.3 123
(4)
2
(5)
2
(6)
Fig. 5. (a) Shear stress vs shear rate plot showing linear relationship; (b) plot between viscosity and volume concentration showing increase with increase volume concentration till 0.06% and decrease with increasing temperature at pH 9; (c) linear relationship plot between viscosity and shear rate; (d) viscosity plot at different pH; (e) viscosity at pH 5; (f) correlation of the experimental data with theoretical models.
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5.1.3. Electrical Conductivity Electrical Conductivity was measured using microprocessor based conductivity meter. Few studies have been done on the electrical properties of nanofluids. Baby et. al. [27] studied on the electrical conductivity of CuO and copper oxide decorated graphene (CuO/HEG) and found an increment with the volume fraction and temperature. In this study we also observed the same behaviour where electrical conductivity was increased on the addition of nanoparticles to the base fluids and with increase in the temperature (fig. 6a & 6b). This shows correlation behaviour between electrical conductivity and density of the CuONF, where at higher volume fraction density increases which may increase the number of ions present thereby increase the electrical conductivity. Acidic nature of the CuONF possesses higher electrical conductivity compared to basic nature which clearly shows that acidic medium is more applicable as coolants in electronic devices (fig. 6c). Electrical conductivity was found to be highest at volume concentration 0.06% in acidic medium (fig. 6d).
Fig. 6. (a) Electrical conductivity plot against volume concentration showing increment on addition of nanoparticles at pH 9; (b) electrical conductivity plot against temperature showing increment with increase in temperature; (c) plot showing higher electrical conductivity for acidic medium rather than basic medium; (d) electrical conductivity at pH 5. 6. Conclusion The CuONF is more stable in acidic medium compared to basic medium. Density of CuONF increases with increase in volume concentration and decreases with increase in temperature. But the experimental viscosity values do not show a linear trend with volume fraction of the nanoparticles. The nanofluids show a Newtonian behaviour. The electrical conductivity of the nanofluids is proportional to volume fraction and temperature. The electrical conductivity and density experimental value correlates with each other but disparity behaviour was observed with viscosity experimental values on altering volume fraction. In acidic medium both density and viscosity remain constant on nanoparticles addition. More work should be done to understand the correlation between these physicochemical properties. The Pak and Cho density model correlates with the experimental results at lower volume fraction of the nanoparticles. But viscosity classical models contradict the experimental results. Therefore, the effect of all entity in nanofluids should be engaged to predict theoretically the behaviour of nanofluids.
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Acknowledgement The authors are highly grateful to SAIF, NEHU, Shillong and Tezpur University, Assam for providing the facility of HRTEM and Powder XRD respectively and Department of Chemistry, NEHU, Shillong for FTIR. The authors are grateful to UGC, India for financial support. References [1] L. Zhang, W. Yu,D. Zhu, H. Xie,G. Huang, J. of Nanomaterials 2017 (2017) 5802016. [2] S. Bhanushali, N. N. Jason, P. Ghosh, A. Ganesh,G. P Simon, W. Cheng, ACS Appl. Mater. Interfaces 9 (2017) 18925−18935. [3] J. Garg, B. Poudel, M. Chiesa, J. B. Gordon, J. J. Ma, J. B. Wang, Z. F. Ren, Y. T. Kang, H. Ohtani, J. Nanda, G. H. McKinley, G. Chen, J. App. Phy.103 (2008) 074301. [4] N. S. Nagulkar, S. M. Lawankar, Inter. Res. J. Eng. and Tech. 4 (2017) 2584-2588. [5] S. Kim, H. C. Kwon, D. Lee, H. S. Lee, Met. Mater. Int. 23 (2017) 1144-1149. [6] R. Dharmalingama, K. K.Sivagnanaprabhub, B. S. Kumar, R. Thirumalaid, Procedia Eng. 97 (2014) 1434 – 1441. [7] N. Sandeep, R. P. Sharma, M. Ferdows, J. Molecular Liq. 234 (2017) 437–443. [8] S. M. S. Murshed, S. H. Tan, N. T. Nguyen, J. Phy. D 41 (2008) 085502. [9] K. F. V. Wong, T. Kurma, Nanotechn. 19 (2008) 345702. [10] H. Chen, Y. Ding, Y. He, C. Tan, Chem. Phys. Lett. 444 (2007) 333–337. [11] M. T. Jamal-Abad, M. Dehghan, S. Saedodin, M. S.Valipour, A. Zamzamian, J. Heat and Mass Trans. Res. 1 (2014) 17-23. [12] M. J. Pastoriza-Gallego, L. Lugo, J. L. Legido, M. M. Piñeiro, Nanoscale Res. Lett. 6 (2011) 560. [13] R. Sadri, K. Z. Kamali, M. Hosseini, N. Zubir, S. N. Kazi, G. Ahmadi, M. Dahari, N. M. Huang, A. M. Golsheikh, J. Dispersion Sci. and Tech. 38 (2017) 1302–1310. [14] S. K. Das, N. Putra, W. Roetzel, Inter. J. Heat and Mass Trans. 46 (2003) 851–862. [15] M. J. Pastoriza-Gallego, L. Lugo, J. L. Legido, M. M. Piñeiro, Nanoscale Res. Lett. 6 (2011) 221. [16] D. P. Kularni, D. K. Das, S. L. Patil, J. Nanosci. and Nanotech. 7 (2007) 2318-2322. [17] D. P. Kulkarni, D. K. Das, G. A. Chukwu, J. Nanosci. and Nanotech. 6 (2006) 1–5. [18] P. K. Namburu, D. P. Kulkarni, D. Misra, D. K. Das, Exp. Therm. Fluid Sci. 32 (2007) 397–402. [19] S. Kumar, G.S. Sokhal, J. Singh, J. Eng. Res. Appl. 4 (2014) 28-37. [20] S. N. Shoghl , J. Jamali , M. K. Moraveji, Exp. Ther. and Fluid Sci. 74 (2016) 339-346. [21] M. T. Naik, G. R. Janardhana, K. V. K. Reddy, B. S. Reddy, J. Eng. Appl. Sci. 5 (2010) 29–34. [22] L. Chen, Y. Zhang, P. Zhu, F. Zhou, W. Zeng, D. D. Lu, R. Sun, C. Wong, Sci. Rep. 5 (2015) 1-7. [23] D. Guo, L. Wang, Y. Du, Z. Ma, L. Shen, Mater. Lett. 160 (2015) 541-543. [24] V. V. T. Padil, M. Cerník, Int. J. Nanomedicine 8 (2013) 889-898. [25] M. Gopalakrishnan, A. K. S. Jeevaraj, Mat. Sci. Semiconductor Processing 26 (2014) 512–515. [26] Z. Jia-Fei, L. Zhong-Yang, N. Ming-Jiang, C. Ke-Fa. Chin, Phy. Lett. 26 (2009) 066202. [27] T. T. Baby, R. Sundara, J. Phys. Chem. C 115 (2011) 8527–8533.