Effect of surfactant on thermo-physical properties and spray cooling heat transfer performance of Cu-Zn-Al LDH nanofluid

Applied Clay Science 168 (2019) 43–55

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Research Paper

Effect of surfactant on thermo-physical properties and spray cooling heat transfer performance of Cu-Zn-Al LDH nanofluid Samarshi Chakrabortya, Iman Senguptaa, Ishita Sarkara, Surjya K. Palb, Sudipto Chakrabortya, a b

T ⁎

Department of Chemical Engineering, Indian Institute of Technology Kharagpur, India Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, India

ARTICLE INFO

ABSTRACT

Keywords: Cu-Zn-Al LDH Nanofluid Surfactant Spray cooling Steel plate Cooling rate

The focus of the present study is to investigate the effect of surfactant addition on thermo-physical properties, stability, and heat transfer performance of Cu-Zn-Al LDH nanofluid. For this purpose, both an anionic (Sodium dodecyl Sulfate (SDS), concentration: 200–800 ppm) and a non-ionic surfactant (Tween 20, concentration: 28–70 ppm) have been used at different concentrations with Cu-Zn-Al LDH nanofluid at a fixed concentration. Among both the surfactants, SDS displayed better compatibility and thermo-physical properties when combined with Cu-Zn-Al LDH nanofluid compared to LDH-Tween 20 combination. The addition of both the surfactants into the nanofluid suspension has led to reduced surface tension and viscosity value which is highly desired for better wettability and improved contact between the coolant and the hot surface. The maximum increment in thermal conductivity value was attained in the case of Cu-Zn-Al LDH at 600 ppm SDS concentration which is 20.9% higher than the water. In terms of stability analysis, the highest zeta potential value of −52.7 mV was also observed for Cu-Zn-Al LDH at 800 ppm SDS loading. The highest cooling rate of 174.8 °C/s was attained by CuZn-Al LDH-SDS (600 ppm) nanofluid which is 30.7% higher than what had been achieved by water based cooling. However, the use of Tween 20 in LDH nanofluid has displayed detrimental impact on poor thermal conductivity, zeta potential, and heat transfer results for the LDH nanofluid.

1. Introduction In general, there exists a perception that the addition of surfactant in nanofluid leads to enhancement in nanofluids stability, thermal conductivity as well as heat transfer performance (Ravikumar et al., 2015b). Here, an attempt has been made to verify such perceptions for Cu-Zn-Al LDH nanofluid using two different types of surfactant (anionic and non-ionic). Since, the inventions of nanofluid in 1993 by Stefan U.S. Choi (Choi, 1995), many researchers (Chakraborty et al., 2015; Das et al., 2003a,b; Eastman et al., 2011, 2004; Lee et al., 1999; Mitra et al., 2012; Murshed et al., 2005, 2008; Patel et al., 2003) have studied its potential as an highly efficient engineered coolant. Nanofluid basically consists of two key component, one is base fluid (water, oil, alcohol etc.) and the other one is the dispersed phase (particle having at least one dimension lower than 100 nm.). Majority of the research on nanofluid is mainly restricted to three types of nanofluid, namely metal based (Cu, Fe, Au etc.) (Hong et al., 2005; Patel et al., 2003; Xuan and

Li, 2000), metal oxide based (TiO2, Al2O3, CuO, ZnO etc.) (Das et al., 2006; Lee et al., 1999; Murshed et al., 2005; Xie et al., 2002), and nonmetallic/carbon based (Assael et al., 2004; Assael et al., 2005; Baby and Ramaprabhu, 2011; Kole and Dey, 2013; Wozniak et al., 2013). In this work, a new breed of mixed-metal based nanofluid has been synthesized and implemented for heat transfer application. Nanofluid has found relevance in widespread applications like industrial heat exchangers, electronic chip cooling, automobile engine (as lubricants and coolants), refrigerator, and nuclear power plant (as a coolant for nuclear fuel rod). In order to achieve industrial applicability, other than having higher thermal conductivity value, higher stability is also greatly desired to make the nanofluids useable for a long duration of time. Implementation of dispersants (surfactants and polymer) in nanofluid suspension is one of the ways of achieving highly stable nanofluid suspension. Several researchers have studied the effect of surfactant addition on various aspects of nanofluid properties and heat transfer performance. Among them, thermal conductivity and stability

Abbreviation: AHF, Average heat flux; AHTC, Average heat transfer coefficient; ASME, American Society of Mechanical Engineers; EDS, Energy dispersive spectroscopy; FESEM, Field emission scanning electron microscope; FTIR, Fourier transform infrared spectroscope; LDH, Layered double hydroxide; SDS, Sodium dodecyl sulphate; TC, Thermocouple; TEM, Transmission electron microscope ⁎ Correspondent author at: Chemical Engineering Department, IIT Kharagpur, Kharagpur 721302, West Bengal, India. E-mail address: [email protected] (S. Chakraborty). https://doi.org/10.1016/j.clay.2018.10.018 Received 29 June 2018; Received in revised form 20 September 2018; Accepted 27 October 2018 0169-1317/ © 2018 Elsevier B.V. All rights reserved.

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from the above literature review that there are several contradictory findings on the heat transfer results and thermal properties of surfactant and nanofluid combination (Chen and Xie, 2010; Kim et al., 2006; Liu et al., 2005). However, most of the works agree on the beneficial effect of surfactant on stability (Bystrzejewski et al., 2010; Manjula et al., 2005; Witharana et al., 2013; Wusiman et al., 2013). The intended application for the nanofluid-surfactant combination under investigation is in steel quenching at experimental condition similar to the run out table of hot strip mill. The high temperature steel quenching plays a major role in determining mechanical properties of steel strip as it has been found out that rapid cooling of steel in the temperature range of 900-600 °C promotes desirable microstructural phase change and improves mechanical properties like hardness and tensile strength (Mohapatra et al., 2013; Ravikumar et al., 2013a). Here in this study, the objective of the research is to attain ultrafast cooling (UFC) of steel (for 6 mm thick steel plate cooling rate > 133.33 °C/s between 900 and 600 °C) using surfactant added nanofluid based spray cooling. Achievement of ultrafast cooling is considered pivotal to the desired phase transformation of steel (Jha et al., 2015; Witharana et al., 2013; Ravikumar et al., 2013a; Ravikumar et al., 2014). In the present study, the aim is to augment the thermal efficiency and stability of nanofluid by introducing surfactant into the solution. When nanofluid is used as a coolant during the boiling process, nanoparticle starts to deposit on the surface which increases the number of nucleation site which in turn helps to improve heat transfer performance (Liang and Mudawar, 2018). Nanoparticle deposition on the hot surface can also alter its wetting characteristics (Liu and Liao, 2008). In case of pool boiling experiments, the nanoparticle deposition hinders the formation of stable vapor film which plays a crucial impact on the heat transfer performance (Park et al., 2004). The suspended nanoparticle can also give rise to micro-convection and thermal interaction (Das et al., 2003a; Das et al., 2006). Implementation of surfactant in the nanofluid can further enhance the wetting characteristics and help to improve the heat transfer results. The research on the effect of surfactant addition on nanofluid suspension mainly restricted to metal, metal oxide and carbon based nanofluids. The consequence of surfactant on the thermo-physical properties and heat transfer performance of mixed metal based nanofluid namely Layered Double Hydroxide (LDH, Chemical Formula:[M2+ 1-x x+ M3+ (Am-)x/m, yH2O) (Wang and O'Hare, 2012) is the relax (OH)2] tively unexplored domain of research. Layered Double hydroxide is a hydrophilic clay consisting of positively charged brucite type layer 3+ (metal hydroxide, M2+ 1-x Mx (OH)2) and interlayer anion (solvent molecule and NO3− present in the metal nitrate salts). In one of our recent works (Chakraborty et al., 2015), CueAl LDH nanofluid has been prepared by using the co-precipitation method. The synthesized nanofluid improved the thermal conductivity value and also displayed high zeta potential value. Tiara et al. (2017b) studied the influence of ZneAl LDH nanofluid concentration variation on thermal conductivity (enhancement of 10.8%) and jet cooling heat transfer of hot steel plate. Similar work has also been carried out by Sarkar et al. (2017) using CueAl LDH nanofluid where authors have observed 41% enhancement in cooling rates. In one of our recently published work, Cu-Zn-Al LDH nanofluid has been used at a different concentration (without surfactant) for spray

Nomenclature Cp k

Specific heat capacity of steel plate Thermal conductivity of steel plate

Greek letter α ρ

Thermal diffusivity of steel Density of the steel plate

are the most researched topic of interest. The thermal conductivity of nanofluid can be boosted by multiple factors such as particle concentration, particle size and shape, Brownian motion, dispersion stability, nature of base-fluid, nanofluid temperature, and addition of surfactant (Das et al., 2006, 2003b; Eapen et al., 2010; Prasher et al., 2005; Prasher et al., 2006; Xie et al., 2011). Keblinski et al. (2002) proposed that other than Brownian motion; liquid layering and optimum clustering can also contribute to thermal conductivity enhancement. Among all the aforementioned criteria, the consequence of surfactant addition on thermal conductivity enhancement and heat transfer performance of Cu-Zn-Al LDH nanofluid is the focus of the current study. Assael et al. (2004) observed that the CNT based nanofluid with surfactant (Sodium dodecyl sulphate, SDS and Cetyltrimethyl ammonium bromide, CTAB) showed higher thermal conductivity value than nanofluid suspension without surfactant. Addition of SDBS was found to be advantageous for increasing thermal conductivity value of CNT based nanofluid compared to base fluid (Wusiman et al., 2013) whereas the trend is entirely opposite when SDS is implemented as a dispersant. It is also to be pointed out that with an increase in surfactant concentration in both the cases lead to a reduction in thermal conductivity value. Researchers have also observed that addition of Sodium dodecyl benzene sulfonate (SDBS) in Cu-water nanofluid lead to improved stability and uniformly distributed nanofluid (Li et al., 2007). Witharana et al. investigated the effect of different surfactant addition on the stability of metal oxide based nanofluids (TiO2, Al2O3, and ZnO) (Witharana et al., 2013). Addition of surfactant in nanofluid also reduces the surface tension of coolant which in turn leads to improved wettability and the contact area between the coolant and hot surface (Ravikumar et al., 2014; Tiara et al., 2017a). Some researchers have also reported positive attributes of surfactant addition on thermal conductivity and heat transfer performance of nanofluid (Ravikumar et al., 2015b; Tiara et al., 2017a). Use of cationic Gemini surfactant in excess amount may lead to augmented nanofluid (water-MWCNT nanofluid) stability but can also reduce thermal conductivity value (Zana et al., 1991). Xuan et al. (2013) also found the presence of SDBS in Cu –water nanofluid improves stability and thermal conductivity of nanofluid but deteriorates jet impingement heat transfer coefficient value with increasing surfactant concentration as deposition of surfactant molecule forms to a thin layer which hinders heat transfer performance of nanofluid. Addition of surfactant molecules can help to improve nanofluid stability via steric stabilization and help in altering surface properties of the suspended nanoparticle (Ilyas et al., 2014). It is clear Table 1 Raw material chart. Name

Chemical formula

Molecular weight

Manufactured by

Copper nitrate tri-hydrate Aluminium nitrate non-hydrate Zinc nitrate hexa-hydrate Sodium nitrate Sodium hydroxide Sodium dodecyl sulphate Tween 20

Cu(NO3)2.3H2O Al (NO3)3·9H2O Zn (NO3)2·6H2O NaNO3 NaOH C12H25NaSO4 C58H114O26

241.60 375.13 297.48 84.99 40 288.37 1227.54

Merck, India Merck, India Loba Chemie Merck, India Merck, India Merck, India Merck, India

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cooling application. Authors have observed a maximum 18% improvement (160 ppm concentration) in cooling rate compared to water based cooling (Chakraborty et al., 2018b). Therefore, in order to enhance the heat transfer rate and prolong the nanofluid stability, both anionic (SDS) and non-ionic (Tween 20) surfactant has been used as the dispersant. In the current study, the concentration of the nanofluid (160 ppm) is kept constant and the surfactant (SDS and Tween 20) concentration has been varied to check its impact on thermo-physical properties, stability and heat transfer performance during spray cooling. To the best of our knowledge, no work has been reported on the high temperature (temperature range 900600 °C) spray cooling of steel using surfactant aided Cu-Zn-Al LDH nanofluid. The complex chemical structure (cationic layer and anionic interlayer) of LDH and the thermo-physical implication due to the interaction between the surfactant molecule and host LDH makes the study worthy of exploration.

this step, surfactants are added into the nanofluid mixture as per requirement. Post surfactant addition, the mixture is stirred for 12 h followed by 30 min of sonication. Similar steps have been followed for all the surfactant and nanofluid combination. 3. Characterization of nanofluid Thermo-physical properties (thermal conductivity, surface tension, and viscosity), stability, and nanoparticle dispersion of the surfactantnanofluid mixture are the three main topics to be discussed in this section. For thermo-physical characterization of surfactant added LDH nanofluid, three main characterizing tools were used. For thermal conductivity measurement, KD2 thermal analyzer (Decagon device, USA) was used whereas for surface tension measurement, Du-Noüy ring surface tensiometer (Jencon, India) was implemented. Viscosities of all the nanofluids were measured at a constant shear rate of 100 s−1 using MCR 301 Rheometer (Anton Paar, Austria) having a cone and plate geometry. Other than its thermo-physical characterization, stability analysis is also a crucial parameter of consideration which is determined by zeta potential measurement using Zeta Sizer Nano-ZS (Malvern Instrument, USA) and via sedimentation photography (Nikon D7100, Japan). Effectiveness of surfactant addition on nanoparticle dispersion was evaluated by using transmission electron microscopy (TEM) Model: TECNAI G2 20S Twin (FEI Company, USA).

2. Materials and preparation technique 2.1. Materials The materials used for the synthesis of Cu-Zn-Al LDH nanofluids are listed in Table 1. The nanofluid is made out of the nitrate salts of copper (Cu), aluminium (Al), and zinc (Zn). The method used for its preparation is co-precipitation technique which uses 2 M sodium hydroxide solution as precipitating agent. Sodium nitrate (NaNO3) has also been used in this study to provide additional nitrate ions and limit the chance of atmospheric CO2 intercalation. In the current work, Sodium Dodecyl Sulphate (SDS, Anionic Surfactant) and Polysorbate 20(Tween 20, Nonionic Surfactant) have been used as dispersants. Distilled water has been used as the basefluid for nanofluid preparation.

3.1. Thermo-physical properties of nanofluid It is believed to be the most significant properties of any coolant. These properties have a direct implication on the heat transfer performance of nanofluid. Surfactant addition in nanofluid can alter its thermal conductivity, surface tension and viscosity value which can ultimately impact the heat transfer results.

2.2. Preparation of surfactant added Cu-Zn-Al LDH nanofluids

3.1.1. Thermal conductivity analysis The thermal conductivity of nanofluid is the most crucial parameters for estimating the heat transfer potential of nanofluid. Surfactant addition in the nanotube is considered beneficial for thermal conductivity by several scientists (Assael et al., 2004; Liu et al., 2005; Ravikumar et al., 2015b; Tiara et al., 2017a; Tiara et al., 2016). Due to high surface activity and augmented Van der Waal force in nanoparticles, it tends to form clusters at higher nanoparticle loading. Excessive clustering tendency can lead to poor stability and thermal conductivity value. Well dispersed, high aspect ratio nanoparticles display enhanced thermal conductivity value as observed by several scientists (Assael et al., 2005; Chen and Xie, 2010; Sadri et al., 2014). The nanoparticle (Cu-Zn-Al LDH) used for this study has a high aspect ratio (rod shaped) which advantageous in terms of having higher thermal conductivity value (Chakraborty et al., 2015). High aspect ratio nanoparticle also forms a cluster which creates a detrimental effect on nanofluid stability at a higher concentration. Implementation of surfactant/dispersant is intended to counteract against the problem of particle aggregation and its impact on thermal conductivity value.

In the current work, nanofluid synthesis scheme were kept exactly same to what had been described in our earlier study (Chakraborty et al., 2018b; Chakraborty et al., 2015). In this work, efforts have been made to investigate the influence of dispersant (surfactant) addition on the thermo-physical properties, stability and heat transfer performance in spray cooling of hot steel plate. Two kinds of surfactants have been used in this study, a) anionic surfactant (SDS), and b) non-ionic (Tween 20) surfactant. Here, the surfactant concentration has been varied to obtain the perfect surfactant and nanofluid combination. In order to achieve the desired goal, SDS and Tween 20 concentration has been varied between 200 and 800 ppm, and 28–70 ppm, respectively. For nanofluid preparation, Cu, Al, and Zn nitrate salts (Molar Ratio: 4:1:1) are dissolved in water and 2 M NaOH solution has been added in the mixture to increase the pH up to 10.7 and then the solution is stirred for 16 h. The final solution is then filtered using to obtain LDH precipitate. The highly basic (pH 10.7) LDH filtrate is then water washed to eliminate excess NaOH and the precipitate is re dispersed in water using a magnetic stirrer and an ultrasonic bath to create final nanofluid. During Table 2 Thermal conductivity chart for all the surfactant and nanofluid combination. Nanofluid

Surfactant

Thermal conductivity (W/m.K)

Standard error

Cu-Zn-Al LDH (160 ppm)

– Anionic, SDS (200 ppm) Anionic, SDS (400 ppm) Anionic, SDS (600 ppm) Anionic, SDS (800 ppm) Non-ionic, Tween 20 (28 ppm) Non-ionic, Tween 20 (42 ppm) Non-ionic, Tween 20 (56 ppm) Non-ionic, Tween 20 (70 ppm)

0.67 0.61 0.65 0.71 0.68 0.65 0.64 0.63 0.61

0.012 0.010 0.005 0.007 0.007 0.008 0.011 0.003 0.007

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Here, in the present study addition of non-ionic surfactant (Tween 20) into the nanofluid (Cu-Zn-Al LDH) has led to poor thermal conductivity value of the suspension. Table 2 shows the variation in thermal conductivity value with altering Tween 20 concentration (28–70 ppm). The reduction in thermal conductivity value of nanofluid has also been observed by several other researchers using different surfactants (Wusiman et al., 2013; Zana et al., 1991). However, in the case of SDS, the thermal conductivity variation is much more complicated. At a lower concentration of SDS (200 ppm), the dispersant addition has an unfavorable effect on thermal conductivity value. Poor value of thermal conductivity is attributed to poor stability of nanofluid suspension at lower SDS concentration which is clearly observed in the zeta potential analysis. However, as the surfactant concentration is further augmented, it leads to an increment in the thermal conductivity value of the suspension. When the concentration reached 600 ppm, the maximum augmentation in thermal conductivity is observed. Table 2 depicts the thermal conductivity value of SDS-LDH nanofluid combination with varying SDS concentration. The interaction between LDH nanoparticles and Tween 20 surfactants leads to clustering of particles (refer to TEM images in Section 3.3), which severely affect the stability, as well as thermal conductivity. The lattice formation of LDH nanoparticles is interrupted by the introduction of Tween 20, which hinders heat transport through the nanofluid medium and hence thermal conductivity of nanofluid is affected. Nanoparticles become uniformly dispersed with the introduction of SDS to the nanofluids, which promotes heat transport in the nanofluid medium and hence thermal conductivity of the medium enhances. At low SDS concentration (200 ppm), sedimentation of nanoparticles is observed (Fig. 1) because of the opposite charge of surfactant and nanoparticles in the solution. Therefore, thermal conductivity is severely affected. At higher concentration, surfactant stabilizes the nanofluid solutions by promoting uniform dispersion of nanoparticles in a liquid medium, which owes to the reason of electrostatic repulsion between anionic tails of surfactants, attached to LDH nanoparticles.

3.1.2. Surface tension analysis LDH nanofluids do not show significant alteration in surface tension value by concentration variation (Chakraborty et al., 2018b; Chakraborty et al., 2015) value. However, in this work surfactants were added into the nanofluid which significantly reduced the surface tension value (See Table 3). Surfactant consists of two parts one is the nonpolar tail and the other is the polar head. The non-polar tail part weakens the hydrogen bonds between other water molecules which help in reducing the surface tension value. Addition of both Tween 20 and SDS lead to a reduction in surface tension value. However, reduction in surface tension is marginally higher in case of SDS added nanofluid samples. The decline in surface tension of a nanofluid by the introduction of surfactant has been observed by several researchers (Harikrishnan et al., 2017; Tanaka et al., 2017; Tanvir and Qiao, 2012).With augmentation in surfactant loading in the nanofluid, surface tension values constantly decline until the surfactant concentration reaches its CMC value. The maximum reduction in surface tension value has been witnessed in case of 800 ppm SDS concentration using 160 ppm of Cu-Zn-Al LDH nanofluid. Detailed surface tension value of surfactant added nanofluid suspension is reported in Table 3 which also provides standard error data for all the measurements. 3.1.3. Viscosity analysis In this study, the addition of dispersant in nanofluid has led to a reduction in viscosity value compared to nanofluid without surfactant. Table 4 shows the change in viscosity value in nanofluid by the addition of surfactants. Surfactant added nanofluid showed lower viscosity value than the nanofluid without surfactant. Reduction in viscosity value by the inclusion of surfactant in nanofluid has also been observed by several other scientists (Alphonse et al., 2009; Sharma et al., 2016; Tiara et al., 2017a; Tiara et al., 2016; Tseng and Chen, 2003; Tseng and Lin, 2003) where studies have been conducted on different (Al2O3, CueAl LDH, TiO2, Ni, BaTiO3) nanofluid using various surfactants/ dispersants (PEG,SDS, CTAB, Tween 20, PVP and other polymeric dispersants).Some scientists have also reported that the nanofluid viscosity

Fig. 1. Sedimentation images of Cu-Zn-Al LDH nanofluid aided with SDS and Tween 20 surfactant at different time intervals. 46

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Table 3 Surface tension chart for all the surfactant and nanofluid combination. Nanofluid

Surfactant

Surface tension (dynes/cm)

Standard error

Cu-Zn-Al LDH (160 ppm)

– Anionic, SDS (200 ppm) Anionic, SDS (400 ppm) Anionic, SDS (600 ppm) Anionic, SDS (800 ppm) Non-ionic, Tween 20 (28 ppm) Non-ionic, Tween 20 (42 ppm) Non-ionic, Tween 20 (56 ppm) Non-ionic, Tween 20 (70 ppm)

71.8 51.7 48.9 41.6 40.2 50.4 45.7 43.4 40.2

0.10 0.26 0.38 0.19 0.51 0.28 0.40 0.13 0.34

can also increase due to surfactant addition (Sharma et al., 2016; Wang et al., 2012). In spite of the existing contradictory opinions on the impact of surfactant addition on nanofluid viscosity value, the positive effect of reduced viscosity on the heat transfer performance of nanofluid is unquestionable. If the coolant has a low viscosity, it can spread more easily and have better surface contact. On the other hand, low viscosity means low pumping cost which is very crucial for industrial applicability of any nanofluid.

Table 5 Effect of surfactant concentration change on zeta potential values of Cu-Zn-Al LDH nanofluid. Coolant

Surfactant

Zeta potential (mV) 2 h

Zeta potential (mV) 1 day

Cu-Zn-Al LDH (160 ppm) Cu:Zn:Al = 4:1:1

– SDS: 200 ppm SDS: 400 ppm SDS: 600 ppm SDS: 800 ppm Tween 20: 28 ppm Tween 20: 42 ppm Tween 20: 56 ppm Tween 20: 70 ppm

38.6 −30.4 −40.5 −46.1 −52.7 25.8

36.6 −29.7 −39 −42.1 −50.6 23.7

26.1

24.3

26.2

23.3

25.4

24

3.2. Stability analysis of nanofluid Stability analysis of surfactant added nanofluid solution showed that addition of non-ionic (Tween 20) surfactant has lead to a reduction in zeta potential value for all the nanofluid samples. However, the addition of SDS showed interesting results as SDS addition in lower concentration (200 ppm SDS) lead to a reduction in zeta potential value. Without the addition of a surfactant, zeta potential value of CuZn-Al LDH was 38 mV. Post SDS addition, zeta potential value shifted from +ve value to a –ve value. At 200 ppm SDS concentration, zeta potential value of the nanofluid was near −30 mV. As the SDS concentration was further enhanced, zeta potential value started to improve. Beyond 400 ppm SDS concentration, zeta potential value reached beyond −45 mV (zeta potential value measured after 2 h). The highest enhancement in zeta potential value was observed for 800 ppm SDS concentration. Irrespective of SDS concentration for the entire LDH-SDS nanofluid samples, the zeta potential value decreases slightly after keeping the solution undisturbed for 24 h.Details of the zeta potential analysis have been displayed in Table 5. It is to be noted for considering any nanofluid to be stable, it is essential to have a zeta potential value of ± 30 mV (Chakraborty et al., 2015). The zeta potential values of aqueous SDS solution (without nanofluid) were measured at 200 and 800 ppm concentration which was −41.9 and − 64.8 mV, respectively. Similarly, the zeta potential value of aqueous Tween 20 solution (without nanofluid) at 28 and 70 ppm concentration was found out to be −11.32 and − 18.3 mV, respectively. The sedimentation photography also showed the addition of Tween 20 in different concentration showed no significant improvement in the stability of LDH nanofluid. Both lower and higher concentration of

Tween 20 (28 ppm & 70 ppm) gave comparable stability. However, at 200 ppm SDS concentration the LDH nanofluid showed significant agglomeration and poor stability, whereas, at 800 ppm SDS concentration, the nanofluid suspension remained highly stable up to 1 day (See Fig. 1) without any sign of sedimentation. The results clearly display that SDS addition at a higher concentration can positively impact the nanofluid stability. As discussed before, LDH exhibits a positive charge in the solution whereas, anionic nature of SDS leads to conjugation of the surfactant tail with the particles. At low concentration of SDS, this leads to the formation of agglomerates. At higher concentration, more surfactant chains get attached to the particles and electrostatic repulsion between the surfactant chains leads to the formation of a stable suspension and uniform dispersion of the LDH nanoparticles in base fluid. Hydrophilic part of Tween 20 gets attached to the hydroxide layers of LDH which causes clustering of particles. Formation of agglomerates leads to poor stability of suspension and phase separation of the solid particles from the solution.

Table 4 Viscosity chart for different nanofluid and surfactant combination. Nanofluid

Surfactant

Viscosity (mPa-s)

Standard error

Cu-Zn-Al LDH (160 ppm)

– Anionic, SDS (200 ppm) Anionic, SDS (400 ppm) Anionic, SDS (600 ppm) Anionic, SDS (800 ppm) Non-ionic, Tween 20 (28 ppm) Non-ionic, Tween 20 (42 ppm) Non-ionic, Tween 20 (56 ppm) Non-ionic, Tween 20 (70 ppm)

1.50 1.12 0.94 0.93 0.91 1.26 0.97 0.92 0.96

0.007 0.002 0.002 0.002 0.002 0.001 0.002 0.002 0.002

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3.3. Effect of surfactant addition on nanoparticle dispersion

inside the furnace. Once all the TCs reach 1050 °C, the steel plate (AISI 304) was removed from the furnace and kept on an insulating resting pad. The steel plate has the following dimensions of 100 mm (length) × 100 mm (breadth) × 6 mm (thickness). In order to accommodate the steel plate, resting pad was ridged as per the steel plate dimensions to limit the heat transfer from non-spray impinging sides of the plate. The coolant flow through the spray nozzle is only allowed once the plate is properly placed on the cooling pad. The flow control unit used in the setup consists of two key parts; a) rotameter and, b) solenoid valve. The spray nozzle used in this study is a full cone spray nozzle (Lechler 460–843-17-CG).The coolant (nanofluid) used for the experiments was provided by a centrifugal pump which is connected to a coolant tank. Transient temperature data recorded during the spray experiment was processed to obtain surface heat flux and temperature data via a commercially obtained 2D inverse heat conduction solver (INTEMP). Brief details on the operating condition and coolant used for this particular study have been shown in Table 6. For surface heat flux and temperature calculation, the steel plate is converted to the 2D computational domain (length x = 100 mm, thickness y = 6 mm) having 7781 nodes and 7500 elements (∆x = 0.4 mm and ∆y = 0.2 mm). The computational domains have 3 TCs placed inside it. The location of TC1, TC2, and TC3 are Node 3816, Node 3891 and Node 3941, respectively. The governing formula for inverse heat conduction calculation is as follows,

To study the effect of surfactant addition on nanoparticle dispersion in basefluid, TEM analyses were conducted for Cu-Zn-Al LDH-SDS and Cu-Zn-Al LDH-Tween 20. TEM images clearly show that addition of Tween 20 into the LDH suspension has no beneficial effect on the nanoparticle distribution quality. With the implementation of Tween 20 in the nanofluid, agglomeration tendency seemed to rise up compared to nanofluid without surfactant. However, the addition of SDS improved the dispersion quality for the nanofluids. In case of LDH-SDS combination, nanoparticle does not form large clusters like in the case of LDHTween 20 nanofluids. Fig. 2 shows the impact of different surfactant addition on the clustering tendency of aforesaid nanofluids. 4. Experimental setup, design, and INTEMP calculation The spray cooling experimental setup consist of seven key elements, a) muffle furnace, b) resting pad, c) spray nozzle, d) centrifugal pump, e) coolant reservoir, f) flow control unit, and g) data acquisition system (See Fig. 3). At first, the steel plate was heated up in a muffle furnace to a temperature of 1050 °C with 3 K type thermocouples (TC) inserted inside it. The inserted thermocouples are used to record the transient temperature data during the spray cooling process which is connected to a data acquisition system (National instrument, NIcDAQ 9174) for storing the data in a computer. The three thermocouples are placed asymmetrically in the steel plate at 3 mm depth from the surface to verify temperature gradient across the surface (TC1 = 20 mm, TC 2 = 50 mm, and TC3 = 70 mm from one side). The TC 2 is placed just below the spray nozzle and TC1 is placed farthest from it. During the start of each experiment, the data acquisition system equipped with LabView software displays the temperature of steel plate

x

k 2T

x2

T x +

+ 2T

y2

y =

T y

k

= Cp

T t

Cp T 1 T = t t

k

where k, ρ, Cp, and α are thermal conductivity, density, specific heat

Fig. 2. TEM analysis of CueAl LDH and Cu-Zn-Al LDH nanofluid aided with SDS and Tween 20 as dispersants. 48

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Fig. 3. Spray cooling experimental setup for steel plate quenching using nanofluid.

capacity, and thermal diffusivity of steel. The thermocouple data is used as the input data for solving the inverse heat conduction problem. Here, in this case, except for the top surface which is the spray impingement surface, all other surfaces are considered adiabatic (See Fig. 4). In the beginning, INTEMP assumes a heat flux value for the top surface and calculates the temperature for all the nodes including the input data node. The difference between the measured data and calculated data is checked and the heat flux value is modified to lower the error value. The non-linear optimization continues until the error value is lower than the pre-defined tolerance limit. For surface heat flux calculation, the entire upper surface is separated into three zones, Flux 1, Flux 2 and Flux 3 (See Fig. 4) having varying heat flux value. Details about the INTEMP software and calculation procedure can be found in the work of Trujilo and Busby (Busby and Trujillo, 1985; Chakraborty et al., 2018a; Ravikumar et al., 2015a).

Table 6 Experimental design for spray cooling experiments using nanofluid-surfactant. Parameter

Experimental condition

Steel plate temperature Temperature zone of concern Basefluid (water) temperature Water flow rate Coolant pressure Impingement height Spray angle Nanofluid Cu:Zn:Al molar ratio Nanofluid concentration Surfactant used Surfactant concentration

1050 °C 900–600 °C 30 °C 16 lpm. 4 bar 6 cm 45o (with respect to x axis) Water-Cu-Zn-Al LDH 4:1:1 160 ppm Sodium dodecyl sulfate, Tween 20 SDS (200, 400, 600, and 800 ppm), Tween 20 (28,42,56, and 70 ppm)

Fig. 4. Computational domain and boundary condition for surface heat flux and surface temperature calculation. 49

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Fig. 5. (a-b) Effect of SDS concentration on cooling rate and average heat flux values of Cu-Zn-Al LDH-SDS nanofluid.

Fig. 6. (a–b) Effect of Tween 20 concentration on heat transfer results of Cu-ZnAl LDH-Tween 20 nanofluid.

5. Results and discussion

Table 7 Coolant requirement for cooling down the steel plate from 900 to 600 °C.

In this section, authors have discussed the impact of surfactant addition on the heat transfer characteristics of nanofluid. As mentioned in the experimental design table (Table 6), the nanofluid concentration has been kept at 160 ppm for the nanofluid suspension. Several researchers have described the positive effect of surfactant addition on thermal conductivity and heat transfer rate values. However, some studies suggest that surfactant addition in excess amount can lead to a reduction in thermal properties of the nanofluid sample. Therefore, in this section, the focus will be given to study the effect of non-ionic and anionic surfactant concentration on spray cooling heat transfer results. Optimization of surfactant concentration has been done based on the heat transfer results. The spray cooling experiments were conducted on Cu-Zn-Al LDH nanofluid using SDS and Tween 20 as dispersants. The effect of cooling rate variation across three thermocouple location can be found in supplementary document 1 (Transient temperature profile for Cu-Zn-Al-SDS nanofluid at three thermocouple location). The fastest drop in temperature was registered at TC 2 thermocouple for all the nanofluid-surfactant combination as TC2 is placed just below the spray

Nanofluid

Surfactant

Surfactant concentration (ppm)

Cooling rate (oC/s)

Cooling time (s)

Coolant requirement (litre)

Cu-Zn-Al LDH (160 ppm)

SDS SDS SDS SDS SDS Tween Tween Tween Tween Tween

0 200 400 600 800 0 28 42 56 70

158.44 138.51 165.61 174.82 147.33 158.44 134.36 135.55 138.31 135.70

1.89 2.17 1.81 1.72 2.04 1.89 2.23 2.21 2.17 2.21

0.50 0.58 0.48 0.46 0.54 0.50 0.60 0.59 0.58 0.59

20 20 20 20 20

nozzle. Since the fastest temperature drop was attained at TC2, therefore the cooling rate, average heat flux and average heat transfer coefficient values corresponding to TC2 are reported here.

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Fig. 8. (a–b) Synergistic effect of the constituent element on cooling rate performance of; (a) Cu-Zn-Al LDH-SDS, and (b) Cu-Zn-Al LDH-Tween 20 nanofluid.

5.1. Optimization of surfactant concentration variation based on cooling rate and AHF value The first step towards attaining the best surfactant and nanofluid combination for heat transfer application was to analyze its thermophysical properties and stability value. The analysis clearly revealed that in terms of thermal conductivity and stability, the best surfactant and nanofluid combination is SDS- LDH nanofluid (at higher surfactant concentration). The study revealed that at lower SDS concentration (200 ppm) thermal conductivity value declined due to poor stability however with increasing SDS concentration both thermal conductivity and stability starts to improve. The addition of Tween 20 in the nanofluid suspension has led to a reduction in stability as well as thermal conductivity value. In this section, an attempt has been made to check the impact of surfactant addition on heat transfer performance of nanofluid. The heat transfer results were represented in terms of cooling rate value (temperature range 900–600 °C), and average heat flux (by taking an average of all the heat flux data between 900 and 600 °C) value. Fig. 5(a) clearly shows that cooling rate value declines when SDS is added in a lower concentration (200 ppm) as the SDS concentration is

Fig. 7. (a–c) Selection of best nanofluid and surfactant combination based on heat transfer parameter; a) cooling rate, b) AHF, and c) AHTC.

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Table 8 Surface roughness variation due to nanoparticle deposition on steel surface for Cu-Zn-Al LDH-surfactant combination. Coolant

Deposition surface

Surface roughness (μm)

% increment

– Cu-Zn-Al LDH + SDS (600 ppm) Cu-Zn-Al LDH + Tween 20 (56 ppm)

AISI 304 steel plate

4.5 5.5 5.0

– 21.2 9.7

Fig. 9. FESEM analysis of Cu-Zn-Al LDH nanoparticle deposition on the steel surface.

further increased cooling rate also shoots up. The highest enhancement of cooling rate value was observed for Cu-Zn-Al LDH at 600 ppm SDS concentration. The maximum increment in cooling rate and AHF values were 10.3% and 5.6% higher than what attained by pure Cu-Zn-Al LDH nanofluid at 160 ppm concentration (See Fig. 5(a–b)). In case of 800 ppm SDS concentration, although the zeta potential value improved further both the thermal conductivity as well as cooling rate value declined. Such a trend in thermal conductivity may be owed to the fact that excess surfactant loading can hinder the thermal interaction which in turn reduces thermal conductivity (Xie et al., 2011). The similar trend was also replicated in the cooling rate results which also showed a reduction at 800 ppm SDS concentration. The declined value of cooling rate and AHF at higher surfactant concentration can also be owed to excessive foaming tendency of SDS. Cooling rate and AHF is decreased significantly after the addition of Tween 20 to the Cu-Zn-Al LDH nanofluids. This trend in line with the thermal conductivity and zeta potential value obtained for Cu-Zn-Al LDH-Tween 20 nanofluid. Cooling rate and AHF values remained almost constant even after altering the Tween 20 concentration (28–70 ppm) in Cu-Zn-Al LDH nanofluid (Fig. 6(a–b)). The highest cooling rate reported for Cu-Zn-Al LDH-Tween 20 nanofluid was 138.3 °C/s, at a Tween 20 concentration of 56 ppm. In comparison to Cu-Zn-Al LDH without surfactant, both cooling rate and AHF value are significantly lower in case of Tween 20 added-LDH nanofluid. Table 7 depicts the cooling time and coolant requirement for cooling down the steel plate from 900 to 600 °C.

5.2. Selection of best surfactant-nanofluid combination based on heat transfer results To show the comparison between the different surfactant and nanofluid combination, all three heat transfer parameters (cooling rate, average heat flux (AHF), and average heat transfer coefficient (AHTC)) have been plotted in this section. AHTC value was calculated by taking an average of all the heat transfer coefficient value within the temperature range of 900-600 °C. Among all the surfactant and nanofluid combination, Cu-Zn-Al LDH nanofluid with SDS surfactants (600 ppm) gave the highest cooling rate, AHF, AHTC value. The maximum enhancement in cooling rate, AHF and AHTC value was reported to be 30.7%, 14.2%, and 11.8%, respectively as compared to water based cooling. The heat transfer results obtained in this study are in sync with thermal conductivity and zeta potential results where Cu-Zn-Al LDHSDS nanofluid displayed superior behavior than Cu-Zn-Al LDH-Tween 20 nanofluid. Fig. 7 (a–c) shows the variation in cooling rate, AHF and AHTC value for different LDH and surfactant combination. It is also to be noted that maximum cooling rate value attained in case of all LDH and surfactant combination is above the ultrafast cooling rate (for 6 mm thick steel plate cooling rate of > 133.33 °C/s is termed as ultrafast cooling) (Ravikumar et al., 2013b). 5.3. Synergistic effect of the nanofluid-surfactant combination To distinctly separate the heat transfer contribution of each of the 52

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Fig. 11. FTIR Analysis of Cu-Zn-Al LDH nanoparticle.

constituent element, the following study has been carried out for all the surfactant and nanofluid combination. Cooling rate data for pure water, aqueous SDS solution (600 ppm), aqueous Tween 20 solution (56 ppm), Cu-Zn-Al LDH nanofluid (160 ppm), Cu-Zn-Al LDH (160 ppm) - Tween 20 (56 ppm) nanofluid, and Cu-Zn-Al LDH (160 ppm) - SDS (600 ppm) nanofluid has been categorized and plotted in two separate graphs. Fig. 8 (a–b) clearly demonstrates the individual effect of each coolant used for the ongoing study on cooling rate. 5.4. Influence of nanoparticle and surfactant deposition on heat transfer results Thermal conductivity is regarded as the most crucial parameter for evaluating heat transfer potential of nanofluid. In addition to that nanoparticle deposition on heat transfer surface also plays a critical role in heat transfer enhancement via surface roughness increase and by providing additional nucleation sites. As the roughness of the heat transfer surface increases, it hinders the formation of insulating vapor film which can reduce the heat transfer rate at higher surface temperature. Advantages of nanoparticle deposition on heat transfer have been confirmed by several researchers (Barber et al., 2011; Chang et al., 2012; Ravikumar et al., 2015b; Sarkar et al., 2017; Seo and Bang, 2015). In order to conduct the above mentioned study, surface roughness evaluation (SJ-201 P/M, Mitutoyo, Japan) and FESEM analysis (JEOL JSM 7610F, JEOL, USA) were carried out to evaluate the extent of nanoparticle and surfactant deposition on surface roughness alteration after the cooling experiments have taken place. Table 8 shows that the deposition of nanoparticle on the steel surface has significantly improved the surface roughness in all cases. However, due to the addition of SDS and Tween 20 surfactant in LDH nanofluid, excessive deposition has taken place on steel surface which has detrimentally affected heat transfer results in many cases (specially for nanofluids with poor stability and at 800 ppm SDS concentration). Excess deposition on the heat transfer surface has created a nanoparticle and surfactant layer which prevents the contact between the impinging coolant and hot surface. FESEM images clearly show the extent of nanoparticle deposition on steel surface (See Fig. 9). The detrimental effect of excess nanoparticle deposition on heat transfer results has also been reported by several other researchers (Chakraborty et al., 2018a; Liu and Qiu, 2007). To confirm that the particle deposition observed in the above FESEM image is Cu-Zn-Al LDH nanoparticle, Energy Dispersive Spectroscopy (EDS) (JEOL JSM 7610F, JEOL, USA) analysis were

Fig. 10. (a–c). EDS analysis of Cu-Zn-Al LDH+ SDS/Tween 20 deposition on a steel plate; a) steel plate without deposition, b) Cu-Zn-Al LDH + SDS nanoparticle on steel, and c) Cu-Zn-Al LDH + Tween 20 nanoparticle on steel. 53

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conducted. This analysis revealed the presence of Cu, Al, Zn and Na, O along with the constituent elements of steel. Fig. 10 shows the EDS analysis of steel plate pre and post nanoparticle deposition. Fourier Transform Infrared Spectroscope (FTIR) analysis (Spectrometer100, Perkin Elmer, USA) of Cu-Zn-Al LDH nanoparticle was conducted to prove the formation of LDH by analyzing its characteristics function groups. In addition to EDS analysis, FTIR analysis was also conducted on CuZn-Al LDH nanoparticle to confirm the presence of characteristics functional group in it. LDH nanoparticle possesses three distinct functional groups, a) broad hydroxide band, b) NO3− adsorption and vibration band, and c) metal‑oxygen vibration bands. The broad hydroxide band lies in the wavenumber range of 3200–3600 cm−1. NO3− adsorption and vibration bands are observed in the wavenumber of 1385 cm−1(high intensity), 1471 cm−1, and 841 (low intensity). On the other hand, metal oxygen bands are found between 800 and 400 cm−1. FTIR analysis clearly shows the existence of all three characteristics peaks found in LDH (Fig. 11). The present results are in accordance with the findings of several other researchers including our previous work on CueAl LDH (Cavani et al., 1991; Chakraborty et al., 2014; Chakraborty et al., 2018a; Costa et al., 2008).

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6. Conclusion The current chapter deals with the investigation on the thermophysical properties and spray cooling heat transfer performance of CuZn-Al LDH (160 ppm) nanofluid at different concentration of SDS (200–800 ppm) and Tween 20 (28–70 ppm). Other than the thermophysical properties, stability analysis (zeta potential and sedimentation photography) and the study of nanoparticle dispersion with different surfactant (TEM analysis) has also been investigated. FESEM analysis has been carried out to confirm the presence of nanoparticle deposition post spray cooling experiments. Summary of important observations are listed below, 1) Highest improvement in thermal conductivity value was attained in the case of Cu-Zn-Al LDH-SDS (600 ppm) nanofluid which is 20.9% higher than the water. 2) Increase in surfactant concentration in all four LDH-surfactant combinations leads to a reduction in surface tension value. The lowest surface tension value of 40.1 dynes/cm was attained for CuZn-Al LDH-SDS (800 ppm) nanofluid. 3) As per the zeta potential analysis, the highest zeta potential value was achieved by Cu-Zn-Al LDH-SDS (800 ppm) nanofluid. Zeta potential value increased with increasing SDS concentration for Cu-ZnAl LDH nanofluid. On the other hand, irrespective of its concentration addition of Tween 20 lead to poor zeta potential value for both the nanofluids. 4) The highest cooling rate and AHF value of 174.8 °C/s and 1.7 MW/ m2 were attained by Cu-Zn-Al LDH-SDS (600 ppm) nanofluid among all four surfactant-nanofluid combinations. The highest augmentation in cooling rate and AHF value was reported to be 30.7% and 14.2% respectively as compared what had been achieved by water based cooling. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.clay.2018.10.018. References Alphonse, P., Bleta, R., Soules, R., 2009. Effect of PEG on rheology and stability of nanocrystalline titania hydrosols. J. Colloid Interface Sci. 337, 81–87. Assael, M.J., Chen, C.-F., Metaxa, I., Wakeham, W.A., 2004. Thermal conductivity of suspensions of carbon nanotubes in water. Int. J. Thermophys. 25, 971–985.

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