Thermo-physical properties of Cu-Zn-Al LDH nanofluid and its application in spray cooling

Accepted Manuscript Thermo-physical properties of Cu-Zn-Al LDH nanofluid and its application in spray cooling Samarshi Chakraborty, Ishita Sarkar, Avinash Ashok, Iman Sengupta, Surjya K. Pal, Sudipto Chakraborty PII: DOI: Reference:

S1359-4311(18)31500-X https://doi.org/10.1016/j.applthermaleng.2018.05.114 ATE 12253

To appear in:

Applied Thermal Engineering

Received Date: Revised Date: Accepted Date:

8 March 2018 27 May 2018 28 May 2018

Please cite this article as: S. Chakraborty, I. Sarkar, A. Ashok, I. Sengupta, S.K. Pal, S. Chakraborty, Thermophysical properties of Cu-Zn-Al LDH nanofluid and its application in spray cooling, Applied Thermal Engineering (2018), doi: https://doi.org/10.1016/j.applthermaleng.2018.05.114

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Thermo-physical properties of Cu-Zn-Al LDH nanofluid and its application in spray cooling Samarshi Chakraborty a, Ishita Sarkar a, Avinash Ashok a, Iman Senguptaa, Surjya K. Pal b , Sudipto Chakraborty a* a b

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

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

Abstract: The current experimental investigation deals with the thermo-physical attributes of Cu-Zn-Al LDH nanofluid its use in high temperature steel cooling. Here, authors used three metals (Copper, Aluminium, and Zinc) having high thermal conductivity to synthesize a brand new nanofluid for heat transfer application. Authors have achieved moderate increment (13.9%) in thermal conductivity value compared to water. A section of this work also aims to maximize the cooling rate which aids in improving mechanical properties of quenched steel plate. The maximum cooling rate of 158.4oC/sec was attained at 160 ppm of nanofluid concentration which is 18.5% higher than that attained by water. In addition to enhanced thermal conductivity, nanoparticle deposition on the cooling surface also contributes to the heat transfer enhancement by providing additional nucleation site. It is also to be considered that above an optimum nanofluid concentration both thermal conductivity and cooling rate values decline. Such trend is owed to several factors namely poor suspension stability, high agglomeration tendency and formation of nanoparticle layer on steel surface which prevents contact between coolant and surface. Keywords: Cu-Zn-Al LDH, nanofluid, spray cooling, thermal conductivity, cooling rate, average heat flux. 1

* Author to whom all the correspondence should be addressed Sudipto Chakraborty, Chemical Engineering Department, IIT Kharagpur, Kharagpur-721302, West Bengal, India Phone (office): +91 - 3222 -283942 Email: [email protected]

1. Introduction: In the past few decades with continuous growth in nanotechnology, synthesis of nanoparticle has become a reality. In early 1990, an American scientist named Stephan U.S. Choi [1]first used nanoparticle suspension as a coolant. The concept of particle suspension in base fluid is around for an even longer time. However, in spite of giving higher thermal conductivity value than the base fluid, the highly unstable nature of millimeter and micron sized particle suspension made it undesired for heat transfer application. Poor stability of micron sized suspension gives rise to higher sedimentation, higher erosion in heat transfer equipment, high pressure drop, increased pipeline clogging, higher viscosity value and higher pumping cost etc. Therefore, there was a need for a stable particle suspension which would also have a higher thermal conductivity value. In order to achieve stable particle suspension, scientists have used nanoparticle and suspended it in a basefluid. Basefluid having suspended nanoparticle is termed as nanofluid [1]. The beneficial attributes of nanofluids over micron sized particle suspension has been discussed by Das et al. and Li et al. [2, 3] in details. Due to several advantageous attributes, nanofluid has been used for wide range of applications starting from the heat exchanger, electronic chips, microchannel, automobile engine, refrigerators, chillers, and nuclear reactor etc. Among all the attributes of nanofluids, high thermal conductivity value makes it research worthy and specifically crucial for the current study. 2

The present study partially focuses on the high temperature steel plate cooling using nanofluid aided pressurized spray cooling scheme. In steel manufacturing process, run out table plays a decisive part in creating desired microstructure which is responsible for improved mechanical properties (tensile strength). Manufacturing of high strength steel is also possible via a metal alloying technique which is much expensive as compared to the cheaper alternative named ultrafast cooling[4]. Attainment of ultrafast cooling in the run out table (ROT) (Temperature range 900-600oC)is critical for obtaining desired microstructure (combination of austenite and martensite, bainite and pearlite phase, etc.)[5]. When the product between cooling rate and steel plate thickness goes above 800, and then ultrafast cooling is achieved. According to Zhang et al.[6] by using conventional laminar jet cooling and conventional coolant (such as water) attaining such a high cooling rate is difficult. The cooling rate achieved during jet or spray cooling process (under ROT condition) is not only dependent on experimental flow parameters and fluid properties but also on plate thickness and plate composition. To nullify the effect of plate thickness, authors have used 6 mm thick steel plate for all the spray cooling experiments. In order to attain desired cooling rate, both high mass flux spray cooling and advanced coolant are needed. Nanofluid provides a suitable and more efficient alternative to any conventional coolant due to its enhanced thermal properties. In this study, authors are focused on the high temperature applications of nanofluid especially thermal treatment in the steel industry. Nanofluid based cooling of high temperature steel plate is a relatively unexplored domain of research. Chakraborty et al. [7] explored the potential of TiO2-water nanofluid as a coolant to cool down high temperature steel plate by using jet impingement technique and found improvement in cooling rate. Mitra et al.[8] also conducted laminar jet impingement cooling of hot steel plate by using water-TiO2 and water-MWCNT nanofluids and found substantial augmentation in heat

3

transfer rates. Water based cooper[9]and alumina[10] nanofluids were also used by researchers along with an air-atomized spray to cool down high temperature steel plate(>900oC). Implementation of nanofluid for high temperature metal quenching are motivated by several factors such as, 1) increase thermal conductivity of coolant, 2) better suspension stability with limited increase in pumping cost and 3) suspended nanoparticle deposits on the heat transfer surface and aids in surface roughness increase, it provides additional nucleation site and also restricts vapor film formation which can hamper the heat transfer. The possible roadblock for large scale industrial application of nanofluid is its possible environmental impact on aquatic life, human body as well as other environmental impact. In one of the recent works, authors have invented a new breed of nanofluid for heat transfer application which is layered double hydroxide based nanofluid[11]. Layered double hydroxide (LDH) is a layered crystalline material (anionic clay) which has positively charged metal hydroxide sheets compensated by anionic counter ions in the gallery space. LDH is represented by the following chemical formula: [M2+1-x M3+x(OH)2]x+(Am-)x/m x, yH2O, where divalent/bivalent , trivalent are represented by M2+ and M3+ ,respectively[12].Its dynamic chemical formula enables researchers to add multiple metal ions in a single compound. LDH is naturally occurring clay minerals, made out of mostly biocompatible materials[13]. LDH has found application in several field human life including medical application, water treatment process and biological application (ATP, DNA, enzyme intercalation with LDH to avoid degradation). Mg-Al LDH has found application as an antacid and anti-pepsin agent[14]. Mg-Al LDH, Zn-Al LDH, Li-Al LDH and Fe-Al LDH has also been used as a drug delivery agent[15].Above studies confirm the bio-compatibility nature of LDH nanoparticle. Water-Cu-Al LDH[16] and water-Zn-Al LDH[17] nanofluids have already been

4

used as a coolant for jet quenching hot steel plate which gave significant augmentation heat transfer rate compared to water. In the current study, authors have combined three highly thermally conducting metal ions (Cu2+, Zn2+, and Al3+) to form a novel nanofluid which is Cu-Zn-Al LDH nanofluid. No work reported in the open literature has combined thermal attributes of three metal ions into a single nanofluid. Present work centers on the consequence of Cu-Zn-Al LDH nanofluid loading on thermophysical properties as well as its heat transfer application. Implementation of this brand new nanofluid for high temperature metal quenching application makes the present study worthy of investigation.

2. Preparation of Cu-Zn-Al LDH nanofluid: In the present study, Cu-Zn-Al LDH nanofluid was synthesized by co-precipitation methods which uses three metal nitrate salts namely copper (Cu(NO3)2.3H2O), zinc (Zn (NO3)2·6H2O ) and aluminium nitrate(Al (NO3)3·9H2O) and sodium nitrate (NaNO3) in the molar ratio of 4 (Cu2+):1 (Zn+):1 (Al3+):2 (Na+). NaNO3 is used to increase NO3 - ion concentration in the solution and to prevent CO2 intercalation. The aforementioned nitrate salts were dissolved in water and 2 M NaOH was added to the solution until the pH of the solution reaches 10.7. NaOH works as a precipitating agent. The synthesis scheme used in this study was adopted from our earlier work on Cu-Al LDH nanofluid[11]. Post titration, the solution is stirred for 16 hrs and the solution is filtered to bring down the filtrate pH level up to 7. The precipitate is then used to prepare the final nanofluid solution by further stirring it for 12 hrs and followed by 30 minutes of sonication. Nanofluid concentrations were varied between 40 ppm to 240 ppm, to verify its impact on the

5

heat transfer properties. Nanofluid synthesis scheme used for this current study has been depicted in Fig. 1.

Fig. 1.Graphical representation of Cu-Zn-Al LDH nanofluid synthesis method

3. Characterization of Cu-Zn-Al LDH nanoparticle and nanofluid: Characterization of Cu-Zn-Al LDH nanoparticle includes X-Ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FESEM), and Transmission Electron Microscope (TEM) analyses. XRD analysis of Cu-Zn-Al LDH nanoparticle was executed by Philips made XRay Diffractometer (PW-3050/60, Netherlands) having a Cu Kα radiation wavelength, λ of 1.5406 Å. XRD analysis was conducted over a diffraction angle(2θ) range of 8o-70ohaving scan speed of 0.5 sec-1and step increment of 0.05o. FESEM analysis (JEOL JSM 7610F, USA) was performed for both particle morphology and nanoparticle deposition study. Energy dispersive spectroscopy analysis was conducted for the elemental study. For particle size analysis, an FEI

6

made analytical TEM (TECNAI G2 20S Twin, USA) was used. The thermo-physical properties of nanofluid include three main properties which are thermal conductivity, surface tension, and viscosity. The thermal conductivity of all the samples was evaluated by using KD2 thermal conductivity meter manufactured by Decagon Device (USA) which works on the principle of transient needle probe method. The surface tension of nanofluids was measured by Jencon (India) made du Noüy ring surface tensiometer. Static contact angle was measured by using a goniometer (Rame-Hart 190-F2, USA). For viscosity measurement, authors have used a cone and plate rheometer (Physica MCR 301, Austria). Viscosities of all the nanofluid samples were measured at a fixed shear rate of 100 sec -1. All the thermo-physical properties were measured at 30oC.In order to sustain the temperature during thermal conductivity and surface tension measurement, a temperature controlled water bath was used. However, in case of viscosity measurement, liquid sample was kept for at least 5 minutes on a temperature controlled rheometer plate (plate temperature: 30oC) prior to all the experiments. Stability of nanofluid is one of the most crucial factors to be considered for industrial application. The stability of the nanofluid was evaluated by taking sedimentation photograph (Nikon D7100 camera, Japan) and zeta potential measurement of nanofluid samples at different time interval. Surface roughness was measured for both prior and post nanoparticle deposition by using Mitutoyo surface roughness tester (SJ-201 P/M, Japan). 3.1.

XRD analysis

XRD patterns of nanoparticle provide its unique characteristics feature, the degree of crystallinity, basal spacing, and crystal size. XRD analyses of Cu-Zn-Al LDH nanoparticles were matched with JCPDS file (37-0629). JCPDS file contains characteristics peaks corresponding to known Cu-Zn-Al LDH samples. The XRD patterns of Cu-Zn-Al LDH nanoparticle consists of 7

several distinctive peaks in the 2θ angle range of 8-70o (Fig. 2). From JCPDS file details, it was found that nanoparticle is rhombohedral in character and its lattice is rhombo-centred. LDH is a layered crystalline material which is made of metal hydroxide layers and anionic counter ions. Nanoparticle sample was analyzed to determine basal spacing (Braggs Law) and crystal size (Scherrer Law) of the nanoparticle[11, 18]. The basal spacing and crystal size data corresponding to each characteristics peak are reported in Table 1.

Fig. 2. XRD pattern of Cu-Zn-Al LDH nanoparticle with varying diffraction angle

8

Table 1.Basal spacing and crystal size chart of Cu-Zn-Al LDH nanoparticleat different diffracion angles. Nanoparticle

d

2θo

Basal spacing,

Crystal size,

JCPDS file

d (nm)

L (nm)

No 037-0629

(h k l) Cu-Zn-Al

(0 0 3)

11.72

0.75

37

LDH

(0 0 6)

23.64

0.38

18

(1 0 1)

33.81

0.26

24

(0 1 2)

34.71

0.26

43

(1 0 7)

44.83

0.20

95

(1 0 10)

53.08

0.17

99

(1 1 0)

60.48

0.15

126

(1 1 3)

61.57

0.15

11

(1 1 6)

65.71

0.14

105

3.2.

Morphology and elemental analysis

FESEM analysis was carried out on Cu-Zn-Al LDH nanoparticle which is layered crystalline material. High magnification image of Cu-Zn-Al LDH nanoparticle clearly shows its layered morphology. It also shows that metal hydroxide sheets (flakes) are stacked upon each other and its thickness is well below 100 nm. It confirms that at least one of the particle dimensions is in the nanometer range (See Fig. 3 (a)). This observation can be further varied in TEM analysis. The layered morphology of layered double hydroxide has also been observed by other scientists [19-21]. Nanoparticles were also tested for elemental analysis by using Energy dispersive

9

spectroscopy (EDS). EDS analysis established the existence Cu, Zn, Al, O, and N in the nanoparticle.

Fig. 3 (a-b). Morphology and elemental analyses of Cu-Zn-Al LDH nanoparticle 3.3.

Particle size analysis

TEM analysis was carried out to check the average particle size as well as the aspect ratio of CuZn-Al LDH nanoparticle. Fig. 4 shows that the particles possess a layered geometry (flake type structure) which has a high aspect ratio (See Fig. 4(b)).Cu-Zn-Al LDH nanoparticles are stacked upon each other which clearly match with its characteristic feature. According to several scientists [22-24], higher the aspect ratio of nanoparticles greater will be its thermal conductivity in a suspension. The average particle length was observed to be 49 nm whereas average width was 7 nm (average of 12 data points). Therefore, the aspect ratio was 7 which are significantly higher than that of any sphere shaped nanoparticles and making it more effective for heat extraction. Particles with high aspect ratio provide longer heat conduction path and create a mesh for faster transport of heat. The current findings are in line with our earlier finding with Cu-Al

10

LDH[11] and Zn-Al LDH[17] nanoparticle as well as with the work of other scientists worked on different LDH[25].

(a)

(b)

Fig. 4. Size analysis of Cu-Zn-Al LDH nanoparticle, a) TEM image and b) histogram plot

3.4.

Thermo-physical property analyses

Thermo-physical properties (thermal conductivity, surface tension, and viscosity) of nanofluid are critical while considering it for thermal application. Thermal conductivity is the most crucial factor for any nanofluid because higher the thermal conductivity of the coolant better will be its thermal performance. The surface tension of any coolant and contact angle it creates with the surface determines its spreadability over the same. A lower value of surface tension and contact angle is desired for greater contact area with the hot surface. Nanofluid viscosity is also a factor to be considered for its industrial application as higher viscosity will increase pressure drop (increase in pumping cost) and also influence its spreadability over the surface.

11

3.4.1. Thermal Conductivity The main driving force for creating nanofluid was to produce a coolant which will have superior thermal conductivity compared to any conventional coolant such as water, alcohol, transformer oil etc. In the present study, the focus is to find the effect of concentration variation on thermal conductivity of Cu-Zn-Al LDH nanofluid. Figure 5 shows that with growing particle concentration thermal conductivity value increases and beyond an optimum concentration it starts to decline. The maximum enhancement in thermal conductivity value was observed at160 ppm concentration of Cu-Zn-Al LDH nanoparticle which is 13.9% greater than that of water. The responsible mechanism behind both increase and decrease in thermal conductivity can be owed to combination of several critical factors such as particle concentration[2, 11], Brownian motion of suspended particle[26, 27], degree of agglomeration and clustering [23, 28, 29], dispersion stability[30-32], liquid layering effect[33], particle size[34, 35] and aspect ratio/shape [22, 36, 37]etc. It is to be noted that for spherical nanoparticles, the mechanism of Brownian motion can estimate the thermal conductivity more precision than in case of particles with high aspect ratio where both translational and rotational diffusion reduces the effect of Brownian motion. The complex behaviour of asymmetric nanoparticle in the base fluid makes thermal conductivity prediction harder using basic micro-convection model as it does not include shape factor and ordered layer thickness [38-40].However, the positive impact of high aspect ratio of nanoparticles on the thermal conductivity of nanofluid has been reaffirmed by several researcher [37, 41]. At high particle concentration, clustering tendency has a detrimental effect on thermal conductivity. According to Ozerinc et al.[42], there exists an optimal clustering level above which thermal conductivity value declines. Increase in thermal conductivity value with increasing particle loading is a common phenomenon with nanofluids. In this study also authors 12

have observed similar trend up to a concentration of 160 ppm. The improved thermal properties can be linked to Brownian motion, optimum clustering tendency, proper heat conduction path, high aspect ratio and small size (length 49 nm and width 7 nm) of the nanoparticle etc. However, it is also to be noted that at higher particle concentration due to increased Van der Waal attractive force (agglomeration tendency), poor stability and undesired shape modification, thermal conductivity value declines. A table has been added in this section to show the comparison between the thermal conductivity increments attained by conventional nanofluids and the newly developed Cu-Zn-Al LDH nanofluid (See Table 2).

Fig. 5.Effect of concentration on thermal conductivity variation of Cu-Zn-Al LDH nanofluid

13

Table 2.Comparative summary of thermal conductivity improvement achieved by different nanofluids Reference

Nanofluid

Maximum Augmentation in Thermal Conductivity

Lee et al. [43]

Water- Al2O3, Water- CuO

10 % and 12 %

Ravikumar et al. [44] Tiara et al. [45] Chakraborty et al. [46] Jeong et al. [41] Chakraborty et al. [47] Tiara et al.[48]

Water- Al2O3

4%

Water- Alumina

7.02 %

Water-TiO2

8.3%

Water- ZnO

18%

Water- Cu-Al LDH

16.1%

Water- Zn-Al LDH

10.5%

Water- Cu-Zn-Al LDH

13.9%

Present Work

3.4.2. Surface Tension and Contact Angle The surface tension of a coolant plays a vital role important in determining spreadability. Low surface tension value of any coolant indicates better spreadability, low contact angle, and higher contact area. Positive attributes of reduced surface tension on the heat transfer application have been accepted by numerous researchers [9, 49-51]. Addition of nanoparticle can also play a role in altering the surface tension value of nanofluid by changing the surface energy in the liquid-air boundary. The increase and decrease in surface tension value of nanofluid samples depend on 14

three basic factors such as variation in the nanoparticle, base fluid, and concentration. It is also observed that irrespective of nanoparticle and basefluid nature, at higher nanoparticle concentration surface tension value tends to increase [52]. As the nanoparticle concentration rises in the base fluid, large amount nanoparticles accumulates around the liquid surface. Due to nanoparticle aggregation on the liquid-air interface, the cohesive force between each nanoparticles increases which is responsible for increased surface tension value at higher concentration[53, 54]. In addition to that increase or decrease in surface tension value of nanofluid depends on electrostatic repulsion force and Van der Waal (VDW) attractive force between suspended particles. At low nanoparticle concentration (40 ppm), slight reduction in surface tension value is observed as repulsive force can dominate over the VDW attractive force due to the charges present on the nanoparticle surface. However, with further increase concentration, surface tension value rises up again due to over dominating VDW force. In the current study, authors have observed both of these trends with varying nanoparticle concentration (See Fig. 6). The current trend is in synchronous with the observation made by Tanvir and Qiao[54] for MWCNT/DI water nanofluid. However, it is to be noted that alteration in surface tension value for Cu-Zn-Al LDH nanofluid with varying concentration is insignificant (surface tension variation ±1-1.3mN/m) as compared to that achieved by surfactant added nanofluids[54, 55].

15

Fig. 6. Effect of concentration on surface tension variation of Cu-Zn-Al LDH nanofluid The importance of surface tension analysis is partly insignificant for this study because spreading of impinging drops not only depends on liquid surface tension but also on the surface roughness of steel. The surface roughness plays a crucial role in determining contact angle as well as the spreadability of drop on the surface. With increase in surface roughness contact angle of reduces for a fixed coolant. In order to validate our claim, contact angle was measured for different nanofluid concentration at two different surfaces which includes steel plate prior to deposition and steel plate post nanoparticle deposition. The result clearly shows that post particle deposition as the surface roughness increases; it leads to lower contact angle value for all the nanofluid concentration (See Fig. 7). The effect of nanoparticle deposition on reducing static contact angle and improved surface wettability has also been observed by Kim et al.[56]. However, for a fixed surface roughness increase in nanofluid concentration gives identical trend which is comparable with the trend obtained during surface tension analysis. 16

Fig. 7. Variation in static contact angle by varying nanofluid concentration and surface roughness of the steel plate 3.4.3. Viscosity Viscosity is one of the crucial parameters which impacts both flow properties as well as heat transfer efficiency of the nanofluid. Viscosity can influence the heat transfer performance of any system like thermal conductivity value. Here, in this study thermal conductivity of nanofluid changes with the addition of nanoparticle concentration. Addition of nanoparticle increases the viscosity of nanofluid which in turn increases the pressure drop and pumping cost. The implementation of nanoparticle instead of a micron sized particle in base fluid is expected to limit the viscosity rise significantly. High viscosity can also hinder the spreadability of coolant over the hot surface. Several scientists have observed that with the increase in nanoparticle concentration viscosity value also increases irrespective of nanoparticle nature such as metal [57], metal oxide [58-61]and carbon based nanoparticle. The finding obtained in this current study for Cu-Zn-Al LDH nanofluid also indicates towards the same conclusion. Figure 8 shows 17

increasing viscosity value with increasing particle concentration. When compared with the viscosity of water increase in viscosity at 240 ppm concentration is 68.7%. It is also to be noted that moderately high viscosity can be considered beneficial in some aspects as it increases the residence time of the impinging drop on a solid surface. Hence, it can increase the contact time between hot surface and coolant which indirectly influences the heat transfer rates [7].

Fig. 8. Effect of concentration on viscosity value of Cu-Zn-Al LDH nanofluid 3.5.

Stability

Stability is one of the main parameters to be considered for nanofluid in order to use it industrially. Stability analyses were conducted via sedimentation photography and zeta potential value (See Fig. 9 and Table 3). Zeta potential values for different nanofluid concentrations were reported at two different time interval (2 and 12 hours) to check the effect of time on nanofluid stability. Table 3 clearly shows that nanofluid stability decreases slightly with increasing time

18

which true for all the samples reported here. It is also to be noted that even after 12 hours from preparation the value remains above the desired zeta potential value of ± 30 mV. Using sedimentation photography technique, it can be said that up to initial 12 hours, there is no sign of sedimentation in all the samples. However, as the time progresses 120, 240 ppm solutions start to show sedimentation after 12 hours. On the other hand, 40 ppm solution remained stable up during the entire duration of the experiment. To give a clear idea on sedimentation, photographs were taken after 24 hours from the bottom side which clearly shows no sedimentation has taken place for 40 ppm solution whereas both 120 and 240 ppm solutions show traces of sedimentation below the container. However, it is to be noted that Cu-Zn-Al LDH nanofluid shows best stability within 2 hours from its preparation and it is preferred to be used for application within that time frame.

Fig. 9. Sedimentation photography of Cu-Zn-Al LDH nanofluid at various concentrations and time duration 19

Table 3. Zeta potential value of Cu-Zn-Al LDH nanofluid at different particle loading and time interval Nanofluid Concentration

Zeta potential value (mV)

Zeta potential value (mV)

(ppm)

(after 2 hrs )

(after 12 hrs )

40

36.9

34.6

120

37.3

35.4

160

38.6

36.6

240

37.7

35.3

4. Spray cooling experimental setup & surface temperature calculation: Detailed schematic diagram of spray cooling experimental setup is shown in Fig. 10. The experimental setup contains several key components such as Lechler full cone spray nozzle, pressure gauge, rotameter, centrifugal pump, coolant reservoir, solenoid valve, gate valve, muffle furnace, insulating resting pad, data acquisition system and computer. The key objective of the experiments is to check the effect nanofluid concentration on surface cooling rate. AISI 304 grade stainless steel plates were used for all experiments. The steel plate dimensions were 100 mm (length) ×100 mm (width) ×6 mm (thickness). An electrically powered muffle furnace (Voltage 440V, Load 8/12 kW) which has a maximum heating range up to 1400oC was used to heat up the steel plate. The test plates were heated up to 1050oC for spray cooling experiments. A Lechler (Nozzle No: 460-843-17-CG) manufactured full cone water spray nozzle was used for the cooling experiments. An insulating resting pad (made with fire brick) was fabricated to ensure adiabatic boundary condition where the hot steel plate was kept during the experiment. 20

The transient temperature data during the experiments were collected by using 3 K-type thermocouples which were connected to a National Instrument (USA) made data acquisition system (NIcDAQ-9174 and NI 9211 card). The data acquisition system was then connected to a computer for data storage. All the three thermocouples were placed at three specific locations to capture the temperature variation across the steel. TC 1(x=20 mm, y= 3 mm; Distance from spray/plate centerline = 30 mm) was placed farthest from spray/plate centre, TC 2 (x=50 mm, y= 3 mm; Distance from spray centerline = 0 mm) was placed right below the spray/place centre and TC 3 (x= 70 mm, y= 3 mm; Distance from spray centerline = 20 mm) was placed on the opposite side of TC1 and closer to the spray/plate centerline. Figure 10 also shows the position of the three thermocouples and their coordinates. The thermocouples holes are drilled up to 50 mm in the Z direction and the holes were sealed with a conducting paste to eliminate any air gap between thermocouples and plate. In order to ensure that water does not fall on hot steel plate until the spray is stabilized, a wooden board was used to prevent the spray impingement. The board was only removed after the spray is stabilized and desired flow rate was attained. All other details regarding the spray cooling experiments were given in Table 4. Using the three subsurface thermocouple data, authors have calculated surface temperature profiles by using a commercially purchased 2 D inverse heat conduction solver, INTEMP[6265]. For surface temperature distribution, calculations were done by transforming the entire geometry in to two dimensions (x= 100 mm, y= 6 mm). The entire geometry is divided into 7781 nodes and 7500 elements (Δx= 0.0004 m, Δy= 0.0002 m). The transient thermocouple data is taken as the input data. Only the top surface is considered of heat transfer as all other surface is covered by insulating fire bricks. The boundary conditions for aforesaid 2 D computational domain are as follows:

21

For x = 0 mm and y = 0 to 6 mm,

T 0 x

For x = 100 mm, and y= 0 to 6 mm,

T 0 x

For y = 0 mm, and x= 0 to 100 mm,

T 0 y

For y = 6 mm, and x= 0 to 100 mm,

T  unknown y

The principal equation for the computation of surface heat flux is given below:

  T  T  k   C p  t  y  y   2T  2T T k 2  k 2  C p x y t   T k x  x

  2T  2T  2  2 y  x

  C p T  k t 

Where, k (Unit: W/m.K), ρ (Unit: Kg/m3), and Cp (Unit: J/Kg.K) denotes the thermal conductivity, density, and specific heat capacity of steel plate, respectively. To calculate surface heat flux and surface temperature from internal thermocouple data, the software takes a guess value of surface heat flux and computes temperature data for all the nodes as typical heat conduction problem. Nonlinear optimization technique is used to re-modify the guess value of heat flux for the purpose of error minimization (difference between measured temperature value and INTEMP calculated temperature at the same node). The INTEMP calculation proceeds and iteration takes place until the error value goes below the predefined tolerance limit. Several researchers have used INTEMP for surface heat flux and temperature calculation [66, 67]. For the current study, three thermocouples were used for temperature

22

recording. Based on the position of three thermocouples in steel plate, authors have divided the top surface into three heat flux zones, a) Flux zone 1 (x= 0 to 36 mm, y =6 mm), b) Flux zone 2 (x= 36 to 64 mm, y =6 mm), and c) Flux zone 3 (x=64 to 100 mm, y=6 mm) having different heat flux value. It is assumed that heat flux value within each zone is uniform.

Fig. 10. Experimental setup for spray impingement cooling using Cu-Zn-Al LDH nanofluid

23

Table 4. Experimental design for Cu-Zn-Al LDH nanofluid based spray cooling experiments Parameter of Concern

Operating Condition

Steel Plate Temperature

1050 oC

Zone of Interest (Temperature)

900-600oC

Coolant Temperature

30oC

Coolant Flow Rate

16 lpm.

Coolant Pressure

4 bar

Spray Impingement Height

6 cm

Spray Angle

45o

Nanofluid

Water-Cu-Zn-Al LDH

Nanofluid Concentration

40, 80, 120, 160, 200 & 240 ppm

5. Results and Discussion: Implementation of Cu-Zn-Al LDH nanofluid for heat transfer enhancement during steel quenching process is the core of the current study. In this section, authors have focused on the effect of varying nanofluid concentration on cooling rate and effect of nanoparticle deposition behind the heat transfer mechanism. 5.1.

Cooling curves and cooling rate

The transient surface temperature corresponding to three thermocouple locations was calculated using INTEMP. Figure11(a-b) shows the variation of surface temperature with time during spray cooling within a temperature range of 10500C to 2000C for pure water and 160 ppm Cu-Zn-Al LDH nanofluid concentration. From the figure, it can be seen that both the curves follow an 24

identical trend with thermocouple TC2 showing the highest cooling rate.TC2 is located just beneath the nozzle and hence the temperature declines faster as compared to other two thermocouples. Based on its distance from the spray impingement zone, fastest temperature drop was observed in TC2 which is followed by TC3 and TC1.Another distinctive feature observed in all the graphs is the presence of two characteristic stages of temperature drop. Both the stages are owed to different modes of heat transfer such as natural convection (first stage), forced convection (second stage), and radiation (first stage). Temperature drop in the first stage is much slower than the second stage as it only involves heat loss due to radiation and natural convection. In Fig. 11, t= 0 sec is measured when the plate is removed from the furnace. The duration of the first stage extends from the time when the plate is detached from the furnace and placed on the fire brick till the time spray starts to fall on the hot steel plate. For the purpose of ensuring stable and uniform spray impingement on a steel plate, a wooden board was used to prevent any spray impingement until desired water flow rate; water pressure and uniform spray distribution are attained. Once the wooden board is removed and spray impinges on the steel surface the temperature profile starts to show rapid decline which is the onset point of the second stage. From the slope of the transient temperature profile, both the stages can be easily identified.

25

(a) Water

(b) 160 ppm

Fig. 11 (a-b). Transient surface temperature profile for all three thermocouple locations,(a) water, and (b) 160 ppm concentration of Cu-Zn-Al LDH nanofluid Temperature drop in TC2 thermocouple is the fastest among all three thermocouples. Therefore, from here onwards only data corresponding to TC2 thermocouple has been reported in the manuscript. For the current study, cooling rate value attained (between the temperature zone of 900-600oC) for all the nanofluid concentration has been displayed in Fig. 12. It was observed that on increasing LDH concentration up to 160 ppm, cooling rate increases and thereafter it decreases. At 160 ppm, the maximum cooling rate of 158oC/s was achieved which lies in the ultra-fast cooling region indicating that UFC can be achieved with Cu-Zn-Al LDH nanofluid assisted spray cooling. An increase of 18.5% in cooling rate was found out for a concentration of 160 ppm as compared to water. Authors have achieved 15.6% reduction in coolant consumption at 160 ppm concentration when compared with pure water (Supplementary Table 1). During the spray cooling of nanofluid, nanoparticles get deposited on the steel surface which creates additional nucleation sites and helps to rupture the insulating vapour layer formed on the steel surface. As observed in contact angle analysis, nanoparticle deposition also helps in improving

26

surface wettability and effective heat transfer rate. However, too high nanofluid concentration can also adversely affect the cooling rates because the entire steel surface gets covered with LDH nanoparticle layer which acts as a hindrance for heat transfer between the coolant and the steel surface. The current trend in cooling rate plot is owed to both surface roughness of steel (owed to nanoparticle deposition) and thermal conductivity variation due to nanofluid concentration change. The influence of particle deposition on heat transfer enhancement and the subsequent decline has been clearly explained in section 5.4. To compare the cooling performance of the current nanofluid with earlier reported nanofluids (at similar experimental condition), a comparative table has been formulated (See Table 5). Table 5. Comparison between cooling rate enhancement obtained by different nanofluid at similar experimental condition Reference

Cooling Technique

Nanofluid

% Increase in Cooling Rate than Base Fluid

Ravikumar et al. [9]

Air-atomized spray

Water-Cu Nanofluid

21.6%

Ravikumar et al. [44]

Air-atomized spray

Water-Al2 O3 Nanofluid

Tiara et al.[68]

Forced Jet

Water-Al2 O3 nanofluid

16.1%

Ishita et al.[16]

Forced Jet

Water-Cu-Al LDH nanofluid

41%

Tiara et al.[17]

Forced Jet

Water-Zn-Al LDH nanofluid

29%

Present Study

Spray

Water- Cu-Zn-Al LDH nanofluid

18.5%

(without surfactant) 10.2%

(without surfactant)

27

Fig. 12.Cooling rate alteration at different concentration of Cu-Zn-Al LDH nanofluid 5.2.

Boiling curve

Surface heat flux variation with surface temperature (900 0–2000C) during cooling at various CuZn-Al LDH nanofluid concentrations has been shown in Fig. 13. A nonlinear variation of surface heat flux with surface temperature was observed irrespective of the LDH concentration. Initially, an insulating vapour layer forms due to the high temperature difference between coolant and steel surface resulting in a low heat flux. The formation of vapour cushion due large temperature gradient is called as the Leidenfrost effect [69]. As the temperature decreases during cooling, the heat flux increases and attains a peak value termed as critical heat flux (CHF) due to the rupture of insulating vapour layer and this region is termed as transition boiling regime.On further cooling, nucleate boiling dominates where the surface heat flux value decreases after CHF due to the reduction in thermal energy. The highest enhancement in critical heat flux was achieved for a nanofluid loading of 160 ppm.

28

It was also observed that the average heat flux (taking the average of heat flux values between 900-600oC) value increases with LDH concentration up to 160 ppm, thereafter it decreases as shown in Table 6. Reduction in thermal conductivity of nanofluid and formation of a thick layer of particles on steel surface is responsible for the lowering of heat transfer at high nanofluid concentrations.

Fig. 13.Variation in surface heat flux with surface temperature at different concentration of CuZn-Al LDH nanofluid 5.3.

Heat transfer coefficient

Heat transfer coefficient, h (W/m2.K) of a coolant is found out by using the following equation.

h

Q Ts  Tc

29

(1)

Where, Q is the surface heat flux in W/m2, Ts is the surface temperature in K and T c is the coolant temperature in K. Heat transfer coefficients for different nanofluid concentrations were calculated and plotted against the surface temperature (9000-2000C) as shown in Fig. 14. It was found out that irrespective of nanofluid concentration heat transfer coefficient values were almost same at initial stages of cooling where the surface temperature was higher. However, heat transfer coefficient value increases as cooling proceeds in all cases. This occurs due to the rupture of insulting vapour layer during cooling. As cooling proceeds, nanoparticle deposition increases leading to newer nucleation sites and thus enhances heat transfer. Heat transfer coefficient value rises with nanofluid concentration up to 160 ppm, thereafter it decreases. Table 6 also shows that the highest average heat transfer coefficient (AHTC) value of 2.34 kW/m2K was obtained for a nanofluid concentration of 160 ppm and in the surface temperature of the range of 900-6000C. A maximum of 4.47% enhancement was observed at 160 ppm concentration as compared to that achieved by pure water spray.

Fig. 14. Alteration in heat transfer coefficient value with surface temperature at varying Cu-Zn-Al LDH nanofluid concentration 30

Table 6. Summary of average heat flux and heat transfer coefficient values obtained at different nanofluid concentration Nanofluid Concentration

AHF (MW/m2)

AHTC (kW/m2 K)

(ppm)

5.4.

0

1.52

40

1.55

80

1.57

120

1.58

160

1.65

200

1.61

240

1.60

2.24 2.25 2.26 2.28 2.34 2.33 2.32

Effect of nanoparticle deposition on heat transfer mechanism

Presence of nanoparticle in the base fluid leads to increment in heat transfer rate by two ways one is by elevating the thermal conductivity value of the coolant and secondly by increasing the number of nucleation site via nanoparticle deposition. Effect of nanoparticle dispersion on thermal conductivity value has already been discussed in thermal conductivity analysis section. Therefore, in this section authors have mainly focused on the other aspect of heat transfer enhancement which is nanoparticle deposition. During the steel quenching process, nanoparticle suspended in water gets deposited on the steel surface which increases the surface roughness. Enhanced surface roughness acts as an advantage in terms of the heat transfer aspects [16, 70]. The deposited particles act as additional nucleation sites. Increase in nucleation site by particle

31

deposition is considered to be one of the reasons behind improved cooling rate. The effect of nanoparticle concentration on surface roughness has been displayed in Fig. 15. The figure shows that with increasing particle concentration, surface roughness gradually increases up to 160 ppm concentration, and then it starts to decline as the entire surface gets covered with the nanoparticle layer. In order to explain the phenomenon, a schematic diagram (See Fig. 16) of nanoparticle deposition with varying nanoparticle concentration has been added along with the actual FESEM image to further validate the claim. FESEM image clearly shows that at concentration beyond 160 ppm, the steel surface gets covered by a layer of deposited nanoparticles which is responsible for the reduced heat transfer rate. Nanoparticle layers hinder the contact between impinging drops and the hot steel surface which in turn, reduces the cooling rates. Such observation has also been made by few other researchers who have found similar attributes of nanoparticle deposition on heat transfer performance [71-74]. Similar to current observation, Chang et al.[74] also reported that at higher nanoparticle (Al2O3) loading, excess nanoparticle deposition causes reduction in nucleation site and decline in convective heat transfer rate. However, at lower concentration optimum particle deposition helps to improve both nucleation site and heat transfer rate during spray cooling. The aforesaid observation is in sync with results obtained in the present study.

32

Fig. 15.Influence of nanofluid concentration on deposition induced surface roughness

Fig. 16.Schematic diagram of nanoparticle deposition on steel plate

33

6. Measurement uncertainty: The error analysis or uncertainty measurement is one of the key studies for any experimental investigation. To ensure measurement accuracy and to acknowledge the system error, it is important to go for uncertainty analysis. In this study, authors have used ASME recommended test code for error analysis [75]. For ensuring measurement accuracy, all experimental data reported in this study has been repeated multiple times to guarantee accuracy. All the parameters from which uncertainties may arise have been reported in Table 7 along with their contribution. Table 7.Measurement uncertainty for different parameters Source of Error

Error Type

Maximum Error

Water Flow Rate

Bias

±3%

Spray height

Bias

± 0.1 cm

Temperature measurement

Bias

± 4oC

Nanofluid Concentration

Bias

± 3 ppm

Thermal Conductivity

Precision

± 4.00 %

Surface Tension

Precision

± 0.69 %

Viscosity

Precision

± 6.55 %

Surface Roughness

Precision

± 4.98 %

Cooling Rate

Precision

± 8.64 %

Average Heat Flux

Precision

± 8.18 %

34

7. Conclusion: A new breed of nanofluid namely Cu-Zn-Al LDH has been synthesized by one step coprecipitation technique. The current work focuses on the thermo-physical aspects of the aforementioned nanofluid and its use in the spray cooling of hot steel plate (above 900oC). Implementation of nanofluids aids in heat transfer enhancement during steel quenching via two routes, firstly by enhancing the thermal conductivity of coolant and secondly by increasing the number of nucleation site with nanoparticle deposition. The nanofluid concentration is varied in the range of 40-240 ppm to check its impact on the thermo-physical property as well as its thermal performance. The following summarized points are the key outcomes of the present research, 1) Cu-Zn-Al LDH nanoparticles were rod shaped. The average Cu-Zn-Al LDH nanoparticle size was found to be 49 nm which was measured by using TEM analysis. 2) The thermal conductivity of Cu-Zn-Al LDH nanofluid at 160 ppm was 13.9% higher than that of water. Thermal conductivity increases with increasing particle loading upto 160 ppm concentration then it starts to decline again. Surface tension remains almost unchanged with changing nanoparticle concentration. However, the viscosity value increased with increasing particle concentration. Highest enhancement in viscosity was attained at 240 ppm which is 68.7% higher than water. 3) The highest enhancement in surface cooling rate was reached at 160 ppm nanofluid concentration which is 18.5% greater than what attained by pure water. The maximum cooling rate of 158.43oC/sec was obtained at 160 ppm which is well above ultra-fast cooling range (>133.3oC/sec for 6 mm plate).

35

4) Other than the thermal conductivity value, nanoparticle deposition on steel plate also plays a crucial role in heat transfer enhancement. With increasing particle concentration, surface roughness value increases which in turn attributes in improving a number of nucleation site. However, as the particle concentration is further increased steel surface becomes entirely covered with particles and it prevents incoming drop contact with the hot surface. As a result, the overall heat transfer performance declines beyond 160 ppm concentration (See Fig. 12).

Reference: [1] S.U.S. Choi, Enhancing thermal conductivity of fluids with nanoparticles, in: American Society of Mechanical Engineers, Fluids Engineering Division (Publication) FED, Vol. 231, 1995, pp. 99-105. [2] S.K. Das, S.U.S. Choi, H.E. Patel, Heat Transfer in Nanofluids—A Review, Heat Transfer Engineering, 27 (2006) 3-19. [3] Y. Li, J.e. Zhou, S. Tung, E. Schneider, S. Xi, A review on development of nanofluid preparation and characterization, Powder Technology, 196 (2009) 89-101. [4] S.D. Cox, S.J. Hardy, D.J. Parker, Influence of runout table operation setup on hot strip quality, subject to initial strip condition: heat transfer issues, Ironmaking & Steelmaking, 28 (2001) 363-372. [5] S.V. Ravikumar, J.M. Jha, I. Sarkar, S.K. Pal, S. Chakraborty, Mixed-surfactant additives for enhancement of air-atomized spray cooling of a hot steel plate, Experimental Thermal and Fluid Science, 55 (2014) 210-220. [6] D.-h. Zhang, B.-x. Wang, N. Zhou, M. Yu, J. Wang, Cooling Efficiency of Laminar Cooling System for Plate Mill, Journal of Iron and Steel Research, International, 15 (2008) 24-28. 36

[7] S. Chakraborty, A. Chakraborty, S. Das, T. Mukherjee, D. Bhattacharjee, R.K. Ray, Application of Water Based-TiO2 Nano-fluid for Cooling of Hot Steel Plate, ISIJ International, 50 (2010) 124-127. [8] S. Mitra, S.K. Saha, S. Chakraborty, S. Das, Study on boiling heat transfer of water–TiO2 and water–MWCNT nanofluids based laminar jet impingement on heated steel surface, Applied Thermal Engineering, 37 (2012) 353-359. [9] S.V. Ravikumar, J.M. Jha, K. Haldar, S.K. Pal, S. Chakraborty, Surfactant-Based Cu–Water Nanofluid Spray for Heat Transfer Enhancement of High Temperature Steel Surface, Journal of Heat Transfer, 137 (2015) 051504. [10] J.M. Jha, S.V. Ravikumar, A.M. Tiara, I. Sarkar, S.K. Pal, S. Chakraborty, Ultrafast cooling of a hot moving steel plate by using alumina nanofluid based air atomized spray impingement, Applied Thermal Engineering, 75 (2015) 738-747. [11] S. Chakraborty, I. Sarkar, K. Haldar, S.K. Pal, S. Chakraborty, Synthesis of Cu–Al layered double hydroxide nanofluid and characterization of its thermal properties, Applied Clay Science, 107 (2015) 98-108. [12] Q. Wang, D. O’Hare, Recent Advances in the Synthesis and Application of Layered Double Hydroxide (LDH) Nanosheets, Chemical Reviews, 112 (2012) 4124-4155. [13] V.R.R. Cunha, R.B. de Souza, A.M.C.R.P. da Fonseca Martins, I.H.J. Koh, V.R.L. Constantino, Accessing the biocompatibility of layered double hydroxide by intramuscular implantation: histological and microcirculation evaluation, Scientific Reports, 6 (2016) 30547. [14] F. Li, X. Duan, Applications of Layered Double Hydroxides, in: X. Duan, D.G. Evans (eds.) Layered Double Hydroxides, Springer Berlin Heidelberg, Berlin, Heidelberg, 2006, pp. 193-223.

37

[15] B. Li, J. He, D. G. Evans, X. Duan, Inorganic layered double hydroxides as a drug delivery system—intercalation and in vitro release of fenbufen, Applied Clay Science, 27 (2004) 199207. [16] I. Sarkar, S. Chakraborty, J.M. Jha, S.K. Pal, S. Chakraborty, Ultrafast cooling of a hot steel plate using Cu-Al layered double hydroxide nanofluid jet, International Journal of Thermal Sciences, 116 (2017) 52-62. [17] A.M. Tiara, S. Chakraborty, I. Sarkar, S.K. Pal, S. Chakraborty, Synthesis and characterization of Zn-Al layered double hydroxide nanofluid and its application as a coolant in metal quenching, Applied Clay Science, 143 (2017) 241-249. [18] M.A. Short, P.L. Walker, Measurement of interlayer spacings and crystal sizes in turbostratic carbons, Carbon, 1 (1963) 3-9. [19] N. Yamaguchi, T. Nakamura, K. Tadanaga, A. Matsuda, T. Minami, M. Tatsumisago, Direct Formation of Zn−Al Layered Double Hydroxide Films with High Transparency on Glass Substrate by the Sol−Gel Process with Hot Water Treatment, Crystal Growth & Design, 6 (2006) 1726-1729. [20] S.A. Khan, S.B. Khan, A.M. Asiri, Layered double hydroxide of Cd-Al/C for the Mineralization and De-coloration of Dyes in Solar and Visible Light Exposure, Scientific Resports, 6 (2016) 35107. [21] T.D. Nguyen, Q.T.P. Bui, H.Q.H. Phan, C.X. Thang, L.T.B. Tran, L.X. Tien, L.G. Bach, Synthesis and Characterization of Layered Double Hydroxides with divalent ions (Mg 2+, Cu2+, Ca2+, Ni2+, Co2+, and Zn2+), Journal of Materials Science & Surface Engineering. 4 (2016) 488491.

38

[22] M.M. Ghosh, S. Ghosh, S.K. Pabi, Effects of Particle Shape and Fluid Temperature on Heat-Transfer Characteristics of Nanofluids, Journal of Materials Engineering and Performance, 22 (2013) 1525-1529. [23] J. Philip, P.D. Shima, Thermal properties of nanofluids, Advances in Colloid and Interface Science, 183–184 (2012) 30-45. [24] J. Buongiorno, D.C. Venerus, N. Prabhat, T. McKrell, J. Townsend, R. Christianson, Y.V. Tolmachev, P. Keblinski, L.-w. Hu, J.L. Alvarado, I.C. Bang, S.W. Bishnoi, M. Bonetti, F. Botz, A. Cecere, Y. Chang, G. Chen, H. Chen, S.J. Chung, M.K. Chyu, S.K. Das, R.D. Paola, Y. Ding, F. Dubois, G. Dzido, J. Eapen, W. Escher, D. Funfschilling, Q. Galand, J. Gao, P.E. Gharagozloo, K.E. Goodson, J.G. Gutierrez, H. Hong, M. Horton, K.S. Hwang, C.S. Iorio, S.P. Jang, A.B. Jarzebski, Y. Jiang, L. Jin, S. Kabelac, A. Kamath, M.A. Kedzierski, L.G. Kieng, C. Kim, J.-H. Kim, S. Kim, S.H. Lee, K.C. Leong, I. Manna, B. Michel, R. Ni, H.E. Patel, J. Philip, D. Poulikakos, C. Reynaud, R. Savino, P.K. Singh, P. Song, T. Sundararajan, E. Timofeeva, T. Tritcak, A.N. Turanov, S.V. Vaerenbergh, D. Wen, S. Witharana, C. Yang, W.-H. Yeh, X.-Z. Zhao, S.-Q. Zhou, A benchmark study on the thermal conductivity of nanofluids, Journal of Applied Physics, 106 (2009) 094312. [25] G. Hu, N. Wang, D. O'Hare, J. Davis, Synthesis of magnesium aluminium layered double hydroxides in reverse microemulsions, Journal of Materials Chemistry, 17 (2007) 2257-2266. [26] J. Koo, C. Kleinstreuer, Impact analysis of nanoparticle motion mechanisms on the thermal conductivity of nanofluids, International Communications in Heat and Mass Transfer, 32 (2005) 1111-1118.

39

[27] P.D. Shima, J. Philip, B. Raj, Role of microconvection induced by Brownian motion of nanoparticles in the enhanced thermal conductivity of stable nanofluids, Applied Physics Letters, 94 (2009) 223101. [28] W. Evans, R. Prasher, J. Fish, P. Meakin, P. Phelan, P. Keblinski, Effect of aggregation and interfacial thermal resistance on thermal conductivity of nanocomposites and colloidal nanofluids, International Journal of Heat and Mass Transfer, 51 (2008) 1431-1438. [29] R. Prasher, P.E. Phelan, P. Bhattacharya, Effect of Aggregation Kinetics on the Thermal Conductivity of Nanoscale Colloidal Solutions (Nanofluid), Nano Letters, 6 (2006) 1529-1534. [30] Y. Xuan, Q. Li, Heat transfer enhancement of nanofluids, International Journal of Heat and Fluid Flow, 21 (2000) 58-64. [31] F. Yongjin, Y. Boming, X. Peng, Z. Mingqing, The effective thermal conductivity of nanofluids based on the nanolayer and the aggregation of nanoparticles, Journal of Physics D: Applied Physics, 40 (2007) 3164. [32] P.D. Shima, J. Philip, B. Raj, Influence of aggregation on thermal conductivity in stable and unstable nanofluids, Applied Physics Letters, 97 (2010) 153113. [33] W. Yu, S.U.S. Choi, The Role of Interfacial Layers in the Enhanced Thermal Conductivity of Nanofluids: A Renovated Maxwell Model, Journal of Nanoparticle Research, 5 (2003) 167171. [34] H.E. Patel, T. Sundararajan, S.K. Das, An experimental investigation into the thermal conductivity enhancement in oxide and metallic nanofluids, Journal of Nanoparticle Research, 12 (2010) 1015-1031.

40

[35] T.-P. Teng, Y.-H. Hung, T.-C. Teng, H.-E. Mo, H.-G. Hsu, The effect of alumina/water nanofluid particle size on thermal conductivity, Applied Thermal Engineering, 30 (2010) 22132218. [36] X.F. Zhou, L. Gao, Effective thermal conductivity in nanofluids of nonspherical particles with interfacial thermal resistance: Differential effective medium theory, Journal of Applied Physics, 100 (2006) 024913. [37] E.V. Timofeeva, J.L. Routbort, D. Singh, Particle shape effects on thermophysical properties of alumina nanofluids, Journal of Applied Physics, 106 (2009) 014304. [38] M.P. Beck, T. Sun, A.S. Teja, The thermal conductivity of alumina nanoparticles dispersed in ethylene glycol, Fluid Phase Equilibria, 260 (2007) 275-278. [39] J. Eapen, W.C. Williams, J. Buongiorno, L.-w. Hu, S. Yip, R. Rusconi, R. Piazza, MeanField Versus Microconvection Effects in Nanofluid Thermal Conduction, Physical Review Letters, 99 (2007) 095901. [40] E.V. Timofeeva, A.N. Gavrilov, J.M. McCloskey, Y.V. Tolmachev, S. Sprunt, L.M. Lopatina, J.V. Selinger, Thermal conductivity and particle agglomeration in alumina nanofluids: Experiment and theory, Physical Review E, 76 (2007) 061203. [41] J. Jeong, C. Li, Y. Kwon, J. Lee, S.H. Kim, R. Yun, Particle shape effect on the viscosity and thermal conductivity of ZnO nanofluids, International Journal of Refrigeration, 36 (2013) 2233-2241. [42] S. Özerinç, S. Kakaç, A.G. Yazıcıoğlu, Enhanced thermal conductivity of nanofluids: a state-of-the-art review, Microfluidics and Nanofluidics, 8 (2009) 145-170. [43] S. Lee, S.U.S. Choi, S. Li, J.A. Eastman, Measuring Thermal Conductivity of Fluids Containing Oxide Nanoparticles, Journal of Heat Transfer, 121 (1999) 280-289.

41

[44] S.V. Ravikumar, K. Haldar, J.M. Jha, S. Chakraborty, I. Sarkar, S.K. Pal, S. Chakraborty, Heat transfer enhancement using air-atomized spray cooling with water–Al2O3 nanofluid, International Journal of Thermal Sciences, 96 (2015) 85-93. [45] A.M. Tiara, S. Chakraborty, I. Sarkar, S.K. Pal, S. Chakraborty, Effect of alumina nanofluid jet on the enhancement of heat transfer from a steel plate, Heat and Mass Transfer, 53 (2017) 2187-2197. [46] S. Chakraborty, I. Sarkar, D.K. Behera, S.K. Pal, S. Chakraborty, Experimental investigation on the effect of dispersant addition on thermal and rheological characteristics of TiO2 nanofluid, Powder Technology, 307 (2017) 10-24. [47] S. Chakraborty, I. Sarkar, K. Haldar, S.K. Pal, S. Chakraborty, Synthesis of Cu–Al layered double hydroxide nanofluid and characterization of its thermal properties, Applied Clay Science, 107 (2015) 98-108. [48] A.M. Tiara, S. Chakraborty, I. Sarkar, S.K. Pal, S. Chakraborty, Synthesis and characterization of Zn-Al layered double hydroxide nanofluid and its application as a coolant in metal quenching, Applied Clay Science, 143 (2017) 241-249. [49] G. Hetsroni, J.L. Zakin, Z. Lin, A. Mosyak, E.A. Pancallo, R. Rozenblit, The effect of surfactants on bubble growth, wall thermal patterns and heat transfer in pool boiling, International Journal of Heat and Mass Transfer, 44 (2001) 485-497. [50] L. Cheng, D. Mewes, A. Luke, Boiling phenomena with surfactants and polymeric additives: A state-of-the-art review, International Journal of Heat and Mass Transfer, 50 (2007) 2744-2771.

42

[51] S.V. Ravikumar, J.M. Jha, S.S. Mohapatra, S.K. Pal, S. Chakraborty, Experimental Investigation of Effect of Different Types of Surfactants and Jet Height on Cooling of a Hot Steel Plate, Journal of Heat Transfer, 136 (2014) 072102. [52] M.H.U. Bhuiyan, R. Saidur, R.M. Mostafizur, I.M. Mahbubul, M.A. Amalina, Experimental investigation on surface tension of metal oxide–water nanofluids, International Communications in Heat and Mass Transfer, 65 (2015) 82-88. [53] M.H.U. Bhuiyan, R. Saidur, M.A. Amalina, R.M. Mostafizur, A. Islam, Effect of Nanoparticles Concentration and Their Sizes on Surface Tension of Nanofluids, Procedia Engineering, 105 (2015) 431-437. [54] S. Tanvir, L. Qiao, Surface tension of Nanofluid-type fuels containing suspended nanomaterials, Nanoscale Research Letters, 7 (2012) 226. [55] A.R. Harikrishnan, P. Dhar, P.K. Agnihotri, S. Gedupudi, S.K. Das, Effects of interplay of nanoparticles, surfactants and base fluid on the surface tension of nanocolloids, The European Physical Journal E, 40 (2017) 53. [56] S.J. Kim, I.C. Bang, J. Buongiorno, L.W. Hu, Effects of nanoparticle deposition on surface wettability influencing boiling heat transfer in nanofluids, Applied Physics Letters, 89 (2006) 153107. [57] X. Li, D. Zhu, X. Wang, Experimental investigation on viscosity of Cu-H2O nanofluids, Journal of Wuhan University of Technology-Mater. Sci. Ed., 24 (2009) 48-52. [58] R. Prasher, D. Song, J. Wang, P. Phelan, Measurements of nanofluid viscosity and its implications for thermal applications, Applied Physics Letters, 89 (2006) 133108. [59] J. Li, Z. Li, B. Wang, Experimental viscosity measurements for copper oxide nanoparticle suspensions, Tsinghua Science and Technology, 7 (2002) 198-201.

43

[60] B.C. Pak, Y.I. Cho, Hydrodynamic and heat transfer study of dispersed fluids with submicron metallic oxide particles, Experimental Heat Transfer, 11 (1998) 151-170. [61] S.K. Das, N. Putra, W. Roetzel, Pool boiling characteristics of nano-fluids, International Journal of Heat and Mass Transfer, 46 (2003) 851-862. [62] H.R. Busby, D.M. Trujillo, Numerical solution to a two-dimensional inverse heat conduction problem, International Journal for Numerical Methods in Engineering, 21 (1985) 349-359. [63] I. Sarkar, D.K. Behera, J.M. Jha, S.K. Pal, S. Chakraborty, Effect of polymer additive on the cooling rate of a hot steel plate by using water jet, Experimental Thermal and Fluid Science, 70 (2016) 105-114. [64] S.V. Ravikumar, J.M. Jha, I. Sarkar, S.S. Mohapatra, S.K. Pal, S. Chakraborty, Achievement of ultrafast cooling rate in a hot steel plate by air-atomized spray with different surfactant additives, Experimental Thermal and Fluid Science, 50 (2013) 79-89. [65] S.V. Ravikumar, J.M. Jha, I. Sarkar, S.K. Pal, S. Chakraborty, Enhancement of heat transfer rate in air-atomized spray cooling of a hot steel plate by using an aqueous solution of non-ionic surfactant and ethanol, Applied Thermal Engineering, 64 (2014) 64-75. [66] S.S. Mohapatra, S. Chakraborty, S.K. Pal, Experimental Studies on Different Cooling Processes to Achieve Ultra-Fast Cooling Rate for Hot Steel Plate, Experimental Heat Transfer, 25 (2012) 111-126. [67] J.M. Jha, S.V. Ravikumar, I. Sarkar, S.K. Pal, S. Chakraborty, Ultrafast cooling processes with surfactant additive for hot moving steel plate, Experimental Thermal and Fluid Science, 68 (2015) 135-144.

44

[68] A.M. Tiara, S. Chakraborty, I. Sarkar, S.K. Pal, S. Chakraborty, Effect of alumina nanofluid jet on the enhancement of heat transfer from a steel plate, Heat and Mass Transfer, 53 (2016) 2187-2197. [69] J.G. Leidenfrost, On the fixation of water in diverse fire, International Journal of Heat and Mass Transfer, 9 (1966) 1153-1166. [70] Y.C. Kim, Effect of surface roughness on pool boiling heat transfer in subcooled water-CuO nanofluid, Journal of Mechanical Science and Technology, 28 (2014) 3371-3376. [71] A.M. Tiara, S. Chakraborty, I. Sarkar, S.K. Pal, S. Chakraborty, Effect of alumina nanofluid jet on the enhancement of heat transfer from a steel plate, Heat and Mass Transfer, (2016) 1-11. [72] Z.-H. Liu, Y.-H. Qiu, Boiling heat transfer characteristics of nanofluids jet impingement on a plate surface, Heat and Mass Transfer, 43 (2007) 699-706. [73] S.J. Kim, I.C. Bang, J. Buongiorno, L.W. Hu, Surface wettability change during pool boiling of nanofluids and its effect on critical heat flux, International Journal of Heat and Mass Transfer, 50 (2007) 4105-4116. [74] T.-B. Chang, S.-C. Syu, Y.-K. Yang, Effects of particle volume fraction on spray heat transfer performance of Al2O3–water nanofluid, International Journal of Heat and Mass Transfer, 55 (2012) 1014-1021. [75] R.B. Abernethy, R.P. Benedict, R.B. Dowdell, ASME Measurement Uncertainty, Journal of Fluids Engineering, 107 (1985) 161-164.

45

List of Figures: Fig. 1

Graphical representation of Cu-Zn-Al LDH nanofluid synthesis method

Fig. 2

XRD pattern of Cu-Zn-Al LDH nanoparticle with varying diffraction angle

Fig. 3

Morphology analysis of Cu-Zn-Al LDH nanoparticle

Fig. 4

Size analysis of Cu-Zn-Al LDH nanoparticle, a) TEM image and b) histogram plot

Fig. 5

Effect of concentration on thermal conductivity variation of Cu-Zn-Al LDH nanofluid

Fig. 6

Effect of concentration on surface tension variation of Cu-Zn-Al LDH nanofluid

Fig. 7

Variation in static contact angle by varying nanofluid concentration and surface roughness of the steel plate

Fig. 8

Effect of concentration on viscosity value of Cu-Zn-Al LDH nanofluid

Fig. 9

Sedimentation photography of Cu-Zn-Al LDH nanofluid at various concentrations and time duration

Fig. 10

Experimental setup for spray impingement cooling using Cu-Zn-Al LDH nanofluid

Fig. 11 (a-b)

Transient surface temperature profile for all three thermocouple locations,(a) water, and (b) 160 ppm concentration of Cu-Zn-Al LDH nanofluid

Fig. 12

Cooling rate alteration at different concentration of Cu-Zn-Al LDH nanofluid

Fig. 13

Variation in surface heat flux with surface temperature at different concentration of Cu-Zn-Al LDH nanofluid

Fig. 14

Alteration in heat transfer coefficient value with surface temperature at varying 46

Cu-Zn-Al LDH nanofluid concentration Fig. 15

Influence of nanofluid concentration on deposition induced surface roughness

Fig. 16

Schematic diagram of nanoparticle deposition on steel plate

List of Tables: Table 1

Basal spacing and crystal size chart of Cu-Zn-Al LDH nanoparticle at different diffracion angles

Table 2

Comparative summary of thermal conductivity improvement achieved by different nanofluids

Table 3

Zeta potential value of Cu-Zn-Al LDH nanofluid at different particle loading and time interval

Table 4

Experimental design for Cu-Zn-Al LDH nanofluid based spray cooling experiments

Table 5

Comparison between cooling rate enhancement obtained by different nanofluid at similar experimental condition

Table 6

Summary of average heat flux and heat transfer coefficient values obtained at different nanofluid concentration

Table 7

Measurement uncertainty for different parameters

Supplementary Table: Supplementary Table 1

Variation in coolant consumption at different nanofluid concentration

Nomenclature: Cp

Specific heat capacity of steel plate

d

Basal spacing

47

h

Heat transfer coefficient

k

Thermal conductivity of steel plate

L

Crystal size

Q

Heat flux

Ts

Surface Temperature

Tc

Coolant Temperature

Greek Letter: ρ

Density of the steel plate

θ

X-Ray diffraction angle

λ

X-Ray wavelength

Abbreviation: AHF

Average Heat Flux

AHTC

Average Heat Transfer Coefficient

ASME

American Society of Mechanical Engineers

CHF

Critical Heat Flux

EDS

Energy Dispersive Spectroscopy

FESEM

Field Emission Scanning Electron Microscope

JCPDS

Joint Committee on Powder Diffraction Standards

LDH

Layered Double Hydroxide 48

TC

Thermocouple

TEM

Transmission Electron Microscope

UFC

Ultrafast Cooling

VDW

Van der Waal

XRD

X-Ray Diffraction

49

Graphical abstract

50

Highlights

 Cu-Zn-Al LDH nanofluid was prepared and used for metal quenching.  Nanoparticles are rod shaped having an average particle size of 49 nm.  13.9% enhancement in thermal conductivity was achieved at 160 ppm loading.  Nanofluid was used for spray cooling of hot steel plate (above 900oC).  Maximum cooling rate of 158.4oC/sec was also achieved at 160 ppm concentration.

51