Tuning of Thermal Conductivity and Rheology of Nanofluids Using an

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Tuning of Thermal Conductivity and Rheology of Nanofluids Using an External Stimulus P. D. Shima and John Philip* SMARTS, NDED, Metallurgy and Materials Group Indira Gandhi Centre for Atomic Research, Kalpakkam 603 102, Tamilnadu, India ABSTRACT: We discuss a new methodology to tune the thermal properties of magnetic nanofluids from low to very high values by varying the magnetic field strength and its orientation. This is achieved by varying the mode of conduction of heat, through nanoparticles and base fluid, from a series to parallel mode. Because the parallel mode has a geometric configuration that allows the most efficient means of heat propagation through nanoparticle paths, very large thermal conductivity enhancement is achieved with parallel fields. With the increase in nanoparticle size, the field-induced k enhancement also increases because of enhanced dipole
dipole interactions. Furthermore, we also demonstrate that the thermal and rheological properties of such response stimuli fluids are reversibly switchable and may find applications in miniature devices such as micro- and nano-electromechanical systems.

1. INTRODUCTION Magnetic nanofluid is a unique material that exhibits both the liquid and magnetic properties.1 Because the properties and the location of these fluids are easily influenced by an external magnetic field, they have been employed in many scientific, industrial, and commercial applications.2
4 These fluids have several fascinating applications such as magneto-optical wavelength filter,5,6 optical modulators,7 nonlinear optical materials,8 tunable optical fiber filter,9 optical grating,10 and optical switches.11 In addition, they are wonderful model system for fundamental studies.12 Besides, magnetic fluids have applications in magnetofluidic seals, lubricants, density separation, ink jet printers, refrigeration, tunable dampers, clutches, diagnostics in medicine, drug delivery, and so on. With depleting hydrocarbon reserves, the demand for reducing power consumption and development of superior coolants with improved performance is increasing.13 In this context, nanofluids have been considered as a potential candidate for cooling applications.14
29 Several previous studies show unusual thermal conductivity (k) enhancement in nanofluids, whereas recent reports show modest k enhancement within the predictions of classical effective medium theory (EMT). More recent systematic studies reveal that the conduction through particular agglomerates is one of the significant contributing factors for the dramatic enhancement of k. 17,26,27,30 Realizing the modest thermal conductivity enhancement in conventional nanofluids, there is an urgent need to develop nanofluids with significantly large k, especially for miniature devices such as micro- and nano-electromechanical systems (MEMS and NEMS). Toward this goal, we have demonstrated a thermal conductivity enhancement up to 300% of base fluids in r 2011 American Chemical Society

a magnetic fluid under suitable external field conditions.31 In an effort to develop magnetic nanofluid as a multifunctional smart material, we study both the thermal and rheological properties of magnetic nanofluids under different magnetic field strength and orientation with respect to the direction of heat flow. We have synthesized oleic-acid-capped magnetite (Fe3O4) nanoparticles of different sizes (3
10 nm) and carried out systematic measurements of k in two different hydrocarbon-based Fe3O4 nanofluids under varying magnetic field strengths and orientations. In addition, we follow the microstructure of the nanofluids and the switching behavior under a magnetic field.

2. MATERIALS AND METHODS We prepared magnetite nanoparticles of different particle sizes by chemical coprecipitation technique.32,33 The X-ray diffraction (XRD) studies have been done using a MAC Science MXP18 X-ray diffractometer. The 2θ values are taken from 20 to 80
using Cu Kα radiation (λ value is 1.5416 Å). A Mettler Toledo TGA/DSC (LF 1100-Star system) is used for thermogravimetric analysis (TGA). Weight loss measurements are taken from 30 to 700
C under an inert atmosphere of argon. Heating rate of 5
C/ min is maintained for the entire measurement. Vibrating sample magnetometer (VSM-Lake Shore model 7404) is used for magnetization measurements with the applied magnetic field in the range of
15 to 15 kG. The size distribution of nanoparticles is determined by dynamic light scattering (DLS) using a ZetasizerNano (Malvern Instrument). The rheological behavior of Received: May 24, 2011 Revised: June 30, 2011 Published: September 12, 2011 20097

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Figure 1. XRD pattern of Fe3O4 nanoparticles; the average particle size is ∼9.5 nm. Inset is the particle size distribution of Fe3O4 nanoparticles where the average hydrodynamic diameter is ∼10 nm.

dispersions is studied with a rotational rheometer with magneto rheological attachment (Anton Paar Physica MCR 301). Thermal conductivity was measured using a transient hot wire (KD2pro), which has accuracy in the k measurement of 5%. Testing shows that the sensor properties remain unaffected under magnetic field in the range of 0
300 G, where no change in k is observed in pure liquids.

3. RESULTS AND DISCUSSIONS 3.1. Properties of Magnetic Nanofluids. The XRD patterns (Figure 1) confirm the cubic crystal structure of magnetite with the characteristic peaks of (220), (311), (400), (422), (511), and (440). Comparison of the XRD patterns with the JCPDS data confirms that the samples are magnetite with inverse spinel structure. The average crystallite size obtained from the most intense peak of (311) in magnetite, by using the Debye
Scherrer formula (d = (0.9λ)/(β cos θ), where d is the crystallite size, β is the full width at half-maxima, λ is the incident Cu Kα wavelength of 1.546 Å, and θ is the maximum peak position), is found to be 9.5 nm. To confirm the exact identity of the magnetic particles, we have carried out room-temperature Mossbauer studies. It shows an intense central doublet due to the superparamagnetic nature of particles and two sextets due to the two structurally different iron sites in the material. Significant Zeeman sextet splitting was not observed because of the superparamagnetic relaxation that occurs when the thermal energy (kBT) is comparable to the anisotropy energy of small particles. The Mossbauer spectrum qualitatively establishes the presence of Fe2+ and Fe3+ ions in octahedral sites of magnetite crystal. The particle size obtained from DLS (Figure 1 inset) fairly matches the XRD size, indicating the absence of aggregation in the dispersed system. The total surfactant molecules in the system are WN0/M, where W is the weight percentage of the surfactant, N0 is Avogadro’s number, and M is the molecular weight of the surfactant. Therefore, the surface area a occupied by oleic acid molecules is the ratio of total surface area on particles to the number of surfactant molecules, a = (6(100
W)M)/(N0dFW), where F is the density of the particle and d is the diameter of nanoparticles. The observed weight loss of 13 wt % (Figure 2) confirms the presence of a monolayer of surfactant on nanoparticles. This surfactant monolayer ensures steric stabilization and thus prevents the nanoparticles from aggregation. Figure 2 (inset a)

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Figure 2. Thermogravimetric curve of oleic-acid-coated of Fe3O4 nanoparticles. Inset (a) schematics of oleic-acid-coated Fe3O4 nanoparticles, (b) HRTEM image of nanoparticles, and (c) magnetization curve of Fe3O4 nanoparticles.

shows the schematics representation of steric stabilization of particles by oleic acid. Figure 2 (inset b) shows HRTEM image of nanoparticle where the amorphous contrast around the nanoparticles is due to the hydrophobic organic layer. The CdO stretch band of the carboxyl group, which is present at 1710 cm
1 in the Fourier transform infrared (FTIR) spectrum of pure liquid oleic acid, was absent in the spectrum of the coated Fe3O4 nanoparticles.33 Instead, two new bands at 1542 and 1643 cm
1 are characteristic of the asymmetric υas(COO
) and the symmetric υs(COO
) stretch. A strong adsorption at 1050 cm
1 arises from C
O single bond stretching. This reveals that oleic acid is chemisorbed as a carboxylate onto the Fe3O4 nanoparticles, and the two oxygen atoms in the carboxylate are coordinated symmetrically to the Fe3O4 atoms. Moreover, the asymmetric CH2 stretch and the symmetric CH2 stretch characteristic bands shifted to a lower frequency region and indicate that the hydrocarbon chains in the monolayer surrounding the Fe3O4 nanoparticles are in a close-packed, crystalline state. Stable magnetic nanofluids are prepared by dispersing the oleic-acid-coated Fe3O4 nanoparticles in kerosene and hexadecane. The dispersions showed excellent long-term stability because nanoparticles are not influenced by the gravitational force owing to their small size. Furthermore, the steric stabilization prevents aggregation of the particles. These particles are superparamagnetic in nature, where the individual dipoles align under an applied magnetic field, exhibiting magnetization similar to those of the bulk magnetic material, but in contrast with bulk materials, the suspensions exhibit no remanence (i.e., residual magnetization) once the field is removed. The oriented dipoles quickly relax by Brownian and Neel relaxation phenomena. Figure 2 (inset c) shows the room-temperature magnetization loops of magnetite nanoparticles in the magnetic field range of (15 kG. It is known that dead layer and surfactant contribution can lead to a decrease in magnetization value. The TGA study shows a weight loss of 13% due to surfactant removal. Therefore, only 87% of the sample contributes to the saturation magnetization (MS) value. The M
H loop in Figure 2 (inset c) is after correcting the surfactant contribution. The superparamagnetic properties of nanoparticles are evident in the magnetization curve. The saturation magnetization is found to be 56 emu/g. 3.2. Thermal Properties of Magnetic Nanofluids under Field Gradients. Figure 3a shows the variation of the thermal conductivity ratio (k/kf) and the percentage of k enhancement 20098

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Figure 3. Thermal conductivity ratio (k/kf) and % of enhancement in k as a function of external magnetic field strength for kerosene-based Fe3O4 nanofluids with ϕ = 0.00031, 0.00401, 0.00819, and 0.0171. (a) Applied magnetic field parallel to temperature gradient and (b) applied magnetic field perpendicular to temperature gradient. Insets of panels a and b show the schematics of direction of heat flow for parallel and perpendicular field direction of nanoparticle path.

with magnetic field strength for kerosene-based magnetite nanofluids at four different particle loadings of ϕ = 0.00031, 0.00401, 0.00819, and 0.0171, where the field orientation is parallel to the temperature gradient. The k/kf values remain unchanged irrespective of the magnetic field strength for the lowest particle loading (ϕ = 0.00031). However, for nanofluids with higher particle loading, the k/kf increases with an increase in applied field strength. The higher the particle loading, the larger the k enhancement for a given magnetic field strength. A maximum k enhancement of 125% is observed for the nanofluid with ϕ = 0.0171 at a field strength of 378 G. The inset of Figure 3a shows the schematics of heat flux (arrow) and the phase contrast microscopy image of nanoparticle chain in the presence of magnetic field parallel to the thermal gradient. When the magnetic field direction is changed from parallel to the perpendicular to the direction of heat flow (Figure 3b), there has been no significant change in k/kf, irrespective of the strength of applied magnetic field and particle loading. The inset of Figure 3b depicts the schematics of heat flux and the microscopy images of nanoparticle structures in the presence of magnetic field, which is perpendicular to the thermal gradient. The large enhancement in k in the presence of magnetic field parallel to temperature gradient is explained as follows: Ferrofluids consist of a colloidal suspension of single domain superparamagnetic nanoparticles with a magnetic moment m. Without any external magnetic field, the magnetic moments of the scatterers orient in random direction. In the presence of an appropriate magnetic field H, the nanoparticles align in the direction of magnetic field when the magnetic dipolar interaction energy Ud(ij) dominates over the thermal energy kBT, where kB is the Boltzmann constant and T is the temperature. The dipolar interaction energy depends on the distance rij between the ith and jth particles and the mutual orientation of their magnetic moments mi and mj. When the dipolar interaction energy becomes sufficiently strong, the magnetic particles form a chain-like structure. The effective attraction between two ferromagnetic particles is described by a coupling constant L = Ud(ij)/ kBT, which involves two competing factors: magnetic dipolar interaction energy Ud(ij) and thermal energy kBT. Dipolar

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Figure 4. Variation of % of enhancement in k with volume fraction at different magnetic field strengths of 0, 126, 189, 252, and 315 G for kerosene-based Fe3O4 nanofluids. The experimental data are fitted with Maxwell upper and lower bound and HS upper and lower bound. Inset shows phase contrast optical microscopic images for (a) zero external magnetic field and (b
d) with increasing magnetic field strengths.

structure formation is expected when the dipolar potential exceeds thermal fluctuations; that is, for a dipolar coupling constant L > 1. The equilibrium chain length and flexibility of the chains depends on the orientational correlation between the magnetic moments of particles inside a chain. The chain flexibility decreases with field strength, and in strong fields, the chain aggregate resembles a stiff rod-like chain.34 The particle concentration for hard-sphere suspensions is related to its volume fraction, ϕ = nVp, where n is the number density of particles and Vp is their volume (= 4π/3r3, where r is the particle of radius). The extent of chain formation in the presence of an external magnetic field increases with an increase in ϕ since the number of particles per unit volume increases with an increase in ϕ. Therefore, for a given magnetic field strength, the enhancement in k will be higher for the nanofluid with maximum particle loading. Furthermore, the saturation magnetization of Fe3O4 nanoparticle dispersions increases with an increase in nanoparticle concentration.35 Considering the particles as spherical, the interparticle spacing (IPS) for a colloidal dispersion of monodisperse particles is given by36 IPS = 2r[(ϕm/ϕ)1/3
1]. Where r is the particle radius and ϕm is the maximum particle packing fraction, which is 0.63 for random dense packing. The IPS for the concentrations 0.00031, 0.00401, 0.00819, and 0.0171 are 117.4, 44.15, 32.7, and 23.4 nm, respectively. Therefore, with increasing ϕ, because of the decrease in interparticle spacing, the particle
particle heat transfer within the chains also becomes efficient. This explains the dramatic enhancement in thermal conductivity with increasing ϕ. Furthermore, the in situ cryogenic transmission electron microscopy observations of magnetite nanoparticle dispersions under magnetic field confirmed columnar structures exhibiting a distorted hexagonal symmetry.37 Therefore, when the magnetic field direction is parallel to the temperature gradient inside the fluid, the heat energy is effectively transported through the chainlike aggregates. Mean field models predict series and parallel modes of thermal conduction through nanofluids. The parallel mode has the geometric configuration that allows the most efficient means of heat propagation.15 Therefore, extremely large thermal conductivity enhancement is possible with parallel modes. Hashin and Shtrikman (HS) bounds for thermal conductivity of a nanofluid 20099

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Figure 5. Thermal conductivity ratio (k/kf) and the percentage of enhancement of k as a function of external magnetic field strength for hexadecane-based Fe3O4 nanofluids with ϕ = 0.0608 in the presence of different field orientations of 0, 20, 70, and 90
. Inset shows the schematics of the direction of heat and the possible nanoparticle structures under different field directions.

on the basis of volume fraction alone are given by38 " # " # 3ϕ½k 3ð1
ϕÞ½k kf 1 þ e k e 1
kp 3kf þ ð1
ϕÞk 3kp
ϕ½k ð1Þ Figure 4 shows the percentage of enhancement in k at different magnetic field strengths for kerosene-based Fe3O4 nanofluids. The Maxwell upper, lower bounds, series, and parallel bound fits are also shown in Figure 4. In the lower HS limit, nanoparticles are well-suspended, and conduction is essentially through series modes, whereas in the upper HS limit the conduction path is through dispersed particles. In the absence of magnetic field, the particles are well-dispersed, the nanofluids exhibit series mode conduction, and the observed variation of k/kf with ϕ is well within the lower Maxwell limit. In the limit (ϕkp/kf) . 1, the predicted values of k/kf for the upper HS and parallel modes are (2ϕ/3)kp/kf and ϕkp/kf, respectively. It can be seen that the experimental data points, at the highest magnetic field, fall within the parallel mode of conduction, which is a striking manifestation of HS model prediction. For magnetite nanoparticles, an average particle diameter