Article pubs.acs.org/cm
Surfactant Effects on Dispersion Characteristics of Copper-Based Nanofluids: A Dynamic Light Scattering Study Michael S. Saterlie,† Huseyin Sahin,‡ Barkan Kavlicoglu,‡ Yanming Liu,‡ and Olivia A. Graeve†,* †
Kazuo Inamori School of Engineering, Alfred University, Alfred, New York 14802, United States Advanced Materials and Devices, Inc., Reno, Nevada 89502, United States
‡
ABSTRACT: We present a study of powder agglomeration and thermal conductivity in copper-based nanofluids. Synthesis of the copper powders was achieved by the use of three different surfactants (polyvinylpyrrolidone, oleic acid, and cetyl trimethylammonium bromide). After careful determination of morphology and purity, we systematically and rigorously compared all three of the surfactants for the production of viable copper-based nanofluids using dynamic light scattering. Our results show that the use of surfactants during synthesis of copper nanopowders has important consequences on the dispersion of the powders in a base fluid. The oleic-acid-prepared powders consisted of small particles of ∼100 nm that did not change with the addition of dispersant. The CTAB-prepared powders exhibited the best dispersion characteristics, as they formed small particles of approximately 80 nm in the presence of SDBS. The thermal conductivity enhancement in our nanofluids exhibited a linear relationship with powder loading for an average particle size of ∼100 nm and similar particle size distributions that range from ∼50 to 650 nm, but independent of crystallite size and with all other factors maintained constant (surface area, surface additives, levels of oxidation) such that a 0.55 vol % loading results in a thermal conductivity enhancement of 22% over water and a 1.0 vol % loading results in a thermal conductivity enhancement of 48% over water. This study is the first to decouple the effect of a carefully characterized particle size distribution using dynamic light scattering versus crystallite size from X-ray line broadening on the thermal conductivity enhancement of a nanofluid. KEYWORDS: copper nanopowders, nanofluid, PVP, oleic acid, CTAB, chemical reduction, dynamic light scattering
1. INTRODUCTION
permits the characterization of particle size distributions at powder loadings typical for nanofluids.15,16 Nanopowders form different structures in a suspension depending on several factors such as crystallite size, type of particle/agglomerate (hard or soft), surface area and charge, dispersants, pH, temperature, and powder concentration. Changing just one of these characteristics will modify the behavior of the powders in the fluid. Thus, considerable focus has been given to the structure of agglomerates within a fluid. Prasher et al.17,18 developed a model that combines the microconvective effects of Brownian motion and aggregation of the dispersed phase. Because nanofluids exhibit an aging effect, in that a completely dispersed fluid will agglomerate over time, thermal conductivities were calculated on nanofluids with varying degrees of agglomeration. A maximum was observed somewhere between a completely dispersed phase and a fully agglomerated one. In a follow-up investigation, Evans et al.19 used Monte Carlo simulations on various volume fractions and particle sizes of powders. It was found that the thermal conductivity increases with increase in particle size and reaches a maximum depending on the volume fraction. The maximum corresponds with the formation of an interconnected network
Typical heat transfer fluids, such as water or ethylene glycol, are often used in heat transfer equipment for electronics, transportation, industrial process heating/cooling, and power generation. These conventional fluids exhibit poor thermal conductivity compared to bulk metals, resulting in an important limitation in the use of these materials for more demanding heat dissipation applications. In order to overcome this limitation, the thermal conductivity of these fluids can be enhanced through the addition of nanopowders, resulting in what are termed nanofluids, as described in a variety of reviews on the subject.1−6 The effectiveness of a nanofluid is highly dependent on minimum sedimentation of the nanopowders and maximum flow that does not result in clogging of the device. Therefore, it is extremely important to perform stability and dispersion studies of these fluids. Characterization using dynamic light scattering (DLS), which measures particle (i.e., agglomerate) size of the powders in the fluid, can be extremely useful for this purpose, and some ceramic- and metallic-based nanofluids have been analyzed by this technique.7−15 However, in some cases, the measurements have been performed at very low powder loadings due to past equipment limitations. These loadings are not representative of a functional nanofluid because the process of dilution destroys the morphological characteristics of the nanofluid. These days, modern equipment © 2012 American Chemical Society
Received: December 25, 2011 Revised: July 28, 2012 Published: August 13, 2012 3299
dx.doi.org/10.1021/cm203853f | Chem. Mater. 2012, 24, 3299−3306
Chemistry of Materials
Article
2. METHODS
of clusters. The critical factor is the high aspect ratio backbone created by the formation of the particles, which allows for enhanced conduction of phonons. That is, the most effective increases in thermal conductivity will be achieved with chained structures that have few dead ends, such as high aspect ratio fibers. On the experimental side, Philip et al.20 observed a maximum enhancement in thermal conductivity for magnetic Fe3O4 nanoparticles capped with oleic acid when a stable colloidal suspension of chain-like particles was present. No enhancement was observed for nanofluids with particle concentrations below 2 vol %, a concentration at which the nanoparticles were presumably well-dispersed and Brownian motion had the greatest influence. A thermal enhancement of 300% was exhibited for a 6.3 vol % Fe3O4 nanofluid under an external magnetic field, due to the formation of interconnected particles. The enhancement decreased past a certain magnetic field strength, which caused the individual nanoparticle chains to consolidate into larger elongated structures. Thus, it appears that the purposeful formation of stable elongated chains in nanofluids is essential in the preparation of effective nanofluids, as is certainly the case for magnetorheological fluids.21,22 In our previous study on copper-based nanofluids,23 we demonstrated that the increase in thermal conductivity was due to the formation of controlled agglomeration. Powders prepared using oleic acid and cetyl trimethylammonium bromide (CTAB) exhibited agglomeration when introduced in the base fluid, remained stable over extended periods of time, and possessed enhancements of up to 48% for the case of the 1 vol % nanofluids of the CTAB-prepared powders. Specifically, the powders in the base fluid had average particle sizes of ∼120 and ∼80 nm for the oleic-acid- and CTAB-prepared powders, respectively, at a particle loading of 0.55 vol %. When increasing the nanopowder loading to 1.0 vol %, the nanofluids of oleicacid-prepared powders became heavily agglomerated, increasing the particle size from 120 to 800 nm and resulting in settling of the powders in the nanofluid. On the other hand, the nanofluids of the CTAB-prepared powders were only slightly more agglomerated at the larger powder loading, with a particle size average of 107 nm. We now report details of the chemical reduction synthesis of the metallic copper nanoparticles described in our previous study and describe the effect of particle size versus crystallite size on thermal conductivity enhancement effects. The powders were prepared in the presence of polyvinylpyrrolidone, oleic acid, and cetyl trimethylammonium bromide surfactants. All three surfactants exhibit very different capping characteristics and have been chosen for their successful stabilization of metal copper nanoparticles in a variety of syntheses,24−36 thus, serving as effective model systems. After careful determination of morphology and purity, we systematically and rigorously compared all three of the surfactants for the production of viable copper-based nanofluids using dynamic light scattering in order to ascertain the particle size distributions of each powder within the base fluid and the effect of SDBS dispersant additions. This type of analysis is crucial for predicting the efficiency of nanoparticle additions in nanofluids, as it allows one to accurately determine when the powders start to exhibit excessive agglomeration that may eventually result in settling in the fluid. Our results show that the use of surfactants during synthesis of copper nanopowders has important consequences on the dispersion of the powders in a base fluid.
The copper nanoparticles were synthesized using a chemical precipitation technique described previously,23 in which oleic acid [CH3(CH2)7CHCH(CH2)7COOH] (MP Biomedical LLC, Solon, OH) and CTAB [cetyl trimethylammonium bromide, ((C16H33)N(CH3)3Br] (high purity grade, AMRESCO Inc., Solon, OH) were used during synthesis to protect the particles from coarsening. The source for copper was copper(II) chloride dihydrate [CuCl2·2H2O] (99+%, Alfa Aesar, Ward Hill, MA). The specific surfactant amounts used in our previous study and repeated here were 1.67 g of oleic acid and 0.57 g of CTAB. These amounts correspond to molar ratios of surfactant to copper chloride of 1:16 and 1:60 for oleic acid and CTAB, respectively. For this new study, we also report syntheses experiments in which the molar ratios for synthesis with oleic acid were 1:20 (1.33 g of oleic acid), 1:30 (0.89 g of oleic acid), 1:45 (0.59 g of oleic acid), and 1:60 (0.44 g of oleic acid), and the molar ratios for synthesis with CTAB were 1:5 (6.88 g of CTAB), 1:10 (3.44 g of CTAB), 1:30 (1.15 g of CTAB), and 1:45 (0.76 g of CTAB). In addition, we also performed studies using PVP [polyvinylpyrrolidone, (C6H9NO)n] (8000 MW, Alfa Aesar, Ward Hill, MA) as surfactant using molar ratio amounts of 1:1 (10.50 g of PVP), 1:5 (2.10 g of PVP), 1:10 (1.05 g of PVP), 1:15 (0.70 g of PVP), and 1:30 (0.35 g of PVP). Once the reaction was complete, the fluid was removed from the reactor and emptied into 50 mL centrifuge tubes and subsequently centrifuged using an Eppendorf Centrifuge 5810 (Eppendorf, Hamburg, Germany) for 10 min at 11 000 rpm. The clear supernatant liquid was discarded, and 30 mL of 50/50 semiconductor grade methanol (99.9%, Alfa Aesar, Ward Hill, MA 01835) and DI water was added to the centrifuge tubes containing the copper. The powders were washed twice with the methanol and DI water solution and then methanol as the final wash, decanting the supernatant after each centrifugation. The tubes containing the cleaned copper powders were then placed in a vacuum desiccator for 2−3 days to dry. Once dry, the powders were emptied into a mortar and subsequently ground into fine powders, then stored and sealed inside small plastic vials for incorporation into a base fluid and/or characterization. The nanofluids consisted of 0.55 vol % copper nanopowders and DI water as the base fluid. Phase analysis was performed on a Philips PW1800 X-ray diffractometer (Koninklijke Philips Electronics N.V., Eindhoven, The Netherlands) using Cu Kα radiation. Scans were conducted over the range 20−80° 2θ using a step size of 0.05 and a dwell time of 3 s. The diffraction patterns were analyzed using Jade 8 software (Materials Data Inc., Livermore, CA). A Pearson VII deconvolution was used to calculate the area under the diffraction peaks for crystallite size information. To determine the copper content within each sample, the spiking method developed by Lennox et al.37 was utilized to quantitatively analyze the samples through XRD. For each spiking run, approximately 0.1 g of Cu2O powders was successively added to 1 g of the powder samples. The Cu2O powders were synthesized in a similar manner as the copper powders but without the use of surfactant and excluding nitrogen flow, resulting in pure Cu2O powders. Surface area was measured using a Micromeritics Tristar 3000 surface area and porosity analyzer (Micromeritics Instrument Corp., Norcross, GA). High-resolution imaging of the powder samples was completed using a JEOL 2100F transmission electron microscope (JEOL, Inc., Tokyo, Japan). For TEM imaging, the powders were dispersed in acetone and then drop coated onto a copper grid. Fourier transform infrared (FTIR) spectroscopy was performed in transmission using a Nicolet 6700 FTIR spectrometer (Thermo Electron Corp., Newington, NH) with a Smart Collector accessory (model# 0031-999, Spectra-Tech Inc., Shelton, CT) on the pure dried powders. This accessory enables the analysis of highly scattering solids and is also useful when the powder must be analyzed without modification. Particle size measurements were performed on a Microtrac Nanotrac Ultra dynamic light scattering (DLS) system (Microtrac Inc., Montgomeryville, PA). This system determines the particle size distribution of particles in solution, with measurement capability from 0.8 nm to 6.5 μm. Multiple measurements of five runs each, at a run 3300
dx.doi.org/10.1021/cm203853f | Chem. Mater. 2012, 24, 3299−3306
Chemistry of Materials
Article
time of 30 s, were averaged on each sample using the appropriate parameters determined by the estimated particle size range and fluid viscosity, as is recommended by the instrument manufacturer and in conjunction with ASTM standard E2490-09.
3. RESULTS AND DISCUSSION On the basis of a number of factors including particle size, crystallite size, and oxide content, the 1:30 PVP, 1:16 oleic acid, and 1:60 CTAB powders were found to be optimum for incorporation into a nanofluid. The XRD patterns for these powders are illustrated in Figure 1. The CTAB and oleic acid
Figure 2. (a) Average crystallite sizes and (b) surface areas for the powders prepared using various surfactant amounts of PVP, oleic acid, and CTAB.
Figure 1. Powder X-ray diffraction patterns for powders synthesized using (a) CTAB (1:60 CTAB to copper molar ratio), (b) oleic acid (1:16 oleic acid to copper molar ratio), and (c) PVP (1:30 PVP to copper molar ratio).
synthesized from each surfactant. The PVP-prepared powders are significantly agglomerated (Figure 3a). These agglomerates are several hundred nanometers in diameter and could not be reduced even with significant ultrasonication, which indicates that the PVP-prepared powders consist of hard agglomerates. Even with this level of agglomeration, the surface area analysis follows the expected trend with crystallite size because the analysis gas covers the majority of the powder surfaces; that is, the particles/agglomerates are porous. For the case of the CTAB-prepared powders (Figure 3c), completely unagglomerated copper particles of 35−50 nm in size are evident, in agreement with crystallite size measurements. On the other hand, the oleic-acid-prepared powders exhibit a translucent layer that surrounds the particles (Figure 3b), preventing the analysis gas from reaching the inner surfaces of the powder particles. As the amount of surfactant is increased, the surface area decreases because the surfactant promotes higher levels of agglomeration. This translucent layer stays attached to the powders even after vigorous washing in methanol. Thus, we have shown that, while PVP and CTAB can be removed from the powder surfaces during washing, the oleic acid is much more persistent. The cleaning process also results in some level of hard agglomeration of the PVP-prepared powders but not of the CTAB-prepared powders. The surface areas for the 1:30 PVP, 1:16 oleic acid, and 1:60 CTAB powders were ∼29, 15, and 16 m2/g, respectively. The presence of oleic acid after powder synthesis and cleaning can also be confirmed by FTIR spectral analysis (Figure 4). The spectrum for these powders contains several peaks that coincide with peaks in the spectrum for the pure surfactant. There are two sharp C−H stretching peaks located at 2920 and 2850 cm−1 and a carbonyl stretching frequency at approximately 1670 cm−1. The final two peaks at 1400 and
surfactants are better at preventing oxidation of the copper nanopowders, as will be discussed in detail later. The crystallite sizes of all of the powders, calculated from X-ray line broadening, are plotted in Figure 2a. The 1:30 PVP-prepared powders have a crystallite size of 13.5 ± 2.1 nm, the 1:16 oleic acid-prepared powders have a crystallite size of 14.7 ± 1.1 nm, and the 1:60 CTAB-prepared powders have a crystallite size of 38.0 ± 0.9 nm. As the amount of surfactant increases, the resultant crystallite size is reduced. For the case of the powders synthesized in the presence of PVP, the large heterocycle of the polymer coupled with the long polymer chain hinders growth of the particles,38 thus keeping the crystallites in the range of 2−16 nm in diameter. For the case of the powders synthesized in the presence of oleic acid and CTAB, the Cu2+ ions are not completely surrounded by surfactant at lower surfactant concentrations, thus the crystallites experience some growth. As the surfactant concentration increases from 1.574 to 5.901 mmol for oleic acid and 1.574 to 18.88 mmol for CTAB, the average crystallite size is seen to decrease from approximately 45 to 15 nm for the oleic acid powders and from 37 to 10 nm for the CTAB powders. Surface area analysis of the powders for the various concentrations of each surfactant (Figure 2b) confirms that, for the PVP and CTAB samples, the surface area increases with increase in surfactant concentration. That is, the surface area increases with decrease in crystallite size, as would be expected. Interestingly, the trend is opposite for the oleic acid samples. The 1:30 PVP-prepared powders have a surface area of 29.0 ± 0.13 m2/g, the 1:16 oleic acid-prepared powders have a surface area of 15.1 ± 0.09 m2/g, and the 1:60 CTABprepared powders have a surface area of 16.4 ± 0.08 m2/g. Figure 3 presents the TEM images for the three optimum samples (1:30 PVP, 1:16 oleic acid, and 1:60 CTAB) 3301
dx.doi.org/10.1021/cm203853f | Chem. Mater. 2012, 24, 3299−3306
Chemistry of Materials
Article
of 2920 cm−1, while the C−N peaks appear at 1074 cm−1.40,41 The two peaks corresponding to the asymmetric and symmetric stretching of CH2 within CTAB are located at 2925 and 2856 cm−1. The antisymmetric stretching mode of the trimethylammonium headgroup for CTAB is identified by a peak around 3020 cm−1.42 For the case of the PVP- and CTABprepared powders, no signals corresponding to the characteristic peaks for each surfactant were present; therefore, there is no surfactant attached to the surfaces after washing (Figure 5).
Figure 5. FTIR spectra for (a) the PVP-prepared copper powders, (b) pure PVP, (c) CTAB-prepared copper powders, and (d) pure CTAB. Figure 3. Transmission electron micrographs for the (a) 1:30 PVPprepared powders, (b) 1:16 oleic-acid-prepared powders, and (c) 1:60 CTAB-prepared powders.
The fraction of oxide phase (Cu2O) present on the powders can be related to the crystallite size (Figure 6). The powders contain an increasing amount of oxide contamination as the crystallite size decreases for the PVP and CTAB samples, which is attributable to the higher surface area of these powders. Assuming that every particle’s surface forms an oxide layer with the same depth of Cu2O regardless of the diameter, smaller
Figure 4. FTIR spectrum for (a) the oleic-acid-prepared copper powders and (b) pure oleic acid.
1240 cm−1 are attributed to the C−O−H bond with an in-plane bend and the C−O stretching, respectively, within the carboxyl headgroup.39 The FTIR spectra for pure PVP powder exhibits a resonance peak for CO at 1663 cm−1, which is characteristic of the heterocycle of PVP, while the NO3−1 group and the N− OH complex peaks are located at 1363 and 1288 cm−1, respectively. The C−H vibration corresponds to a wavenumber
Figure 6. Crystallite size vs fraction of cupric oxide contamination for the various copper powders. 3302
dx.doi.org/10.1021/cm203853f | Chem. Mater. 2012, 24, 3299−3306
Chemistry of Materials
Article
second step involves the reduction of Cu2+ to Cu0 due to the addition of the sodium borohydride solution and aided by the presence of the PVP, which contributes a higher electron density to the sp orbitals of copper ions than does H2O and, thus, allows the Cu2+−PVP complex to obtain electrons more readily. The formation of these surfactant−metal complexes permits the successful formation of small metal crystallites and corresponds well with what Zhang et al.41 observed in their study. Throughout the synthesis, the surfactant−metal particle system is dynamic due to the weak bonding of the PVP molecules to the metal particles at the surfactant/powder interface. The PVP surfactant is constantly detaching and reattaching itself because of the weak coordinative chemical bonding of C−N with the metal. This results in agglomeration and/or crystal growth during synthesis in both Zhang et al.’s work and in our own work. PVP is typically added as a surface coating during reactions to minimize crystal growth and to control agglomeration. Prevention of agglomeration is sometimes largely achieved and sometimes not achieved,27,34,36,41,43−46 depending on many variables particular to the system in question and whether the PVP coating is left on the powders or removal is attempted. Thus, addition of PVP will not automatically result in unagglomerated nanoparticles. Oleic acid is a surfactant characterized by a long alkyl chain with a carboxyl headgroup, which is the center of negative charge for the molecule. In the presence of oleic acid and water, the positively charged Cu2+ ions are attracted to the carboxyl head groups of the surfactant molecules, forming colloidal structures (Figure 7b). Once the metal ions are reduced, the strongly charged carboxyl heads adsorb on the surface of the metal particles, thus protecting them from growth and oxidation. As mixing continues, the stirring causes the colloids to collide with each other, forming agglomerates but maintaining a small crystallite size. This is the key to the inhibition of both crystallite growth and oxide layer formation. The oleic acid heads adsorbed on the surface create a strong barrier against oxidation, while the hydrophobic tails hinder the interaction with other metal particles preventing crystallite size growth. Due to this strong bonding between the oleic acid and the surface of the copper particles, washing of the powders in methanol cannot detach the surfactant, therefore exhibiting oxidation protection during and after washing28,29 but also causing agglomeration.47 In contrast, the use during synthesis of the cationic surfactant CTAB does not result in agglomeration. To start with, once the CTAB is dissolved in water, the positively charged headgroup will not be attracted to the Cu2+ ions, so no surfactant−ion complex is formed. Building upon results from several studies,14,25 we propose that once the metal ions are reduced to zero valency and some initial nucleation and growth of particles takes place, hydroxyls form on the surface, creating a negatively charged surface, particularly considering the pH of ∼11−12 in our system during synthesis. The electron-deficient CTAB molecule is then attracted to the negatively charged particles, adsorbing on the surface (Figure 7c). To determine agglomeration behavior of the powders in a water base fluid, the particle size distributions were determined for the powders dispersed at a concentration of 0.55 vol % with and without SDBS (15 wt %) as a dispersing agent. Without SDBS, the PVP- and CTAB-prepared powders exhibited average particle sizes in the submicrometer to micrometer range (Figure 8a), whereas the oleic-acid-prepared powders were centered at smaller sizes (∼100 nm). The PVP-prepared
particles will exhibit a greater volume of the oxide phase compared to larger particles. In the oleic acid samples, increasing Cu2O phase coincides with increasing crystallite size, as is the case for the surface area. Thus, it appears that the surfactant left on the surface of the particles inhibits oxidation, even when the crystallite size is decreasing. Therefore, not unexpectedly, the oleic acid acts as an oxidation protector by virtue of its presence. The PVP-, CTAB-, and oleic-acidprepared powders contained 40.2, 12.0, and 8.2% cupric oxide phase, respectively. The very high amount of cupric oxide in the PVP-prepared powders supports the finding of hard agglomeration in these powders. Since all powders are processed the same way, if the PVP powder surfaces are thoroughly cleaned (probably as early as during the first cleaning step), then any subsequent cleaning steps result in significant agglomeration and oxidation. The same is not the case for the CTAB-prepared powders, which are cleaned only enough to remove all of the surfactant, but not enough to promote agglomeration and oxidation, as is evident in Figure 3. The powder characteristics described so far can be understood within the context of the attachment mechanisms for each surfactant. For the case of PVP (Figure 7a), there is
Figure 7. Attachment and reduction mechanisms during precipitation of copper in the presence of (a) PVP, (b) oleic acid, and (c) CTAB.
formation of a complex between the polymer molecules and the positive metal ions in the salt solution because of the strong negative polarity of the oxygen ions in the PVP molecules, as described by Zhang et al.41 for the case of silver nanoparticle synthesis. The first step is the formation of coordinative bonding between PVP and the copper ions. Since the copper salt precursor is in the form of a dihydrate, we assume that two PVP molecules surround the copper ions such that there is a one-to-one substitution of waters of hydration with PVP. This is a reasonable assumption since the nitrogen and oxygen of the PVP have a stronger coordinative field compared to water. The 3303
dx.doi.org/10.1021/cm203853f | Chem. Mater. 2012, 24, 3299−3306
Chemistry of Materials
Article
and can have a bigger impact when higher amounts of powder are added to the base fluid. On the other hand, the CTAB-prepared powders have clean surfaces and the addition of SDBS to the nanofluid should have a measurable effect, involving the dissolution of the SDBS phenyl sulfonic group into water and subsequent adsorption into the copper surfaces. In a neutral aqueous medium, such as what is found in our nanofluids, copper particles have a positively charged surface. The dissociated phenyl sulfonic group carries a negative charge, which facilitates its absorption onto the positively charged surface of the copper nanoparticles, resulting in electrostatic stabilization and a unimodal distribution that extends from ∼50 to 250 nm. Before addition of SDBS, the nanofluid has a particle size centered around 1 μm because there is no stabilizing agent to keep the powders separated from each other. After addition of SDBS, the average particle size reduces to ∼80 nm, thus showing that this nanofluid consists of soft agglomerates. The thermal conductivity enhancement of this latter nanofluid was found to be 22% over water, the same as for the oleic-acid-prepared powders. From this, we associate an average particle size of ∼100 nm with a thermal conductivity enhancement of 22% for nanofluids with 0.55 vol % loadings. It should be pointed out that the levels of oxidation for both sets of powders are similar (12.0 and 8.2% for oleic-acid- and CTAB-prepared powders, respectively), the surface areas are similar (15 and 16 m2/g for oleic-acid- and CTAB-prepared powders, respectively), and the particle size distributions are similar. The only significant difference between the two powders is the crystallite size, with values of 14.7 ± 1.1 nm for the oleic-acid-prepared powders and 38.0 ± 0.9 nm for the CTAB-prepared powders. Thus, the behavior we are seeing from the perspective of thermal conductivity enhancement is independent of crystallite size. When mixing 1 vol % of the CTAB-prepared powders in water, we obtained a thermal conductivity enhancement of 48% over water, roughly double what we obtained for the 0.55 vol % nanofluids, so a doubling of the powder loading resulted in doubling of the thermal conductivity enhancement. On this basis, we conclude that there is an approximate linear relationship between the powder loading and thermal conductivity enhancement for reasonable nanopowder loadings typical for a nanofluid, at a constant particle size of ∼100 nm and independent of crystallite size, excluding any other factors such as phase purity, particle size distribution, and surface area variations. The thermal conductivity enhancement values we obtain are not in agreement with either effective medium theory or the Maxwell−Garnett theory described in detail by Timofeeva et al.,13 which states that the thermal conductivity enhancement can be described by
Figure 8. Particle size distributions for copper powders (a) in water and (b) water with SDBS as dispersant.
powders extended from about 230 nm to 2.5 μm and had a bimodal distribution, which confirms the difficulties in using PVP as a surfactant for the synthesis of powders that exhibit unimodal and narrow particle size distributions. The particle size distribution for the CTAB-prepared powders was much narrower, unimodal, and extended from ∼350 nm to 2 μm, with the peak centered at 630 nm. Finally, the distribution for the oleic-acid-prepared powders was centered at ∼100 nm, was extremely broad and multimodal, and extended from ∼40 nm to 1 μm. These powders also suffered from significant agglomeration because of the presence of the oleic acid on the surfaces, which does not result in controlled stabilization of the powders. With addition of SDBS, the average particle size of the PVPprepared powders did not decrease (Figure 8b, although the peak at the lower size range did reduce in frequency and the distribution became almost unimodal, with a peak at ∼970 nm. Because there was no reduction in particle size of these powders, it can be concluded that the majority of the particles are hard agglomerates of about 1 μm in size. It should be noted that the powders in this nanofluid settled in the base fluid in a matter of hours. For the case of the oleic-acid-prepared powder, the distribution did not change significantly, although the distribution became less broad. The SDBS has little effect on these powders because they are coated with oleic acid, although some level of soft agglomeration is present, as evidenced by the slight narrowing of the distribution, meaning that the outlier particles at the lower end of the scale are soft agglomerates that can be dispersed when the SDBS is added. We previously determined that the 0.55 vol % nanofluids of the oleic-acidprepared powders had a thermal conductivity enhancement of 22% over water.23 When preparing nanofluids with loadings of 1.0 vol % of these same powders, the particle size increased dramatically to an average value of 800 nm (see Figure 2 of our previous publication23). We attribute this to the presence of the oleic acid that can serve as glue that binds the powders together
k nf = 1 + 3 × ϕ (effective medium theory) ko
(1)
3(k1 − ko) k nf =1+ × ϕ (Maxwell−Garnett theory) ko k1 + 2ko (2)
where knf is the thermal conductivity of the nanofluid, ko (H2O) = 0.60 W/m·K is the thermal conductivity of the base fluid, k1 (Cu) = 400 W/m·K is the thermal conductivity of the nanopowder, and ϕ is the nanopowder volume fraction. With a powder loading of 0.55 vol %, the thermal conductivity 3304
dx.doi.org/10.1021/cm203853f | Chem. Mater. 2012, 24, 3299−3306
Chemistry of Materials
Article
validity of our conclusions. For now, we confirm that an average particle size of ∼100 nm and a distribution that extends from ∼50 to 650 nm results in thermal conductivity enhancements that are significantly above the theoretical values predicted from effective medium theory or the Maxwell− Garnett theory. This conclusion was tested with two sets of powders, prepared using either oleic acid or CTAB, and is independent of powder crystallite size.
enhancement values calculated from eqs 1 and 2 are 1.65 and 1.64%, respectively. For loading of 1.0 vol %, the values are 3.00 and 2.99%. Clearly, our nanofluids are exhibiting enhancement values significantly above theoretical predictions. This is not unexpected, as many studies have shown this effect for a variety of systems.1−6 Nevertheless, there have been a few studies that have not shown an enhancement. In particular, Timofeeva et al.’s13 alumina nanofluids exhibited thermal conductivities that were slightly lower than predictions from effective medium theory. Since their DLS measurements were executed at low powder loadings, the measurements of thermal conductivity enhancement cannot be correlated to a particle size distribution since the formation and dispersion of agglomerates in the nanofluids cannot be determined from tests of suspensions with low loadings. Timofeeva et al. also determined that the geometry of agglomerates plays an important role in the thermal conductivity enhancement of specific nanofluids, with dendritic or fractal aggregates being optimum for enhancement of conductivity. The presence of elongated shapes in our nanofluids might be surmised from the particle size distributions of Figure 8. Perfectly spherical geometries would result in a scattering signal that is homogeneous and symmetrical about the peak. However, our signals are unsymmetrical and have extended tales. While this is not definitive proof, we believe further analyses of the DLS signal can result in a better assessment of shape in order to resolve this question. In summary, we have shown that the use of surfactants during synthesis of copper nanopowders has important consequences on the dispersion of the powders in a base fluid. For the case of PVP-prepared powders, since the powders contain significant hard agglomerates, the dispersion in base fluid, even in the presence of SDBS, is not effective. The oleicacid-prepared powders exhibit scant agglomeration, which changes little when introduced in base fluid because the powders have a minimal interaction with the SDBS dispersing agent. From the perspective of dispersion, the CTAB-prepared powders are optimum for several reasons. After synthesis, the CTAB is eliminated from the surfaces, resulting in clean powders, which can easily be redispersed in base fluid by the use of SDBS. Significantly, we have determined that the thermal conductivity enhancement in water-based nanofluids of copper exhibits a linear relationship with powder loading for an average particle size of ∼100 nm and similar particle size distributions that range from ∼50 to 650 nm, but independent of crystallite size and with all other factors maintained constant (surface area, surface additives, levels of oxidation) such that a 0.55 vol % loading results in a thermal conductivity enhancement of 22% over water and a 1.0 vol % loading results in a thermal conductivity enhancement of 48% over water. Timofeeva et al.,13 Prasher et al.,17,18 and Evans et al.19 have correctly indicated that there is limited experimental characterization of nanofluid systems. While there has been some progress in this direction, there are still difficulties associated with obtaining narrow particle size distributions, especially because of the dynamic nature of the formation of the agglomerates in the nanofluid. This study is the first to decouple the effect of a carefully characterized particle size distribution using dynamic light scattering versus crystallite size from X-ray line broadening on the thermal conductivity enhancement of a nanofluid. We are currently completing a study in which other particle loadings and narrower particle size distributions are being tested in order to ascertain the full
4. CONCLUSIONS In this study, copper powders were successfully produced by precipitation in the presence of three different surfactants, polyvinylpyrrolidone (PVP), oleic acid, and cetyl trimethylammonium bromide (CTAB). Depending on the surfactant, the crystallite size and percent oxide on the powders were successfully altered. For all powders, as the surfactant concentration increased, the crystallite size decreased. In the case of PVP and CTAB, this reduction in crystallite size increased the surface area. The samples synthesized in oleic acid exhibited the best oxidation protection due to the persistence of the organic layer surrounding the metal particles after cleaning. Dynamic light scattering analysis results showed that the PVP-prepared copper powders formed hard agglomerates of ∼1 μm that settled out rapidly, even in the presence of a dispersant. The oleic-acid-prepared powders consisted of small agglomerates of ∼100 nm. The CTAB-prepared powders exhibited the best dispersion characteristics, as they formed small agglomerates of approximately 80 nm in the presence of SDBS. From recent studies on aggregation kinetics, it appears that the careful agglomeration of powders into branched structures plays a key role in the anomalous increase in thermal conductivity of nanofluids. Therefore, to be able to form nanofluids of greater particle loadings and stable elongated chains, a complete dispersion study must be completed. This type of analysis is crucial for predicting the efficiency of nanoparticle additions in nanofluids, as it allows one to accurately determine when the powders start to exhibit excessive agglomeration that may eventually result in settling in the fluid. Our results show that the use of surfactants during synthesis of copper nanopowders has important consequences on the dispersion of the powders in a base fluid. It is not necessarily the case that all surfactants will result in unagglomerated powders. We have determined that the thermal conductivity enhancement in water-based nanofluids of copper exhibit a linear relationship with powder loading for an average particle size of ∼100 nm and similar particle size distributions that range from ∼50 to 650 nm, but independent of crystallite size and with all other factors maintained constant (surface area, surface additives, levels of oxidation) such that a 0.55 vol % loading results in a thermal conductivity enhancement of 22% over water and a 1.0 vol % loading results in a thermal conductivity enhancement of 48% over water. These results are not in agreement with effective medium theory or Maxwell−Garnett theory, which predict much lower values closer to 3% enhancement. This study is the first to decouple the effect of a carefully characterized particle size distribution using dynamic light scattering versus crystallite size from X-ray line broadening on the thermal conductivity enhancement of a nanofluid at typical powder loadings found in nanofluids. 3305
dx.doi.org/10.1021/cm203853f | Chem. Mater. 2012, 24, 3299−3306
Chemistry of Materials
■
Article
(27) Wu, C.; Mosher, B. P.; Zeng, T. J. Nanopart. Res. 2006, 8, 965− 969. (28) Yang, J.-G.; Yang, S.-H.; Okamoto, T.; Bessho, T.; Satake, S.; Ichino, R.; Okido, M. Surf. Sci. 2006, 600, L318−L320. (29) Jian-guang, Y.; Yuang-lin, Z.; Okamoto, T.; Ichino, R.; Okido, M. J. Mater. Sci. 2007, 42, 7638−7642. (30) Haas, I.; Shanmugam, S.; Gedanken, A. J. Phys. Chem. B 2006, 110, 16947−16952. (31) Wang, Y.; Chen, P.; Liu, M. Nanotechnology 2006, 17, 6000− 6006. (32) Chandra, M.; Indi, S. S.; Das, P. K. Chem. Phys. Lett. 2006, 422, 262−266. (33) Chen, L.; Zhang, D.; Chen, J.; Zhou, H.; Wan, H. Mater. Sci. Eng., A 2006, 415, 156−161. (34) Sarkar, A.; Mukherjee, T.; Kapoor, S. J. Phys. Chem. C 2008, 112, 3334−3340. (35) Kanninen, P.; Johans, C.; Merta, J.; Kontturi, K. J. Colloid Interface Sci. 2008, 318, 88−95. (36) Lee, Y.; Choi, J.-R.; Lee, K. J.; Stott, N. E.; Kim, D. Nanotechnology 2008, 19, 415604. (37) Lennox, D. H. Anal. Chem. 1957, 29, 766−770. (38) Fried, J. R. Polymer Science & Technology, 2nd ed.; Prentice Hall: New Jersey, 2003; Chapter 8. (39) Brundle, C. R.; Evans, C. A.; Wilson, S. Encyclopedia of Materials Characterization; Butterworth-Heinemann: Boston, MA, 1992; pp 413−460. (40) Wang, H.; Qiao, X.; Chen, J.; Wang, X.; Ding, S. Mater. Chem. Phys. 2005, 94, 449−453. (41) Zhang, Z.; Zhao, B.; Hu, L. J. Solid State Chem. 1996, 121, 105− 110. (42) Campbell, R. A.; Parker, S. R. W.; Day, J. P. R.; Bain, C. D. Langmuir 2004, 20, 8740−8753. (43) Zhu, H.-T.; Zhang, C.-Y.; Yin, Y.-S. J. Cryst. Growth 2004, 270, 722−728. (44) Tang, X.-F.; Yang, Z.-G.; Wang, W.-J. Colloids Surf., A 2010, 360, 99−104. (45) Raut, D.; Wankhede, K.; Vaidya, V.; Bhilare, S.; Darwatkar, N.; Deorukhkar, A.; Trivedi, G.; Salunkhe, M. Catal. Commun. 2009, 10, 1240−1243. (46) Singh, M.; Sinha, I.; Premkumar, M.; Singh, A. K.; Mandai, R. K. Colloids Surf., A 2010, 359, 88−94. (47) Khanna, P. K.; Kale, T. S.; Shaikh, M.; Rao, N. K.; Satyanarayana, C. V. V Mater. Chem. Phys. 2008, 110, 21−25.
AUTHOR INFORMATION
Corresponding Author
*Tel: (607) 871-2749. Fax: (607) 871-2354. E-mail: graeve@ alfred.edu. Notes
The authors declare no competing financial interest.
■
ACKNOWLEDGMENTS
■
REFERENCES
This project was funded by the National Science Foundation under Contract No. IIP 0823112. The assistance of Prof. Miguel J. Yacamán and Dr. Alvaro Mayoral in the TEM imaging is gratefully acknowledged.
(1) Choi, S. U. S. J. Heat Transfer 2009, 131, 033106. (2) Li, Y.; Zhou, J.; Tung, S.; Schneider, E.; Xi, S. Powder Technol. 2009, 196, 89−101. (3) Wen, D.; Lin, G.; Vafaei, S.; Zhang, K. Particuology 2009, 7, 141− 150. (4) Murshed, S. M. S.; Leong, K. C.; Yang, C. Appl. Therm. Eng. 2008, 28, 2109−2125. (5) Wang, X.-Q.; Mujumdar, A. S. Int. J. Therm. Sci. 2007, 46, 1−19. (6) Das, S. K.; Choi, S. U. S.; Patel, H. E. Heat Transfer Eng. 2006, 27, 3−19. (7) Zhu, H. T.; Li, C. J.; Wu, D. X.; Zhang, C. Y.; Yin, Y. S. Sci. China, Ser. E: Technol. Sci. 2010, 53, 360−368. (8) Wen, D.-S.; Ding, Y.-L. IEEE Trans. Nanotechnol. 2006, 5, 220− 227. (9) Raykar, V. S.; Singh, A. K. Thermochim. Acta 2010, 502, 60−65. (10) Wang, X.-J.; Zhu, D.-S.; Yang, S. Chem. Phys. Lett. 2009, 470, 107−111. (11) Lo, C.-H.; Tsung, T.-T.; Chen, L.-C.; Su, C.-H.; Lin, H.-M. J. Nanopart. Res. 2005, 7, 313−320. (12) Lee, D.; Kim, J.-W.; Kim, B. G. J. Phys. Chem. B 2006, 110, 4323−4328. (13) Timofeeva, E. V.; Gavrilov, A. N.; McCloskey, J. M.; Tolmachev, Y. V.; Sprunt, S.; Lopatina, L. M.; Selinger, J. V. Phys. Rev. E 2007, 76, 061203. (14) Li, X.; Zhu, D.; Wang, X. J. Colloid Interface Sci. 2007, 310, 456− 463. (15) Sinha, K.; Kavlicoglu, B.; Liu, Y.; Gordaninejad, F.; Graeve, O. A. J. Appl. Phys. 2009, 106, 064307. (16) Kelly, J. P.; Graeve, O. A. Effect of Powder Characteristics on Nanosintering. In Novel Sintering Processes, Nanosintering & Grain Growth; Castro, R. H. R., Ed.; Springer Science: New York, 2012; in press. (17) Prasher, R.; Evans, W.; Meakin, P.; Fish, J.; Phelan, P.; Keblinski, P. Appl. Phys. Lett. 2006, 89, 143119. (18) Prasher, R.; Phelan, P. E.; Bhattacharya, P. Nano Lett. 2006, 6, 1529−1534. (19) Evans, W.; Prasher, R.; Fish, J.; Meakin, P.; Phelan, P.; Keblinski, P. Int. J. Heat Mass Transfer 2008, 51, 1431−1438. (20) Phillip, J.; Shima, P. D.; Raj, B. Nanotechnology 2008, 19, 305706. (21) Wang, X.; Gordaninejad, F. J. Intell. Mater. Syst. Struct. 1999, 10, 601−608. (22) Goncalves, F. D.; Koo, J.-H.; Ahmadian, M. Shock Vib. Digest 2006, 38, 203−219. (23) Saterlie, M. S.; Sahin, H.; Kavlicoglu, B.; Liu, Y.; Graeve, O. A. Nanoscale Res. Lett. 2011, 6, 217. (24) Liu, C. M.; Guo, L.; Xu, H. B.; Wu, Z. Y.; Weber, J. Microelectron. Eng. 2003, 66, 107−114. (25) Wu, S.-H.; Chen, D.-H. J. Colloid Interface Sci. 2004, 273, 165− 169. (26) Athawale, A. A.; Katre, P. P.; Kumar, M.; Majumdar, M. B. Mater. Chem. Phys. 2005, 91, 507−512. 3306
dx.doi.org/10.1021/cm203853f | Chem. Mater. 2012, 24, 3299−3306
