Article pubs.acs.org/IECR
Green High-Gravitational Synthesis of Silver Nanoparticles Using a Rotating Packed Bed Reactor (RPBR) Chee Meng Ng,† Pao Chi Chen,*,‡ and Sivakumar Manickam*,† †
Department of Chemical and Environmental Engineering, Faculty of Engineering, The University of Nottingham Malaysia Campus, Jalan Broga, 43500 Semenyih, Selangor D.E., Malaysia ‡ Department of Chemical and Materials Engineering, Lunghwa University of Science and Technology, No. 300, Section 1, Wanshou Road, Guishan, Taoyuan County 33306, Taiwan (R.O.C.) ABSTRACT: Although the synthesis of silver nanoparticles via chemical precipitation is the easiest to scale up for industrial production, the use of conventional stirring methods suffers from large and widely distributed particle sizes due to poor macroand micromixing efficiency which is vital in providing the necessary supersaturated conditions. These problems can be mitigated using the high-gravitational mixing method which significantly improves mixing efficiency and greatly reduces reaction times. In this work, we describe the preparation of silver nanoparticles from green materials using a high-gravitational rotating packed bed reactor and present our findings on the significance and effects of concentration and feed flow rate of reactants and packed bed rotation speed on the sample particle size and recovery yield. Taguchi statistical analysis was used to optimize each parameter for small particle size and high product yield. To determine the particle size and silver concentration of the synthesized samples, dynamic light scattering (DLS) and inductively coupled plasma mass spectrometry (ICP) were used respectively. X-ray diffraction (XRD), UV−vis spectroscopy, and transmission electron microscopy (TEM) imaging were used for further characterization of the produced nanoparticles.
1. INTRODUCTION Silver possesses excellent optical, chemical, and electronic properties in addition to being a well-known antimicrobial agent. Silver nanoparticles’ remarkable electrical conductivity lends itself well to semiconductor applications.1−3 Due to its high catalytic activity, silver is also commonly utilized as catalysts either in its original form or as nanocomposites.4 In its nanoparticle form, the antimicrobial effects of silver occur through the latching and perforation of the particles through the bacterial cell wall and their subsequent interference with the cell’s growth signaling pathway.5,6 The synthesis of silver nanoparticles is usually done using photoreduction, microemulsion, and chemical precipitation methods.7−10 The photoreduction and chemical precipitation methods both involve the reduction of silver cations through light irradiation and chemical reducing agents respectively. The microemulsion technique is done by dissolving silver salts in a supercritical fluid before expanding the fluid through a nozzle into a reducing agent-containing solution. While each of these synthesis methods carries its own merits, the chemical precipitation method has the advantage of being the easiest to scale-up for mass industrial production. A typical chemical precipitation process involves the reduction of silver salts with a reducing agent such as formaldehyde, N,N-dimethylformamide, or ascorbic acid.11−13 The particle growth and agglomeration of the nanoparticles are controlled using protecting agents such as Daxad 19, polyvinylpyrrolidone, and polyvinyl alcohol.11,13,14 The stabilizing capability of polymeric stabilizers stems from the steric effects of the formed polymer-silver complexes which reduce particle−particle contact and, hence, minimize agglomeration.15 © 2012 American Chemical Society
The positive effects of conventional reducing and protecting agents, however, are hampered by their high reactivities which pose environmental and biological hazards. The growing concern over the environmental impact from the use of harmful chemicals and high waste generation has necessitated the identification of less-toxic and biodegradable solvents and reactants, as well as the optimization of synthetic pathways to minimize waste.16 In the case of silver nanoparticle production, several alternative green synthetic methods have been reported. A reaction pathway for the synthesis of silver nanoparticles was proposed by Raveendran et al.17 in which β-D-glucose and starch, both nontoxic and inexpensive, were used as reducing and capping agents respectively for silver nitrate. It was found that the hydrogen bonding resulting from the presence of hydroxyl groups in starch expedited the molecular complexation of silver ions. The use of soluble starch as both reducing and protecting agents for the hydrothermal synthesis of silver nanoparticles has also been reported.18 In the study, the aldehyde component of soluble starch was used for silver ion reduction while the starch component acts as a stabilizer. While the aforementioned green techniques are effective in producing particles with small sizes and narrow distribution, they require elevated temperature and pressure and lengthy reaction times to achieve this. The precipitation stage during the reduction process usually involves fast chemical reactions and nucleation kinetics, thus making the mixing process a significant factor in the particle size distribution of the Received: Revised: Accepted: Published: 5375
August 11, 2011 December 4, 2011 February 18, 2012 February 21, 2012 dx.doi.org/10.1021/ie201795u | Ind. Eng. Chem. Res. 2012, 51, 5375−5381
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Article
product.19 A high degree of supersaturation and uniform spatial concentration must be present to produce nanoparticles with narrow size distribution.20 Chen et al.20 confirmed that macromixing is a key factor in ensuring a uniform spatial concentration distribution, while the intensification of micromixing is necessary for high degrees of supersaturation. The use of conventional chemical precipitation techniques through a simple stirring reactor, however, suffers from poor micromixing efficiency. These problems can be mitigated through the use of high-gravity reactive precipitation. In a nutshell, high gravitational mixing works by subjecting the reactants to a high centrifugal force in a rotating packed bed during the mixing phase which greatly increases mass transfer rate as well as macro- and micromixing intensities. In this work, we describe the production of silver nanoparticles using the high-gravitational reactive precipitation method through a rotating packed bed reactor and present our findings on the significance and effects of various operating parameters on the sample particle size and recovery yield. To the best of our knowledge, there have not been any extensive studies on the effects of reactant concentration and operating parameters on the particle size and yield of the silver product for rotating packed bed reactors. Information on the subject would be highly beneficial for the optimization of reaction processes to increase product quality and minimize wastage. Taguchi statistical analysis was conducted to gauge the relative importance of each parameter and to obtain the optimal concentration and feed flow rate of reactants and packed bed rotation speed. To determine the particle size and silver concentration of the synthesized samples, dynamic light scattering (DLS) and inductively coupled plasma mass spectrometry (ICP) were used respectively. X-ray diffraction (XRD), UV−vis spectroscopy, and transmission electron microscopy (TEM) imaging were used for further characterization of the produced nanoparticles.
Aldrich) dissolved in 1 L of distilled water. The starch-water mixture was first heated to 85 °C to disperse the starch granules and allowed to cool before the addition of AgNO3. Tank B holds 0.07 M of sodium hydroxide, NaOH (Sigma Aldrich), and a predefined concentration of glucose (Nacalai Tesque) in 1 L of distilled water. The contents of the two tanks, under constant stirring, were fed into the reactor with their respective flow rates regulated by a flowmeter. The outlet feed was directed into Tank A in a recycling setup. After the content in Tank B was exhausted, the reactor was kept in operation for another 5 min. The pH of Tank A was recorded with a pH meter throughout the operation. To obtain the silver nanoparticles in powder form, the slurry is mixed with acetone at 1:1 proportion before vacuumfiltration through a polytetrafluoroethylene (PTFE) membrane filter (Chromtech, pore size 0.2 μm). The filter cake was dried in an oven at 110 °C overnight to remove excess moisture. Recovered silver nanoparticles were imaged using transmission electron microscopy (TEM) (JEOL JEM-3100F). The extent of the silver crystallization in the product was studied using X-ray diffraction (XRD) (Rigaku X-ray diffractometer) and UV−vis spectroscopy (Jasco V-670 spectrophotometer). The retrieved silver powder samples were ground onto a quartz slide for XRD analysis. The diffraction angle range 2Θ in the XRD study was measured from 20 to 90°. Silver samples used in the UV−vis analysis were diluted with distilled water to about 1 vol. %. The wavelength of interest for the UV−vis spectroscopy was defined from 300 to 800 nm. Silver nanoparticle size was measured using the dynamic light scattering (DLS) method (Malvern Zetasizer Nano-ZS). Prior to analysis, all samples were diluted in distilled water (from 0.1 and up to 1 vol. %) and sonicated for 2 min to remove air bubbles before insertion into square-aperture quartz glass cells. The dispersant viscosity and refractive index were set at 0.8872 cP and 1.330 respectively, and the cell temperature was equilibrated at 25 °C for 120 s. The silver nanoparticle yield was quantified using the inductively coupled plasma (ICP) mass spectrometry (GBC ICP-OEP). Five separate aliquots were extracted from each prepared sample to obtain the mean silver concentration. All samples were syringe-filtered and diluted with deionized water to 1 vol. % prior to ICP analysis. Argon flow rate was kept at 0.30 L/min throughout the operation.
2. MATERIALS AND METHODS Silver nanoparticles were prepared using the high-gravitational precipitation method through a rotating packed bed reactor. The experimental setup is as shown in Figure 1. Tank A contains 0.01 M of silver nitrate, AgNO3 (Nacalai Tesque), and a predefined weight proportion of soluble potato starch (Sigma
3. RESULTS AND DISCUSSION Silver nanoparticles were synthesized using the chemical precipitation method through the rotating packed bed reactor. The design of the packed bed reaction chamber is shown in Figure 2. The solutions fed into the packed bed are pushed through the wire mesh by the centrifugal force and sheared into tiny droplets, threads, and thin films under the high-gravity environment. The intense mixing and high mass transfer that occur from this motion during the reaction phase results in particle sizes that are smaller and more uniformly distributed and greatly reduces reaction time. Unlike other synthetic methods such as the synthesis of silver nanoparticles through microwave irradiation, the rotating packed bed reactor is scalable for large-volume industrial production. The rotating packed bed reactor used in this work has a relatively low hourly power consumption of approximately 750 Wh. In our experiments, the complete formation of the silver nanoparticles using the rotating packed bed reactor at room
Figure 1. Experimental setup of Ag nanoparticles preparation using a high gravity rotating packed bed reactor. (1) Tank A, (2) Tank B, (3) pump, (4) flowmeter, (5) fluid feeder, (6) rotating packed bed, (7) acrylic housing, (8) motor, and (9) pH meter. 5376
dx.doi.org/10.1021/ie201795u | Ind. Eng. Chem. Res. 2012, 51, 5375−5381
Industrial & Engineering Chemistry Research
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however, nullifies its function as a protecting agent. Hence, to fully disperse the starch particles in water, the soluble starch was heated in distilled water to 85 °C under vigorous stirring and allowed to cool before the addition of AgNO3. Besides heat application, we found that the presence of sufficiently strong stirring motion was crucial in preventing the agglomeration of starch granules, with visible starch flakes forming in the solution otherwise. UV−vis spectroscopy of samples prepared using insufficiently dispersed starch solutions in Figure 5 showed that the nonheated starch solution spectrum displayed weak absorbance at 420 nm and a slight peak bump at 350 nm which indicated an incomplete formation of silver nanoparticles as well as the presence of aggregation. In contrast, the spectrum of the silver sample prepared using a fully dispersed starch solution resulted in high silver nanoparticle concentrations with limited, if any, aggregation in the measured sample, as characterized by a strong and pronounced absorbance peak at 410 nm and minimal background absorbance. Also, in our preliminary experiments, we found that the use of regular starch was not as effective in minimizing the agglomeration of reduced silver particles compared to soluble starch due to its relative lack of dispersibility in water. This was evident from the noticeable opacity of the starch-water dispersion after heat application, which was in contrast to the clear solution obtained from the use of soluble starch. Silver nanoparticles are commonly used in electronic, catalytic, and antimicrobial applications. In either of these cases, it is highly beneficial for particle diameters to be as small and narrowly distributed as possible as nanoparticles with smaller diameters tend to exhibit improvements in their inherent qualities. For example, smaller silver nanoparticles showed improved antimicrobial functions due to its larger surface area as well as the greater ease with which it enters the cellular nucleus.21,22 The reduction of the silver size also resulted in enhanced catalytic activity due to the larger potential difference between the silver and the dye.4 Besides the silver nanoparticle size, information on the overall silver yield obtainable from the expanded silver nitrate in the reaction would be beneficial for process optimization. The silver yield percentage is defined as the percentage ratio of the actual to theoretical production volume of silver and is represented in eq 1
Figure 2. (Clockwise from left) Plan-view schematic diagram; half-cut view; and exploded view of the rotating packed bed reaction chamber: (1) acrylic housing, (2) rotating wire-mesh packed bed, (3) reactant inlet feed, and (4) reactant outlet feed. − − → Mixed reactants’ outward radial flow.
temperature occurred within 5 min. The slurry product recovered after 5 min was stirred for a further 30 min before taken for yield measurement. As there was no noticeable increase in silver product even after 30 min of stirring, it was concluded that the total reaction time was around 5 min. The pH measurement during the mixing process showed a stabilization of pH to 12.5 after approximately 2.5 min. XRD analysis was conducted to ascertain the presence of silver in the prepared nanoparticles. As seen in Figure 3, the
silver yield = actual amount of silver produced (mg·mL−1) theoretically maximum possible amount of silver (mg·mL−1)
100%
(1)
Figure 3. XRD peaks of high-gravity prepared silver nanoparticles.
As it was in our interest to optimize the synthetic process to produce silver nanoparticles with the smallest particle size and highest yield possible, the factors of several operating parameters needed to be taken into account. To this end, the effects of starch-AgNO3 ratio, glucose concentration, reactant feed flow-rate ratio, and packed bed rotation speed on the silver yield and particle size were investigated using the Taguchi statistical analysis. Following this, an optimum set of parameters was used to tailor the product of the synthetic process to the desired physical characteristics. In this study, we assigned four different values for each examined parameter as shown in Table 1. Concentrations of AgNO3 and NaOH were fixed at 0.01 and 0.07 M as under these conditions, intensive mixing and uniform supersaturation which promote small particle sizes occur at higher levels.23 For
XRD crystallinity peaks at (1 1 1), (2 0 0), (2 2 0), and (3 1 1) correspond with that of silver and indicates the well-formed crystallinity of the produced samples. TEM images shown in Figure 4 provide an illustration of the morphology and general size of the produced silver nanoparticles. As can be seen from the images, there is relatively minimal agglomeration between the synthesized nanoparticles. Also from the images, the approximate average size of the synthesized nanoparticles is estimated to be between 20−25 nm. For a more precise measurement of silver nanoparticle sizes, DLS analysis was conducted as will be further elaborated. In our experiments, starch was used as a protecting agent to minimize the agglomeration of silver particles during the reduction process. The inherent insolubility of starch in water, 5377
dx.doi.org/10.1021/ie201795u | Ind. Eng. Chem. Res. 2012, 51, 5375−5381
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Figure 4. TEM images of silver nanoparticles synthesized using the rotating packed bed reactor.
Table 2. Parameters of the Respective Runs Conducted for the Taguchi Analysis
Figure 5. UV−vis spectrum of high-gravity prepared silver nanoparticles.
Table 1. Parameters Used for Taguchi Statistical Analysis description
1
2
3
4
starch/AgNO3 ratio glucose concentration (M) LA/LB flow rate ratio rotation speed (rpm)
0.5 0.01 0.5 500
1.0 0.02 1.0 800
1.5 0.05 1.5 1000
2.0 0.06 2.0 1500
(2)
n ⎞ ⎛ S 1 1 = −10log⎜⎜ ·∑ 2 ⎟⎟ N ⎝ n 1 yi ⎠
(3)
starch/ AgNO3 ratio
glucose concentration (M)
LA/LB flow rate ratio
rotation speed (rpm)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
0.5 0.5 0.5 0.5 1.0 1.0 1.0 1.0 1.5 1.5 1.5 1.5 2.0 2.0 2.0 2.0
0.01 0.02 0.05 0.06 0.01 0.02 0.05 0.06 0.01 0.02 0.05 0.06 0.01 0.02 0.05 0.06
0.5 1.0 1.5 2.0 1.0 0.5 2.0 1.5 1.5 2.0 0.5 1.0 2.0 1.5 1.0 0.5
500 800 1000 1500 1000 1500 500 800 1500 1000 800 500 800 500 1500 1000
signal-to-noise ratios for particle sizes, while eq 3 was used for product yield. Table 3 shows the resulting particle size and yield for each run that was prepared according to the aforementioned parameters. As can be seen, with the exception of runs 11 and 16, the mean silver particle sizes were within the 25−40 nm range with narrow polydispersity (
