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Synthesis of Ag-Cu and Ag-Cu2O alloy nanoparticles using a seed-mediated polyol process, thermodynamic and kinetic aspects
Accepted Manuscript Synthesis of Ag-Cu and Ag-Cu2O alloy nanoparticles using a seed-mediated polyol process, thermodynamic and kinetic aspects Yasaman Niknafs, Amirmostafa Amirjani, Pirooz Marashi, Davoud Haghshenas Fatmehsari PII:
S0254-0584(16)30972-5
DOI:
10.1016/j.matchemphys.2016.12.060
Reference:
MAC 19391
To appear in:
Materials Chemistry and Physics
Received Date: 7 June 2016 Revised Date:
11 November 2016
Accepted Date: 28 December 2016
Please cite this article as: Y. Niknafs, A. Amirjani, P. Marashi, D.H. Fatmehsari, Synthesis of Ag-Cu and Ag-Cu2O alloy nanoparticles using a seed-mediated polyol process, thermodynamic and kinetic aspects, Materials Chemistry and Physics (2017), doi: 10.1016/j.matchemphys.2016.12.060. 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.
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Synthesis of Ag− −Cu and Ag− −Cu2O alloy nanoparticles using a seedmediated polyol process, thermodynamic and kinetic aspects
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Yasaman Niknafs, Amirmostafa Amirjani, Pirooz Marashi ∗, Davoud Haghshenas Fatmehsari
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Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran.
Abstract
In this paper, Ag, Ag−Cu and Ag−Cu2O nanoparticles were synthesized using a modified polyol method. Size, shape and composition of the obtained nanostructures were effectively controlled
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by adjusting the kinetic and thermodynamic conditions. Response surface methodology was employed to consider the interaction of parameters and to develop a polynomial equation for predicting the size of the silver nanoparticles. The precisely controlled silver nanoaprticles were
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used as the seeds for the formation of alloyed nanoparticles. By manipulating the involved parameters, both spherical and cubical Ag−Cu and Ag−Cu2O nanostructures are obtainable in the
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size range of 90−100 nm. The morphological, optical and compositional characteristics of the obtained nanostructures were studied using SEM, FE−SEM, UV−Vis, EDS and XRD. Keywords: Silver nanocube; Silver nanoparticles; Silver/Copper alloy nanostructures; Polyol method
∗
Corresponding author at Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran. Email: [email protected]
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1- Introduction Over the past 30 years, synthesis of metallic nanostructures with various
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shapes/sizes has been extensively studied not only for scientific curiosity, but also due to their size and shape–dependant properties. Among them, silver nanostructures have been in the center of attention owing to their extensive
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applications in electronics, optics, biological−labeling and sensing [1−6].
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Generally, silver nanostructures with different shapes and sizes (triangles, pyramids, rods, wires, disks and stars [7−10]) have been derived from the various chemical and physical methods.
Polyol method is a well−known method for preparing colloidal Ag as well as
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less−reducible metals such as Cu, Pb and Ni [11, 12]. In addition to the ability of polyols for dissolving many precursor salts, their temperature−dependent reducing
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power is the main advantage of this method. There is a wide range of nanostructures obtained by polyol method with different
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composition, shape and structure and their distinct applications. Jia et al. [13] used a modified−polyol method for obtaining large scale and multiple crystalline silver nanowires with uniform diameters. Jeon et al. [14] produced silver nanocubes at high yield by tuning the etching effect of O2/Cl- in a polyol process. Different
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silver nanostructures were synthesized by adjusting the stirring−time in the presence of a short−chain polyvinylpyrrolidone (PVP) by Gomez-Acosta et al [15].
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Polyol method was also exploited to prepare core−shell or bimetallic nanostructures as the new generation of nanostructured materials. Coreshell/alloyed nanostructures exhibit improved physical and chemical properties,
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better stability and better protection of core material [16, 17]. Carroll et al. [12]
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synthesized Cu−Ni alloy nanoparticles by the polyol method. Ag−Cu alloy was also produced using the polyol method by Tsuji and coworkers [18]. Mono−sized Au−Fe alloy nanoparticles were synthesized by Liu et al. [19] to achieve the optical functionality of Au together with the magnetic properties of iron.
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One can also find several reports for preparation of various bimetallic nanostructures such as Ni−Pd [20], Ni−Pt [21] and, Au−Ag [22]. However, there
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are only a few reports in the case of Ag−Cu bimetallic nanostructures [18, 23]. The main obstacles in the way of preparing Ag−Cu bimetallic nanostructures are the
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large difference in their lattice constants (0.409 nm for Ag and 0.361 nm for Cu), the simultaneous reduction of Cu and Ag is difficult due to their different redox potentials and the instability of Cu in aqueous media. In order to overcome these issues, the thermodynamic and kinetic aspects governing the synthesis system can provide effective remedies. All of the above mentioned researches can be seen from two distinct viewpoints; thermodynamics 3
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justifies the formation of a nanostructured product as the most stable state while the product with the lower energy barrier (activation energy) is kinetically formed
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faster. There are several studies that discussed the thermodynamic aspects of evolution and growth of silver/bimetallic silver nanostructures [24, 25]; It is worthy of note
considerations is essential but not enough.
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that for the prediction of final structure in a nanosynthesis process thermodynamic
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In this study, we have successfully synthesized and controlled the size of silver nanoparticles via polyol process. The initially formed silver nuclei were used as the seeds for the formation of Ag−Cu nanostructures with controlled stoichiometry.
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Optical properties of pure silver nanoparticles and Ag−Cu alloyed nanoparticles were studied based on UV−Vis spectroscopy. The mechanisms of size controlling
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and alloying of the bi−metallic nanostructures are elucidated based on the
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thermodynamic and kinetic considerations.
2- Materials and methods At first, a summary of the whole experimental work is as follows: size−controlled silver nanoparticles were obtained by adjusting three parameters (synthesis duration, temperature and amount of ammonia). After successful design of
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experiments, the optimal range of factors for obtaining silver nanoparticles at minimum size was acquired. Then, the as−synthesized silver nanoparticles were
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used as seeds for the preparation of different Ag−Cu alloyed nanostructures. Further details about experimental procedures can be found below.
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2.1 Reagents and solutions
Silver nitrate (AgNO3) and Copper nitrate trihydrate (Cu(NO3)2.3H2O), as the
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precursors, were purchased from Scharlau (Spain); Ethylene glycol (EG) and polyvinylpyrrolidone (PVP−K30) were purchased from Sigma−Aldrich (USA). Ammonium hydroxide was prepared from Merck (Germany). The chemicals were
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used without further purification.
2.2 Synthesis procedure for silver nanoaprticles
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Silver nanoparticles were produced by Polyol method. First, 1.7 grams of PVP was dissolved in 10ml of EG and was heated to 160 °C with appropriate stirring rate.
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Then, AgNO3/EG (0.01M) was added to the above solution with the rate of 0.5 ml/min. During the experiment, specific amount of ammonia was added drop−wise to the system in order to control the size of silver nanoparticles. The final solution was held at different temperatures and also different reaction times to obtain the favorable reaction conditions. Finally, the solution was left to cool down to room temperature before centrifuging. 5
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2.3. Design of experiments Eighteen experimental runs consisting of 8−star points (star distance was 0) and 4
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center points were generated with 3 factors and 3 levels by the principle of RSM using MINITAB Release 15. A central composite design (CCD) with multiple linear regressions was used to estimate the model coefficient of the selected
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factors, which was believed to influence the size of the silver nanoparticles. Each
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factor was set at its high level (+1), low level (−1) and medium level (0). The design involved three factors: concentration of ammonia, reaction time and temperature; also, the response was the size of the silver nanoparticles. The levels for these three factors, according to the CCD, and their responses are listed in
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Tables 1 and 2. The experiments were carried out in two replicates and the results for the response were reported as a mean value in a randomized order to avoid systematic bias. Finally, a quadratic polynomial regression model (Eq. (1)) was
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applied to estimate and predict the response value over a range of input factors’
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values:
Y = b + b X +
b X
+ b X X (1)
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where Y is the dependant response variable (i.e. size of the silver nanoaprticles), b0 is the intercept term, bi, bii, and bij are the measures of the effect of variable Xi, Xi2
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and XiXj, respectively. Xi and Xj represent the independent variables. The variable XiXj represents the first order interaction between Xi and Xj (i < j). The purposes of considering a model such as Eq. (1) are:
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1. Estimating a relationship between Y and Xi that can be used to predict response value (Y) for a given setting of the control variables.
Xi.
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2. Determination of the significance of the factors whose levels are represented by
3. Estimation of the optimum settings of Xi that result in the minimum response
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over a certain region of interest.
The analysis of variance (ANOVA) for quadratic model was performed at 10% confidence level (P−value < 0.1). The significance and the magnitude of the effect
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estimations for each variable and all their possible linear and quadratic interactions
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were also determined. At last, the model was used to predict main effective factors in polyol synthesis of silver nanoparticles.
2.4 Synthesis procedure for silver/copper bi−metallic nanoparticles
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The mono−metallic silver nanoparticles were produced at optimum conditions and then, copper nitrate (0.2 M) was added to achieve Ag−Cu nanoparticles. In order to
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shed more light on the mechanisms of Ag−Cu formation, the effects of reaction time, copper nitrate concentration and amount of ammonia were evaluated.
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2.5 Characterization
For estimating the size of synthesized silver nanoparticles, scanning electron
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microscope (SEM, Philips XL30, and 25 kV), field emission scanning electron microscope (FESEM) and UV−Vis spectrophotometer (Shimadzu 160A) were used. X-ray diffraction (XRD) patterns of prepared nanostructures were obtained
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using a Philips PW 1140 X-ray diffraction unit. 3- Results and discussions
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3.1 Structural, morphological and optical study
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Structural study of the silver nanoparticles was done based on XRD results. Four characteristic peaks of silver at 38.3, 44.4, 64.5, and 77.4 degrees (See Fig.1a) corresponding to the (111), (200), (220), and (311) planes of the face-centred cubic (FCC) Ag nanoaprticles (JCPDS File No. 04-0783) were observed. Surface plasmon band of Ag nanoparticles was studied by UV-Vis spectrophotometer. The characteristic surface plasmon band of silver nanoparticles at 400 nm is clearly
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seen in Fig.1b. SEM image of a typical synthesized silver nanoparticle is depicted in Fig.1c indicating the mono−dispersed silver nanoparticles around 60−70 nm
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(test duration was 1hr). Morphological and optical studies were carried out for the samples proposed by design of experiments and the responses and interactions of parameters were
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discussed in following sections. The complete data regarding the nanoparticles’
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size are available in supplementary information (Table S1 and Fig. S1).
3.2 Model fitting
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The regression coefficient values are presented in Table 3. As it is shown, some of the linear, quadratic and interaction terms are significant and thus, a second order polynomial for data expressing is vital. By the help of statistical analysis and
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considering the regression coefficients (Table 3), a polynomial regression model
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equation based on un−coded coefficients that fits 95.7% of the variation in the data is presented as follows:
Nanoparticles’ size = 1358 − 75.25 − 124.3V − 16.32T + 0.05T·T + 0.59t·T (2)
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The low values of P determined for the regression (P < 0.001) together with the insignificant lack of fit of the model (P > 0.1), revealed the suitability of the model
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(Table 4). Moreover, the predicted nanoparticles’ size (the Eq. (2)) was plotted versus experimental data (see supplementary information Fig. S2) indicating the
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3.3 Controlling the size of silver nanoparticles
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proper linear distribution and the adequacy of the model.
By manipulating the experimental conditions one can tune the size of silver nanoparticles in a precise manner. Based on the regression coefficients presented in Table 3 (coded values), the level of importance of parameters can be evaluated.
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The reaction temperature and the time of the synthesis process are the two most important parameters in the polyol process. Our results suggest that the size of
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silver nanoparticles can be tuned even without addition of any reagents. Where interaction between factors is statistically significant, surface plots give useful
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information about the effect of a factor on the response. As it is shown in Fig. 2, when the temperature is at its minimum level (140 °C), increasing the reaction time has no significant effect on the particle size. On the other hand, when the temperature is high enough (>170°C), only at short reaction time, small silver nanoparticles are attainable.
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The optical study of nanoparticles solution is a simple and useful technique for in−situ characterization. According to Mie theory, the extinction cross−section of a
nanostructures in supplementary information):
*+,* -. /0 /4 (5) 3 ; (.) = 2 [/4 (5) + */0 + +7,* -* /*0 ⁄82* ]* + /4 (5)*
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&'()
./*
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spherical particle can be represented as [26] (see optical properties of
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It is obvious that the extinction cross−section of the silver nanoparticles strongly depends on the size of particles and their dielectric constants. Assuming constant dielectric properties, the size of nanoparticles change the optical response of the system.
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Optical responses of silver nanoaprticles with specific sizes were collected using a simple UV−Vis spectrophotometer and the results are depicted in Fig. 3. As it can
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be observed in Fig. 3, the larger particle size results in the higher wavelength of
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maximum extinction which is in agreement with the Mie theory (Equation 3).
3.4 Preparation of Ag-Cu alloyed nanostructures Addition of copper nitrate solution (0.2 M) to the as−synthesized silver nanoparticles (under the optimum conditions) led to the formation of Ag−Cu
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alloyed nanostructures. However, the experiments were conducted in two conditions: a) in the presence of 0.1 mL ammonia and b) in the absence of
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ammonia solution. Surprisingly, the obtained nanostructures were different both in morphology and composition. As it can be seen in Figure 4, in case (a) the pure silver together with copper oxide (Cu2O) nanocubes were produced, while in case
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(b), spherical silver and copper nanoparticles were obtained. (for further
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information on EDS analysis, refer to supplementary information). As mentioned above, the addition of ammonia to the system results in the formation of Ag(NH3)2+ which would kinetically control the formation of Ag0, due to the difference in the reduction potential of Ag+ and Ag(NH3)2+. The decrease in
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the rate of nucleation promotes the precipitation of Ag ions in the active sites and also provides oxidation state in the system which results in the formation of Cu2O
silver).
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nanostructures (Gibbs free energy for oxidation of copper is lower than that of
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These results are consistent with previous reports on controlling the rate of nucleation for tuning the size and shape of nanostructures [27, 28]. 3.4.1 Effect of time
It is worthy of note that the alloyed Ag−Cu nanoparticles are the dominant product in other experiments conducted in case (b). In order to study the effect of time on 12
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the formation of Ag−Cu alloyed nanoparticles, synthesis procedure was repeated at different time durations. X-ray diffraction was used to monitor the silver structural
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changes due to the addition of copper. Samples were extracted from the synthesis batch at different time intervals (30, 60, 90 and 180 minutes after the addition of copper) and XRD patterns were analyzed. XRD patterns of samples are presented
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in Figure 5 in which the changes in peak positions (compared to standard
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positions) are clear. In order to determine the location of each peak in the XRD pattern of alloyed samples (compared to the pure metallic structures), a Gaussian function over XRD peak positions was employed by applying Origin software (version 8.1). (see fitting the Gaussian function to XRD data in supplementary
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information). The results of model fitting procedure presented in Figure S3, reveals that by increasing the reaction time, a slight shift to the higher values occurs. These results are in agreement with previous findings and implies the substitution of the
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silver atoms with copper atoms which results in lattice contraction [29].
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3.4.2 Elucidation of the involved mechanisms In this work, at first we successfully tuned the size of silver nano particles by controlling the thermodynamic and kinetic conditions of the synthesis system. In other words, manipulating the reaction time and introducing an intermediate compound ([Ag(NH3)2]+) resulted in production of various sized silver
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nanoparticles due to their minimum energy barriers of the new pathways. These results are consistent with previous studies where the shape and size of a
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nanostructure was kinetically controlled [24, 27 and 29]. Also, controlling the temperature of the process led to the production of nanoparticles with distinct sizes because they are formed as the most stable products. This is the main difference
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between thermodynamically or kinetically controlled syntheses whether a product forms because it is the most stable form or because its pathway has the lowest
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energy barrier. The prepared silver nanoparticles were used as seeds for the formation of Ag/Cu nanostructures (Ag−Cu2O or Ag−Cu). Again, by manipulating the synthesis parameters, we synthesized Ag/Cu nanostructures in the form of
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cube, instead of spherical, particles. We have designed a pathway in which the formation of cubic nanostructure (Pʹ) had lower energy barrier compared to spherical particles (P); therefore, alloyed nanostructures in the form of cube were
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4. Conclusions
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the final products (see Figure 6).
The present study reported a facile approach for the preparation of size controlled silver nanoparticles over the range of 40−150 nm. By the use of as−synthesized silver nanoparticles as the seeds, alloyed bimetallic nanostructures of Ag−Cu and Ag−Cu2O were achieved. By plotting the extinction spectra of different sizes of
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silver nanoparticles, a simple approach was proposed for predicting size of the colloidal silver using λmax. The addition of ammonia as a complexing agent
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resulted in the different shapes (cube and sphere) and compositions (Ag−Cu and Ag−Cu2O) of nanostructures. The effect of reaction time on the alloying of the silver nanostructured with copper and the related lattice contraction was studied
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using XRD and fitting the Gaussian function. A discussion was made on the
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thermodynamic and kinetic aspects of the synthesis process which provides a parametrical manipulation for precise tuning the products and also helps preparing new nanostructures with desired applications.
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References
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[2] A. Amirjani, M. Bagheri, M. Heydari, S. Hesaraki, Sens. Actuat. B, 2016, 227, pp 373–382.
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[3] C. Y. Loo, R. Rohanizadeh, P. M. Young, D. Traini, R. Cavaliere, C. Whitchurch, W-H. Lee, J. Agric. Food Chem., 2016, 64 (12), pp 2513–2522. [4] P. Sutradhar, M. Saha, J. Phys. Chem. C, 2016, 120 (16), pp 8941–8949. [5] J. Tao, P. Zhao, J. Zheng, C. Wu, M. Shi, J. Li, Y. Li, R. Yang, Chem. Commun., 2015, 51, pp 15704−15707. [6] A. Amirjani, M. Bagheri, M. Heydari, S. Hesaraki, Nanotechnology, 2016, 27(37), pp 375503–375511.
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[7] Y. Yang, S. Matsubara, L. Xiong, T. Hayakawa, M. Nogami, J. Phys. Chem. C, 2007, 111(26), pp 9095−9104. [8] C. J. Murphy, Science, 2002, 298, pp 2139−2141.
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[9] A. Amirjani, P. Marashi, D. Fatmehsari, Int. Nano Lett., 2014, 4(108), pp 1−5. [10] A. Amirjani, D. Fatmehsari, P. Marashi, J. Exp. Nanosci. 2015, 10 (18), pp 1387−1400
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[15] A. Gomez-Acosta, A. Manzano-Ramirez, E. J. Lopez-Naranjo, L. M. Apatiga, R. Herrera-Basurto, E. M. Rivera-Munoz, Mater. Lett, 2015, 138, pp 167–170. [16] R. G. Chaudhuri, S. Paria, Chem. Rev., 2012, 112, pp 2373–2433.
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[17] I. V. Sevonkaev, D. Herein, G. Jeske, D. V. Goia, Nanoscale, 2014, 6, pp 9614–9617.
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[18] M. Tsuji, S. Hikino, R. Tanabe, M. Matsunaga, Y. Sano, Cryst. Eng. Comm, 2010, 12, pp 3900−3908. [19] H. L. Liu, J. H. Wu, J. H. Min, Y. K. Kim, J. Appl. Phys., 2008, 103, 07D529. [20] S. Maity and M. Eswaramoorthy, J. Mater. Chem. A, 2016, 4, pp 3233−3237. [21] B. Zhang, Y. Niu, J. Xu, X. Pan, C-M. Chen, W. Shi, M. G. Willinger, R. Schlogl, D. S. Su, Chem. Comm, 2016, 52, pp 3927−3930. [22] M. M. Kumari, J. Jacob, D. Philip, Spectrochim. Acta. A: Molecular and Biomolecular Spectroscopy, 2015, 137, pp 185−192. 16
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[25] A. Amirjani, P. Marashi, D. Fatmehsari, Colloids. Surf. A, 2014, 444, pp 33−39. [26] M. Rycenga, C. M. Cobley, J. Zeng, W. Li, C. H. Moran, Q. Zhang, D. Qin, Y. Xia, Chem. Rev., 2011, 111, pp 3669−3712.
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[28] H. Jiang, K. Moon, C. P. Wong, Adv. Pack. Mater.: Processes, Properties and Interfaces, 2005, pp.173–177.
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[29] Y. Wang, J. He, C. Liu, W. H. Chong, H. Chen, Angew. Chem. Int. Ed., 2015, 54, pp 2022−2051.
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Figure1. a) XRD pattern of silver nanoparticles, b) UV-Vis spectra of colloidal silver nanoparticles and c) SEM image of silver nanoparticles (the scale bar is 500 nm). Figure2. Surface plot of particle size with respect to the time and temperature of the reaction. The insets show a sample from each region.
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Figure3. Extinction spectra of silver nanoaprticles with different size. Inset shows the linear relationship of particle size versus wavelength of maximum extinction.
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Figure4. XRD and SEM results of obtained nanostructures in cases a (in the presence of ammonia) and b (in the absence of ammonia solution) with weight percent distribution of Ag and Cu in alloyed nanostructures. Figure5. XRD pattern of obtained nanostructures under different reaction times of 30, 60, 90 and 180 minutes.
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Figure6. Schematic of the two involved mechanisms for controlling the size and morphology of nanostructures in a typical synthesis.
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Table1. Experimental ranges for the level of independent variables in response surface study.
Unit
Level -1
1
T
140
160
180
hour
t
1
2.5
4
ml
VAmmonia
0
0.1
0.2
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0
°C
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Reaction temperature Reaction time Concentration of Ammonia
Notation
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Factors
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Table2. Composition of various experiments in CCD design for minimizing the size of silver nanoaprticles.
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Ammonia (ml) 0 0 0.2 0.2 0 0 0.2 0.2 0.1 0.1 0 0.2 0.1 0.1 0.1 0.1 0.1 0.1
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Time (h) 1 4 1 4 1 4 1 4 1 4 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5
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Temperature ( ̊C) 140 140 140 140 180 180 180 180 160 160 160 160 140 180 160 160 160 160
Run order 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
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Table 3.Values of regression coefficients calculated for the synthesis’s factors Independent Regression coefficient Regression coefficient Standard T−value
60.06
1358
t
14.20
-75.27
Vammonia
-6.500
-124.3
T
24.80
-16.32
Constant Linear
<0.000
0.001
2.743
-2.370
0.045
2.743
9.042
<0.000
-1.720
5.269
-0.734
0.484
663.1
5.269
1.258
0.244
0.05
5.269
3.821
0.005
-2.000
-13.33
3.067
-0.652
0.533
17.75
0.59
3.067
5.788
<0.000
-0.500
-0.25
3.067
-0.163
0.875
Vammonia .Vammonia
6.631
T.T
20.13
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Interactive
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-3.869
Vammonia .T
17.60
5.177
t.t
t.T
3.412
2.743
Quadratic
Vammonia .t
error
(un−coded values)
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(coded values)
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factor
P−value
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Table 4.ANOVA table
freedom
squares
Total
17
13955
Regression
9
13353
1483
Residual error
8
601.8
75.23
Lack of fit
5
287.1
57.42
Pure error
3
314.8
104.9
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95.69
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R2
Mean squares
F−value
P−value
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Sum of
19.72
<0.001
0.55
0.741
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Degrees of
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Highlights: • Synthesis of Ag, Ag−Cu and Ag−Cu2O alloy nanostructures.
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• RSM was successfully employed for predicting the size of the AgNPs.
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• Size and composition tuning by adjusting the kinetic and thermodynamic conditions.
H1
S0254-0584(16)30972-5
DOI:
10.1016/j.matchemphys.2016.12.060
Reference:
MAC 19391
To appear in:
Materials Chemistry and Physics
Received Date: 7 June 2016 Revised Date:
11 November 2016
Accepted Date: 28 December 2016
Please cite this article as: Y. Niknafs, A. Amirjani, P. Marashi, D.H. Fatmehsari, Synthesis of Ag-Cu and Ag-Cu2O alloy nanoparticles using a seed-mediated polyol process, thermodynamic and kinetic aspects, Materials Chemistry and Physics (2017), doi: 10.1016/j.matchemphys.2016.12.060. 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.
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Synthesis of Ag− −Cu and Ag− −Cu2O alloy nanoparticles using a seedmediated polyol process, thermodynamic and kinetic aspects
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Yasaman Niknafs, Amirmostafa Amirjani, Pirooz Marashi ∗, Davoud Haghshenas Fatmehsari
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Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran.
Abstract
In this paper, Ag, Ag−Cu and Ag−Cu2O nanoparticles were synthesized using a modified polyol method. Size, shape and composition of the obtained nanostructures were effectively controlled
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by adjusting the kinetic and thermodynamic conditions. Response surface methodology was employed to consider the interaction of parameters and to develop a polynomial equation for predicting the size of the silver nanoparticles. The precisely controlled silver nanoaprticles were
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used as the seeds for the formation of alloyed nanoparticles. By manipulating the involved parameters, both spherical and cubical Ag−Cu and Ag−Cu2O nanostructures are obtainable in the
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size range of 90−100 nm. The morphological, optical and compositional characteristics of the obtained nanostructures were studied using SEM, FE−SEM, UV−Vis, EDS and XRD. Keywords: Silver nanocube; Silver nanoparticles; Silver/Copper alloy nanostructures; Polyol method
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Corresponding author at Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran, Iran. Email: [email protected]
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1- Introduction Over the past 30 years, synthesis of metallic nanostructures with various
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shapes/sizes has been extensively studied not only for scientific curiosity, but also due to their size and shape–dependant properties. Among them, silver nanostructures have been in the center of attention owing to their extensive
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applications in electronics, optics, biological−labeling and sensing [1−6].
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Generally, silver nanostructures with different shapes and sizes (triangles, pyramids, rods, wires, disks and stars [7−10]) have been derived from the various chemical and physical methods.
Polyol method is a well−known method for preparing colloidal Ag as well as
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less−reducible metals such as Cu, Pb and Ni [11, 12]. In addition to the ability of polyols for dissolving many precursor salts, their temperature−dependent reducing
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power is the main advantage of this method. There is a wide range of nanostructures obtained by polyol method with different
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composition, shape and structure and their distinct applications. Jia et al. [13] used a modified−polyol method for obtaining large scale and multiple crystalline silver nanowires with uniform diameters. Jeon et al. [14] produced silver nanocubes at high yield by tuning the etching effect of O2/Cl- in a polyol process. Different
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silver nanostructures were synthesized by adjusting the stirring−time in the presence of a short−chain polyvinylpyrrolidone (PVP) by Gomez-Acosta et al [15].
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Polyol method was also exploited to prepare core−shell or bimetallic nanostructures as the new generation of nanostructured materials. Coreshell/alloyed nanostructures exhibit improved physical and chemical properties,
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better stability and better protection of core material [16, 17]. Carroll et al. [12]
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synthesized Cu−Ni alloy nanoparticles by the polyol method. Ag−Cu alloy was also produced using the polyol method by Tsuji and coworkers [18]. Mono−sized Au−Fe alloy nanoparticles were synthesized by Liu et al. [19] to achieve the optical functionality of Au together with the magnetic properties of iron.
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One can also find several reports for preparation of various bimetallic nanostructures such as Ni−Pd [20], Ni−Pt [21] and, Au−Ag [22]. However, there
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are only a few reports in the case of Ag−Cu bimetallic nanostructures [18, 23]. The main obstacles in the way of preparing Ag−Cu bimetallic nanostructures are the
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large difference in their lattice constants (0.409 nm for Ag and 0.361 nm for Cu), the simultaneous reduction of Cu and Ag is difficult due to their different redox potentials and the instability of Cu in aqueous media. In order to overcome these issues, the thermodynamic and kinetic aspects governing the synthesis system can provide effective remedies. All of the above mentioned researches can be seen from two distinct viewpoints; thermodynamics 3
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justifies the formation of a nanostructured product as the most stable state while the product with the lower energy barrier (activation energy) is kinetically formed
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faster. There are several studies that discussed the thermodynamic aspects of evolution and growth of silver/bimetallic silver nanostructures [24, 25]; It is worthy of note
considerations is essential but not enough.
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that for the prediction of final structure in a nanosynthesis process thermodynamic
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In this study, we have successfully synthesized and controlled the size of silver nanoparticles via polyol process. The initially formed silver nuclei were used as the seeds for the formation of Ag−Cu nanostructures with controlled stoichiometry.
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Optical properties of pure silver nanoparticles and Ag−Cu alloyed nanoparticles were studied based on UV−Vis spectroscopy. The mechanisms of size controlling
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and alloying of the bi−metallic nanostructures are elucidated based on the
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thermodynamic and kinetic considerations.
2- Materials and methods At first, a summary of the whole experimental work is as follows: size−controlled silver nanoparticles were obtained by adjusting three parameters (synthesis duration, temperature and amount of ammonia). After successful design of
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experiments, the optimal range of factors for obtaining silver nanoparticles at minimum size was acquired. Then, the as−synthesized silver nanoparticles were
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used as seeds for the preparation of different Ag−Cu alloyed nanostructures. Further details about experimental procedures can be found below.
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2.1 Reagents and solutions
Silver nitrate (AgNO3) and Copper nitrate trihydrate (Cu(NO3)2.3H2O), as the
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precursors, were purchased from Scharlau (Spain); Ethylene glycol (EG) and polyvinylpyrrolidone (PVP−K30) were purchased from Sigma−Aldrich (USA). Ammonium hydroxide was prepared from Merck (Germany). The chemicals were
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used without further purification.
2.2 Synthesis procedure for silver nanoaprticles
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Silver nanoparticles were produced by Polyol method. First, 1.7 grams of PVP was dissolved in 10ml of EG and was heated to 160 °C with appropriate stirring rate.
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Then, AgNO3/EG (0.01M) was added to the above solution with the rate of 0.5 ml/min. During the experiment, specific amount of ammonia was added drop−wise to the system in order to control the size of silver nanoparticles. The final solution was held at different temperatures and also different reaction times to obtain the favorable reaction conditions. Finally, the solution was left to cool down to room temperature before centrifuging. 5
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2.3. Design of experiments Eighteen experimental runs consisting of 8−star points (star distance was 0) and 4
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center points were generated with 3 factors and 3 levels by the principle of RSM using MINITAB Release 15. A central composite design (CCD) with multiple linear regressions was used to estimate the model coefficient of the selected
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factors, which was believed to influence the size of the silver nanoparticles. Each
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factor was set at its high level (+1), low level (−1) and medium level (0). The design involved three factors: concentration of ammonia, reaction time and temperature; also, the response was the size of the silver nanoparticles. The levels for these three factors, according to the CCD, and their responses are listed in
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Tables 1 and 2. The experiments were carried out in two replicates and the results for the response were reported as a mean value in a randomized order to avoid systematic bias. Finally, a quadratic polynomial regression model (Eq. (1)) was
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applied to estimate and predict the response value over a range of input factors’
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values:
Y = b + b X +
b X
+ b X X (1)
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where Y is the dependant response variable (i.e. size of the silver nanoaprticles), b0 is the intercept term, bi, bii, and bij are the measures of the effect of variable Xi, Xi2
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and XiXj, respectively. Xi and Xj represent the independent variables. The variable XiXj represents the first order interaction between Xi and Xj (i < j). The purposes of considering a model such as Eq. (1) are:
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1. Estimating a relationship between Y and Xi that can be used to predict response value (Y) for a given setting of the control variables.
Xi.
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2. Determination of the significance of the factors whose levels are represented by
3. Estimation of the optimum settings of Xi that result in the minimum response
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over a certain region of interest.
The analysis of variance (ANOVA) for quadratic model was performed at 10% confidence level (P−value < 0.1). The significance and the magnitude of the effect
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estimations for each variable and all their possible linear and quadratic interactions
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were also determined. At last, the model was used to predict main effective factors in polyol synthesis of silver nanoparticles.
2.4 Synthesis procedure for silver/copper bi−metallic nanoparticles
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The mono−metallic silver nanoparticles were produced at optimum conditions and then, copper nitrate (0.2 M) was added to achieve Ag−Cu nanoparticles. In order to
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shed more light on the mechanisms of Ag−Cu formation, the effects of reaction time, copper nitrate concentration and amount of ammonia were evaluated.
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2.5 Characterization
For estimating the size of synthesized silver nanoparticles, scanning electron
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microscope (SEM, Philips XL30, and 25 kV), field emission scanning electron microscope (FESEM) and UV−Vis spectrophotometer (Shimadzu 160A) were used. X-ray diffraction (XRD) patterns of prepared nanostructures were obtained
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using a Philips PW 1140 X-ray diffraction unit. 3- Results and discussions
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3.1 Structural, morphological and optical study
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Structural study of the silver nanoparticles was done based on XRD results. Four characteristic peaks of silver at 38.3, 44.4, 64.5, and 77.4 degrees (See Fig.1a) corresponding to the (111), (200), (220), and (311) planes of the face-centred cubic (FCC) Ag nanoaprticles (JCPDS File No. 04-0783) were observed. Surface plasmon band of Ag nanoparticles was studied by UV-Vis spectrophotometer. The characteristic surface plasmon band of silver nanoparticles at 400 nm is clearly
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seen in Fig.1b. SEM image of a typical synthesized silver nanoparticle is depicted in Fig.1c indicating the mono−dispersed silver nanoparticles around 60−70 nm
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(test duration was 1hr). Morphological and optical studies were carried out for the samples proposed by design of experiments and the responses and interactions of parameters were
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discussed in following sections. The complete data regarding the nanoparticles’
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size are available in supplementary information (Table S1 and Fig. S1).
3.2 Model fitting
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The regression coefficient values are presented in Table 3. As it is shown, some of the linear, quadratic and interaction terms are significant and thus, a second order polynomial for data expressing is vital. By the help of statistical analysis and
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considering the regression coefficients (Table 3), a polynomial regression model
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equation based on un−coded coefficients that fits 95.7% of the variation in the data is presented as follows:
Nanoparticles’ size = 1358 − 75.25 − 124.3V − 16.32T + 0.05T·T + 0.59t·T (2)
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The low values of P determined for the regression (P < 0.001) together with the insignificant lack of fit of the model (P > 0.1), revealed the suitability of the model
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(Table 4). Moreover, the predicted nanoparticles’ size (the Eq. (2)) was plotted versus experimental data (see supplementary information Fig. S2) indicating the
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3.3 Controlling the size of silver nanoparticles
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proper linear distribution and the adequacy of the model.
By manipulating the experimental conditions one can tune the size of silver nanoparticles in a precise manner. Based on the regression coefficients presented in Table 3 (coded values), the level of importance of parameters can be evaluated.
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The reaction temperature and the time of the synthesis process are the two most important parameters in the polyol process. Our results suggest that the size of
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silver nanoparticles can be tuned even without addition of any reagents. Where interaction between factors is statistically significant, surface plots give useful
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information about the effect of a factor on the response. As it is shown in Fig. 2, when the temperature is at its minimum level (140 °C), increasing the reaction time has no significant effect on the particle size. On the other hand, when the temperature is high enough (>170°C), only at short reaction time, small silver nanoparticles are attainable.
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The optical study of nanoparticles solution is a simple and useful technique for in−situ characterization. According to Mie theory, the extinction cross−section of a
nanostructures in supplementary information):
*+,* -. /0 /4 (5) 3 ; (.) = 2 [/4 (5) + */0 + +7,* -* /*0 ⁄82* ]* + /4 (5)*
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&'()
./*
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spherical particle can be represented as [26] (see optical properties of
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It is obvious that the extinction cross−section of the silver nanoparticles strongly depends on the size of particles and their dielectric constants. Assuming constant dielectric properties, the size of nanoparticles change the optical response of the system.
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Optical responses of silver nanoaprticles with specific sizes were collected using a simple UV−Vis spectrophotometer and the results are depicted in Fig. 3. As it can
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be observed in Fig. 3, the larger particle size results in the higher wavelength of
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maximum extinction which is in agreement with the Mie theory (Equation 3).
3.4 Preparation of Ag-Cu alloyed nanostructures Addition of copper nitrate solution (0.2 M) to the as−synthesized silver nanoparticles (under the optimum conditions) led to the formation of Ag−Cu
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alloyed nanostructures. However, the experiments were conducted in two conditions: a) in the presence of 0.1 mL ammonia and b) in the absence of
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ammonia solution. Surprisingly, the obtained nanostructures were different both in morphology and composition. As it can be seen in Figure 4, in case (a) the pure silver together with copper oxide (Cu2O) nanocubes were produced, while in case
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(b), spherical silver and copper nanoparticles were obtained. (for further
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information on EDS analysis, refer to supplementary information). As mentioned above, the addition of ammonia to the system results in the formation of Ag(NH3)2+ which would kinetically control the formation of Ag0, due to the difference in the reduction potential of Ag+ and Ag(NH3)2+. The decrease in
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the rate of nucleation promotes the precipitation of Ag ions in the active sites and also provides oxidation state in the system which results in the formation of Cu2O
silver).
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nanostructures (Gibbs free energy for oxidation of copper is lower than that of
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These results are consistent with previous reports on controlling the rate of nucleation for tuning the size and shape of nanostructures [27, 28]. 3.4.1 Effect of time
It is worthy of note that the alloyed Ag−Cu nanoparticles are the dominant product in other experiments conducted in case (b). In order to study the effect of time on 12
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the formation of Ag−Cu alloyed nanoparticles, synthesis procedure was repeated at different time durations. X-ray diffraction was used to monitor the silver structural
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changes due to the addition of copper. Samples were extracted from the synthesis batch at different time intervals (30, 60, 90 and 180 minutes after the addition of copper) and XRD patterns were analyzed. XRD patterns of samples are presented
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in Figure 5 in which the changes in peak positions (compared to standard
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positions) are clear. In order to determine the location of each peak in the XRD pattern of alloyed samples (compared to the pure metallic structures), a Gaussian function over XRD peak positions was employed by applying Origin software (version 8.1). (see fitting the Gaussian function to XRD data in supplementary
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information). The results of model fitting procedure presented in Figure S3, reveals that by increasing the reaction time, a slight shift to the higher values occurs. These results are in agreement with previous findings and implies the substitution of the
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silver atoms with copper atoms which results in lattice contraction [29].
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3.4.2 Elucidation of the involved mechanisms In this work, at first we successfully tuned the size of silver nano particles by controlling the thermodynamic and kinetic conditions of the synthesis system. In other words, manipulating the reaction time and introducing an intermediate compound ([Ag(NH3)2]+) resulted in production of various sized silver
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nanoparticles due to their minimum energy barriers of the new pathways. These results are consistent with previous studies where the shape and size of a
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nanostructure was kinetically controlled [24, 27 and 29]. Also, controlling the temperature of the process led to the production of nanoparticles with distinct sizes because they are formed as the most stable products. This is the main difference
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between thermodynamically or kinetically controlled syntheses whether a product forms because it is the most stable form or because its pathway has the lowest
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energy barrier. The prepared silver nanoparticles were used as seeds for the formation of Ag/Cu nanostructures (Ag−Cu2O or Ag−Cu). Again, by manipulating the synthesis parameters, we synthesized Ag/Cu nanostructures in the form of
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cube, instead of spherical, particles. We have designed a pathway in which the formation of cubic nanostructure (Pʹ) had lower energy barrier compared to spherical particles (P); therefore, alloyed nanostructures in the form of cube were
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4. Conclusions
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the final products (see Figure 6).
The present study reported a facile approach for the preparation of size controlled silver nanoparticles over the range of 40−150 nm. By the use of as−synthesized silver nanoparticles as the seeds, alloyed bimetallic nanostructures of Ag−Cu and Ag−Cu2O were achieved. By plotting the extinction spectra of different sizes of
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silver nanoparticles, a simple approach was proposed for predicting size of the colloidal silver using λmax. The addition of ammonia as a complexing agent
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resulted in the different shapes (cube and sphere) and compositions (Ag−Cu and Ag−Cu2O) of nanostructures. The effect of reaction time on the alloying of the silver nanostructured with copper and the related lattice contraction was studied
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using XRD and fitting the Gaussian function. A discussion was made on the
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thermodynamic and kinetic aspects of the synthesis process which provides a parametrical manipulation for precise tuning the products and also helps preparing new nanostructures with desired applications.
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References
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[2] A. Amirjani, M. Bagheri, M. Heydari, S. Hesaraki, Sens. Actuat. B, 2016, 227, pp 373–382.
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[3] C. Y. Loo, R. Rohanizadeh, P. M. Young, D. Traini, R. Cavaliere, C. Whitchurch, W-H. Lee, J. Agric. Food Chem., 2016, 64 (12), pp 2513–2522. [4] P. Sutradhar, M. Saha, J. Phys. Chem. C, 2016, 120 (16), pp 8941–8949. [5] J. Tao, P. Zhao, J. Zheng, C. Wu, M. Shi, J. Li, Y. Li, R. Yang, Chem. Commun., 2015, 51, pp 15704−15707. [6] A. Amirjani, M. Bagheri, M. Heydari, S. Hesaraki, Nanotechnology, 2016, 27(37), pp 375503–375511.
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[25] A. Amirjani, P. Marashi, D. Fatmehsari, Colloids. Surf. A, 2014, 444, pp 33−39. [26] M. Rycenga, C. M. Cobley, J. Zeng, W. Li, C. H. Moran, Q. Zhang, D. Qin, Y. Xia, Chem. Rev., 2011, 111, pp 3669−3712.
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[28] H. Jiang, K. Moon, C. P. Wong, Adv. Pack. Mater.: Processes, Properties and Interfaces, 2005, pp.173–177.
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[29] Y. Wang, J. He, C. Liu, W. H. Chong, H. Chen, Angew. Chem. Int. Ed., 2015, 54, pp 2022−2051.
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Figure1. a) XRD pattern of silver nanoparticles, b) UV-Vis spectra of colloidal silver nanoparticles and c) SEM image of silver nanoparticles (the scale bar is 500 nm). Figure2. Surface plot of particle size with respect to the time and temperature of the reaction. The insets show a sample from each region.
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Figure3. Extinction spectra of silver nanoaprticles with different size. Inset shows the linear relationship of particle size versus wavelength of maximum extinction.
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Figure4. XRD and SEM results of obtained nanostructures in cases a (in the presence of ammonia) and b (in the absence of ammonia solution) with weight percent distribution of Ag and Cu in alloyed nanostructures. Figure5. XRD pattern of obtained nanostructures under different reaction times of 30, 60, 90 and 180 minutes.
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Figure6. Schematic of the two involved mechanisms for controlling the size and morphology of nanostructures in a typical synthesis.
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Table1. Experimental ranges for the level of independent variables in response surface study.
Unit
Level -1
1
T
140
160
180
hour
t
1
2.5
4
ml
VAmmonia
0
0.1
0.2
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0
°C
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Reaction temperature Reaction time Concentration of Ammonia
Notation
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Factors
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Table2. Composition of various experiments in CCD design for minimizing the size of silver nanoaprticles.
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Ammonia (ml) 0 0 0.2 0.2 0 0 0.2 0.2 0.1 0.1 0 0.2 0.1 0.1 0.1 0.1 0.1 0.1
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Time (h) 1 4 1 4 1 4 1 4 1 4 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5
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Temperature ( ̊C) 140 140 140 140 180 180 180 180 160 160 160 160 140 180 160 160 160 160
Run order 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
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Table 3.Values of regression coefficients calculated for the synthesis’s factors Independent Regression coefficient Regression coefficient Standard T−value
60.06
1358
t
14.20
-75.27
Vammonia
-6.500
-124.3
T
24.80
-16.32
Constant Linear
<0.000
0.001
2.743
-2.370
0.045
2.743
9.042
<0.000
-1.720
5.269
-0.734
0.484
663.1
5.269
1.258
0.244
0.05
5.269
3.821
0.005
-2.000
-13.33
3.067
-0.652
0.533
17.75
0.59
3.067
5.788
<0.000
-0.500
-0.25
3.067
-0.163
0.875
Vammonia .Vammonia
6.631
T.T
20.13
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Interactive
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-3.869
Vammonia .T
17.60
5.177
t.t
t.T
3.412
2.743
Quadratic
Vammonia .t
error
(un−coded values)
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(coded values)
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factor
P−value
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Table 4.ANOVA table
freedom
squares
Total
17
13955
Regression
9
13353
1483
Residual error
8
601.8
75.23
Lack of fit
5
287.1
57.42
Pure error
3
314.8
104.9
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95.69
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R2
Mean squares
F−value
P−value
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Sum of
19.72
<0.001
0.55
0.741
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Degrees of
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Highlights: • Synthesis of Ag, Ag−Cu and Ag−Cu2O alloy nanostructures.
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• RSM was successfully employed for predicting the size of the AgNPs.
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• Size and composition tuning by adjusting the kinetic and thermodynamic conditions.
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