Effect of experimental factors on magnetic properties of nickel nanoparticles produced by chemical reduction method using a statistical design
Introduction
Transition metal nanoparticles have attracted a lot of interest in recent years since they have intriguing physical and chemical properties which makes them a promising candidate in various applications [1]. Among transition metal nanoparticles, nickel nanoparticles have attracted considerable attention which is mostly due to their magnetic and catalytic properties [2], [3], [4], [5]. Nickel nanoparticles have a wide range of applications in rechargeable batteries [6], chemical catalysts [7], supercapacitors [8], etc. Various chemical methods have been developed for preparation of Ni nanoparticles such as chemical vapor deposition [9], electroless plating [10], polyol process [11], hydrothermal method [12], wet chemical reduction [8] and microemulsion method [13]. Chemical reduction method has many advantages over other synthesis methods. It is a simple, inexpensive and very versatile method for preparing the metallic nanoparticles. In the chemical reduction method, metal ions in metal salt solution are reduced to metal particles by reducing agent. Due to easily oxidizing nature of transition metal nanoparticles and their high tendency to agglomeration, it is inevitable to use the suitable surfactants or capping agents [16], [17]. However, presence of the surfactants can change the physical properties of produced nanoparticles [14], [15] and leads to the formation of stable solutions which makes the precipitation and separation of nanoparticles more difficult [16]. In magnetic nanoparticles, as the size of particles is reduced to a critical amount, they become single magnetic domain. In this case, the thermal energy overcomes the magnetic anisotropy energy barriers of single domain particles and results in super-paramagnetic behavior [17]. Super-paramagnetic nanoparticles have proven to be ideal for many biomedical applications such as magnetic resonance imaging, cancer treatments, biological and chemical sensing and targeted drug delivery [18], [19], [20], [21]. Due to the strong dependence of physical and particularly magnetic properties of metal nanoparticles on their shape and size [22], [23], it is important to control synthesis parameters to achieve desirable morphology and size distribution. It has been shown that the parameters such as solvent composition, reactants concentration, reaction temperature and surfactant concentration can be easily adjusted in the chemical reduction method [24], [25], [26], [27]. The conventional approaches for optimization of process variables require large number of experiments which would be very expensive and time consuming. However, a statistical experimental design can provide an appropriate model for optimizing the process which decrease the number of examinations and evaluate the influence of variables interactions on the process outcome [12], [28]. Some researchers investigated the relationship between process variables and the yield of nickel nanoparticles [29] or their size [12] by design of experiment. However, no systematic study has been done yet for investigating the effect of variables such as the solvents ratio or the rate of adding the precursor solutions to each other, on the magnetic properties of nickel nanoparticles. In previous study [30], we synthesized the metallic nickel nanoparticles using electrohydrodynamic atomization (EHDA) assisted chemical reduction method, which is a useful method for producing fine nanoparticles [31]. It has been shown that the atomization of nickel precursor into the reductive bath was very efficient for decreasing the size of nickel nanoparticles. It was also found out that separation of fine nanoparticles from the precursor solution is difficult due to their high stability in presence of the surfactant [30]. Thus, in present study, we synthesized nickel nanoparticles by reduction of nickel acetate precursor with sodium borohydride without using any surface capping agent.
Response surface methodology (RSM) is an experimental design technique that uses mathematical and statistical techniques to analyze the influence of independent variables (inputs) on a specific dependent variable (response). RSM is an effective alternative to the factorial design. Central composite design (CCD) which is a widely used form of RSM, was used to investigate the effect of the pouring rate of metal precursor into the reductive bath and solvents ratio on the morphological and magnetic properties of nickel nanoparticles. The use of CCD allows determination of the effects of various parameters and also the interrelation between them simultaneously [32].
Section snippets
Experimental
Nickel nitrate (Ni(NO3)2⋅6H2O), sodium borohydride (NaBH4), methanol and ethanol were purchased from Merck and used without further purification. Nickel nanoparticles were synthesized by reduction of Ni2+ cations dissolved in nickel precursor solution. Different solvents were tried as precursor/reductive solutions medium in order to achieve suitable solutions for reduction processes. Methanol and ethanol were chosen as synthesis media due to the high solubility of reactants in both solvents. No
Results and discussion
There was no crystalline peak in the X-ray diffraction patterns of samples. XRD pattern of a typical sample P9 is shown in Fig. 1. This is in agreement with previous work [30] which corroborates the weakly ordered, small size and large surface areas of nanoparticles produced by reduction precipitation using NaBH4 due to its fast reducing nature [28], [29]. A broad diffraction peak around 2θ = 45° is observable in Fig. 1 which is near the characteristic (1 1 1) peak position of metallic nickel. This
Conclusions
In this paper, nickel nanoparticles were synthesized by simple dripping of metal precursor into the reductive bath. Effect of the dripping rate and volume ratio of methanol/ethanol as precursor solvents on the morphology and magnetic properties of nickel nanoparticles were studied using central composite design and a simple empirical model has been proposed for this dependency. The results demonstrated that highly pure super-paramagnetic nickel nanoparticles with size range of 20–50 nm can be
Acknowledgment
This research was funded by Iran National Science Foundation (INSF) as a research project (No. 92004346).
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