Fabrication of Mn_1-xZn_xFe₂O₄ ferrofluids from natural sand for magnetic sensors and radar absorbing materials

Abstract

Mn_1-xZn_xFe₂O₄ ferrofluids were produced from natural sand for magnetic sensors and radar absorbing materials. The X-ray diffraction data showed that the Zn partially substituted the Mn and Fe ions to construct a spinel structure. The increasing Zn composition decreased the lattice parameters of the structure. The transmission electron microscopy images showed that the filler Mn_1-xZn_xFe₂O₄ nanoparticles tended to agglomerate in three dimensions. Lognormal and mass fractal models were used to fit the small-angle X-ray scattering data of the ferrofluids demonstrated that the ferrofluids formed chain-like structures with a fractal dimension of 1.12–1.67 that was constructed from primary particles with sizes of 3.6–4.1 nm. The filler, surfactant, and carrier liquid of the ferrofluids were confirmed by the functional groups of the metal oxides, tetramethylammonium hydroxide, and H₂O, respectively. The secondary particles contributed to the saturation magnetization of the Mn_1-xZn_xFe₂O₄ ferrofluids. The Mn_1-xZn_xFe₂O₄ ferrofluids demonstrated excellent performance as magnetic sensors with high stability, especially compared with MnFe₂O₄ ferrofluids. Furthermore, the ferrofluids exhibited excellent radar absorbing materials. The Mn_1-xZn_xFe₂O₄ ferrofluids prepared in this work may serve as a future platform for advancing magnetic sensors and radar absorbing materials.

Materials science; Nanotechnology; Electromagnetism; Natural sand; Mn_1-xZn_xFe₂O₄; Ferrofluid; Magnetic sensor; Radar absorbing material

1. Introduction

In the last few years, fabrication methods for producing spinel MnZn ferrite (Mn_1-xZn_xFe₂O₄) nanoparticles with high quality structural and magnetic properties have been developed [1]. The development has also intended to improve the specific application performance of Mn_1-xZn_xFe₂O₄ nanoparticles, especially for sensors [2] and radar or microwave absorbing materials [3]. In general, the application of Mn_1-xZn_xFe₂O₄ nanoparticles has been triggered by their fascinating characteristics, such as excellent magnetic loss, good corrosion resistance, moderate saturation magnetization, and low cost [4]. The Mn_1-xZn_xFe₂O₄ nanoparticles have also been proposed for practical applications, including sensors, owing to their high magnetization sensitivity to temperature [5]. Furthermore, the Mn_1-xZn_xFe₂O₄ nanoparticles have high reflection loss and broadband absorption, providing a significant advantage as a radar absorbing material [6, 7]. However, until recently, there were at least two main challenges with producing Mn_1-xZn_xFe₂O₄ nanoparticles for magnetic sensors and radar absorbing materials with excellent performance. The first issue is producing Mn_1-xZn_xFe₂O₄ nanoparticles with a specific hierarchical structure, such as chain-like structure, with high stability and sensitivity under a small external magnetic field. The second issue is producing Mn_1-xZn_xFe₂O₄ nanoparticles in mass production using simple, inexpensive, effective, and ecofriendly synthesis.

To overcome the first issue, it is essential to produce small Mn_1-xZn_xFe₂O₄ magnetic nanoparticles in a monodisperse system by using a suitable surfactant agent to prevent agglomeration. In this study, we employed a single surfactant technique to coat magnetic particles with tetramethylammonium hydroxide (TMAH). The use of a surfactant is crucial to produce monodisperse magnetic nanoparticles with superparamagnetic characteristics [8, 9]. Fabricating magnetic nanoparticles in a ferrofluid system is an ideal experiment to address the structure issue. Practically, ferrofluids have specific advantages compared with bulk, film, and even in nanopowder forms. One such benefit is that ferrofluids can maintain magnetic properties in their liquid form and are very sensitive to external magnetic fields [10, 11], which is required for magnetic sensor applications. Interestingly, the interaction between magnetic nanoparticles and external magnetic fields is contributed to by the magnetic moment and liquid flexibility, making magnetic particles in ferrofluids easier to align under an external magnetic field [12]. In addition, ferrofluids can also maintain the properties of a fluid even in the presence of high magnetic fields, and magnetic particles as fillers do not separate from the carrier fluid to provide additional advantages for sensors and radar absorber applications.

To address the second issue, we proposed a fabrication method that uses an abundant natural material as the primary precursor to produce Mn_1-xZn_xFe₂O₄ ferrofluids. To the best our knowledge, the fabrication of Mn_1-xZn_xFe₂O₄ nanoparticles for ferrofluids tends to use relatively expensive commercial primary precursors that are less economical for mass production [5, 13, 14]. Therefore, in this study, we developed a fabrication method of Mn_1-xZn_xFe₂O₄ ferrofluids using abundant natural iron sand as the main precursor that is effective, efficient, inexpensive, and ecofriendly. Natural iron sand can be employed effectively to minimize the fabrication cost for the synthesis of high quality magnetic nanoparticles [15]. Moreover, to further reduce the fabrication cost, water was used as the polar carrier liquid in the fabrication of Mn_1-xZn_xFe₂O₄ ferrofluids with a chain-like structure. The prepared ferrofluids were investigated by their hierarchical nanostructures, molecular structures, and magnetic properties. Finally, the performance of the Mn_1-xZn_xFe₂O₄ ferrofluids as magnetic sensors and radar absorbing materials were also explored.

2. Experimental methods

In this study, natural iron sand was used as the primary source of Fe by the formation of ferric chloride and ferrous chloride. MnCl₂.H₂O was used as the primary source of Mn and ZnCl₂ was employed as the main source of Zn. The other materials were TMAH used as the surfactant, H₂O used as the carrier liquid, HCl (38%) used as the solvent, and NH₄OH (25%) used as the precipitating agent. Dried natural iron sand was separated from impurities using a permanent magnet to produce Fe₃O₄ powder with a purity of 99.5% [15]. Twenty grams of Fe₃O₄ powder was reacted with 58 mL of HCl using a magnetic stirrer for 30 min at room temperature to obtain ferric chloride and ferrous chloride. The ferric chloride and ferrous chloride were reacted with MnCl₂.H₂O and ZnCl₂ at specific compositions under stirring for 30 min, followed by a sonication process in a room temperature ultrasonic bath at a frequency of 40 kHz for 10 min. The next process was titration with 27 mL of NH₄OH for 30 min to obtain a black precipitate consisting of Mn_1-xZn_xFe₂O₄ nanoparticles. The precipitate was then filtered and washed using distilled water until the pH was 7. The x value of Mn_1-xZn_xFe₂O₄ representing Zn and Mn ions was varied, resulting in compositions of Fe₃O₄, MnFe₂O₄, Mn_0.75Zn_0.25Fe₂O₄, Mn_0.5Zn_0.5Fe₂O₄, Mn_0.25Zn_0.75Fe₂O₄, and ZnFe₂O₄. Subsequently, 1.2 g of Mn_1-xZn_xFe₂O₄ nanoparticles were reacted with 1.2 mL of TMAH under rough stirring for 15 min to obtain a homogeneous suspension. Five milliliters of H₂O was then added to the suspension as a dispersant media and stirred for 15 min to obtain the Mn_1-xZn_xFe₂O₄ ferrofluids.

X-ray diffractometry (XRD; X'Pert Pro, PANalytical) was used to determine the phase, particle size, and lattice parameters of the samples. The morphology of the samples was identified using transmission electron microscopy (TEM; JEOL 1400). Characterization of the functional group of the Mn_1-xZn_xFe₂O₄ ferrofluids was performed using Fourier-transform infrared spectroscopy (FTIR; Shimadzu). The magnetic properties were identified using vibrating magnetometer samples (VSM; Oxford). The hierarchical nanostructure of the Mn_1-xZn_xFe₂O₄ ferrofluids was investigated using a synchrotron-based small-angle X-ray scattering (SAXS). Finally, the potential application of the samples was examined by characterization of the magnetic sensor performance in a magnetic field range of 0–200 mT. The relaxation particle time was also investigated at room temperature. The radar absorption performance of the samples was evaluated using a vector network analyzer (VNA) at a frequency range of 8–12 GHz, which was the working area of the radar.

3. Results and discussion

The X-ray diffraction patterns of the Mn_1-xZn_xFe₂O₄ nanoparticles as fillers are depicted in Figure 1. The green lines represent the fitting model using AMCSD No. 0007423 and the experimental data are represented by the black circles. The Rietveld refinement method was employed using the Rietica program to investigate the crystal structure and particle size of the Mn_1-xZn_xFe₂O₄ nanoparticles [16]. Visually, the most intense diffraction peak was Miller index (311), which tended to shift to a lower 2θ value originating from the Zn ion composition. Quantitatively, the highest diffraction peak of the Fe₃O₄ nanoparticles was detected at 35.66° 2θ, while the highest diffraction peak of the MnFe₂O₄ nanoparticles shifted to a lower 2θ value at 35.48°. The shifting of the highest diffraction peak originated with the presence of Mn substitution into the Fe₃O₄ nanoparticles [17, 18] owing to the difference in Fe²⁺, Fe³⁺, and Mn²⁺ ionic radii of 0.77, 0.65, and 0.82 Å, respectively [19, 20]. Therefore, the lattice parameters increased, leading to a shift in the diffraction peak to a lower position. Furthermore, the higher Zn ion composition in the Mn_0.75Zn_0.25Fe₂O₄, Mn_0.5Zn_0.5Fe₂O₄, Mn_0.25Zn_0.75Fe₂O₄, and ZnFe₂O₄ samples tended to increase the highest diffraction peak position to 35.59°, 35.62°, 35.64°, and 35.71°, respectively. The increasing 2θ values with decreasing lattice parameters originated from the increasing Zn ions with an ionic radii of 0.74 Å, which is smaller than that of the Mn ions [21]. The lattice parameters, crystal volume, and particle size of the samples are presented in Table 1. Interestingly, the trend of the lattice parameters and crystal volumes tended to be similar to the particle size pattern of the samples. For the maximum Mn ion composition, the lattice parameters and crystal volume increased significantly and decreased gradually with the increasing Zn ion composition. The crystal structure of the samples was similar to a previous study [22]. In this work, all samples had a spinel cubic structure [23], where the Mn²⁺, Zn²⁺, Fe²⁺, and Fe³⁺ were randomly in octahedral and tetrahedral sites in the spinel system with lattice parameters of a = b = c.

Figure 1.

X-ray diffraction patterns of the Mn_1-xZn_xFe₂O₄ nanoparticles.

Table 1.

Lattice parameters and particle size of the Mn_1-xZn_xFe₂O₄ nanoparticles.

Sample	Lattice parameters a = b = c (Å)	Crystal volume V = a3 (Å3)	Particle size (nm)
Fe3O4	8.351 ± 0.005	582.4 ± 0.6	9.5 ± 0.3
MnFe2O4	8.380 ± 0.003	588.5 ± 0.6	11.5 ± 0.3
Mn0.75Zn0.25Fe2O4	8.377 ± 0.003	587.9 ± 0.5	10.4 ± 0.2
Mn0.5Zn0.5Fe2O4	8.372 ± 0.002	586.8 ± 0.7	9.8 ± 0.2
Mn0.25Zn0.75Fe2O4	8.365 ± 0.004	585.3 ± 0.5	9.1 ± 0.2
ZnFe2O4	8.349 ± 0.003	581.9 ± 0.7	10.1 ± 0.3

With regard to the change in the crystal parameters with Zn and Mn doping, the cationic distribution of the spinel structure variate depends on the degree of inversion (i). Based on the stoichiometry, the degree of inversion can be defined as the fraction of A-sites that are filled by cations and initially attributed to the B-sites. The Mn_1-xZn_xFe₂O₄ nanoparticles (0 < x < 1) are defined by the cationic distribution shown in Eq. (1), according to the degree of inversion proposed by Klencsár et al. [24]. The samples with x = 0.25, 0.50, and 0.75 have a degree of inversion of 0.59, 0.50, and 0.41, respectively. Furthermore, the degree of inversion of samples x = 0 and 1 are 0.37 and 0.68, respectively. Using the calculation model by Klencsár et al. [24] and Liu et al. [25], including applying the degree of inversion, the cationic distribution of samples x = 0 and 1 can be expressed in Eqs. (2) and (3). Moreover, the cationic distribution of Fe₃O₄ is presented in Eq. (4).

$${\left[{\text{Mn}}_{1-i}^{2+}{\text{Zn}}_{x-i}^{2+}{\text{Fe}}_i^{2+}\right]}_{\text{A}}{\left[{\text{Fe}}_{1-i}^{2+}{\text{Fe}}_1^{3+}{\text{Mn}}_i^{3+}\right]}_{\text{B}}{\text{O}}_4^{2-}$$ (1)

$${\left[{\text{Mn}}_{1-i}^{2+}{\text{Fe}}_i^{2+}\right]}_{\text{A}}{\left[{\text{Fe}}_{2-i}^{3+}{\text{Mn}}_i^{3+}\right]}_{\text{B}}{\text{O}}_4^{2-}$$ (2)

$${\left[{\text{Zn}}_{1-i}^{2+}{\text{Fe}}_i^{2+}\right]}_{\text{A}}{\left[{\text{Fe}}_{1-i}^{2+}{\text{Fe}}_1^{3+}\right]}_{\text{B}}{\text{O}}_4^{2-}$$ (3)

$${\left[{\text{Fe}}^{3+}\right]}_{\text{A}}{\left[{\text{Fe}}^{2+}{\text{Fe}}^{3+}\right]}_{\text{B}}{\text{O}}_4^{2-}$$ (4)

Figure 2 presents the TEM characterization illustrating the morphology of the Mn_1-xZn_xFe₂O₄ nanoparticles. The characterization focused on three samples, Fe₃O₄, Mn_0.5Zn_0.5Fe₂O₄, and ZnFe₂O₄ nanoparticles. As shown in Figure 2, the fabricated samples were nanometer in size. Based on a physics perspective, small magnetic nanoparticles have high surface area, which leads to an increase in van der Waals force [26]. This force causes the Mn_1-xZn_xFe₂O₄ nanoparticles to agglomerate. The average particle size of the Fe₃O₄, Mn_0.5Zn_0.5Fe₂O₄, and ZnFe₂O₄ nanoparticles were 11.1, 13.0, and 10.3 nm, respectively. Although the TEM characterization showed that the nanoparticles were successfully fabricated in a nanometer size, the particle size and hierarchical structure of the Mn_1-xZn_xFe₂O₄ ferrofluids could not be characterized. Therefore, an in situ investigation was conducted using a synchrotron-based SAXS to investigate the real particle size and hierarchical structure of the Mn_1-xZn_xFe₂O₄ ferrofluids. The SAXS profiles of the Mn_1-xZn_xFe₂O₄ ferrofluids and its fitting analysis are presented in Figure 3. The SAXS profiles were fitted using mathematical models as well as the form factor P(q,R), structure factor S(q,R), intensity I(q), and distribution of particle size f(R), as shown in Eqs. (5), (6), (7), and (8) [18, 27]:

$$P\left(q,R\right)=9{\left[\frac{\sin \left(qR\right)-qR\cos \left(qR\right)}{{\left(qR\right)}^3}\right]}^2$$ (5)

$$S\left(q,R\right)=1+\frac{D}{R_0^D}\underset{0}{\overset{\infty }{\int }}{R}^{D-3}h\left(R,\xi \right)\frac{\sin \left(qR\right)}{qR}{R}^{2}dR$$ (6)

$$I\left(q\right)=\underset{0}{\overset{\infty }{\int }}{N}_1\left(R_1\right)F_N^2(q,R_1)d{R}_1+\underset{0}{\overset{\infty }{\int }}{N}_2\left(R_2\right)F_N^2\left(q,R_2\right)d{R}_{2}S\left(q,R_2,\xi ,D\right)$$ (7)

$$f\left(R\right)=\frac{N}{\sigma R\sqrt{2\pi }}exp\left[\frac{{\text{ln}}^2\left(\raisebox{1ex}{$R$}\!\left/ \!\raisebox{-1ex}{$R_0$}\right.\right)}{2{\sigma }^2}\right]$$ (8)

where q is the scattering vector, R is the particle size, σ is the polydispersity index, R₁ is the primary particles, R₂ is the secondary particles, R_o is the mean particle radii, N is the normalization factor, ξ is the cutoff length from fractal correlation, and D is the fractal dimension [20]. In general, the ferrofluids with a single surfactant stabilization have particle size distribution along with a polydisperse character and chain-like structure [28]. According to the theoretical approach, the particle size of the ferrofluids can be suitably fit with a lognormal model in constructing the fractal structures [29]. Specifically, the fitting analysis results of the SAXS data for the Mn_1-xZn_xFe₂O₄ ferrofluids are presented in Table 2. The primary particles of the Mn_1-xZn_xFe₂O₄ ferrofluids were spherical, with a diameter of 3.6–4.1 nm that formed secondary cluster particles, which is similar to the results of a previous work [30]. The primary particle building blocks constructed a fractal structure with a chain-like structure for all samples with a fractal dimension from 1.12 to 1.67. The primary particles built the secondary particles, constructing a fractal structure in one dimension as a chain-like-structure [31]. An illustration of the hierarchical structure of the Mn_xZn_1-xFe₂O₄ ferrofluids is shown in Figure 4. Theoretically, the chain-like structure in the ferrofluids is built even in the presence of an external magnetic field.

Figure 2.

TEM images of the Mn_1-xZn_xFe₂O₄ nanoparticles.

Figure 3.

Synchrotron SAXS profiles of the (a) Fe₃O₄, (b) MnFe₂O₄, (c) Mn_0.75Zn_0.25Fe₂O₄, (d) Mn_0.5Zn_0.5Fe₂O₄, (e) Mn_0.25Zn_0.75Fe₂O₄, and (f) ZnFe₂O₄ ferrofluids. The black circles and green solid lines represent the experimental data and fitting model, respectively.

Table 2.

Results of the synchrotron SAXS fitting of the Mn_1-xZn_xFe₂O₄ ferrofluids.

Sample	Primary particle (nm)	Secondary particle (nm)	Fractal aggregate (nm)	Fractal dimension
Fe3O4	3.6 ± 0.1	11.1 ± 0.1	80.0 ± 4.5	1.67 ± 0.17
MnFe2O4	3.6 ± 0.2	10.5 ± 0.1	27.9 ± 1.3	1.49 ± 0.13
Mn0.75Zn0.25Fe2O4	4.1 ± 0.2	13.9 ± 0.2	68.7 ± 3.6	1.36 ± 0.11
Mn0.5Zn0.5Fe2O4	3.6 ± 0.1	16.8 ± 0.3	65.7 ± 3.1	1.13 ± 0.05
Mn0.25Zn0.75Fe2O4	4.0 ± 0.2	13.0 ± 0.2	32.8 ± 1.0	1.40 ± 0.10
ZnFe2O4	3.6 ± 0.1	12.8 ± 0.1	68.9 ± 3.4	1.12 ± 0.05

Figure 4.

Illustration of the hierarchical structure of the Mn_1-xZn_xFe₂O₄ ferrofluids.

The functional groups of the Mn_1-xZn_xFe₂O₄ ferrofluids are presented in Figure 5. The stretching band of Fe³⁺–O was observed at the wavenumber of 433 cm⁻¹ and the band of Fe²⁺–O was in the range of 573–634 cm⁻¹ [32]. Fe³⁺–O and Fe²⁺–O were located at the octahedral and tetrahedral sites. The functional groups of the metal–oxygen (M–O) group originated from the magnetic particles as fillers to form ferrofluids. The competition of the Mn and Zn ions at the octahedral and tetrahedral sites in the spinel system tended to change the lattice parameters of the Mn_1-xZn_xFe₂O₄ ferrofluids. Furthermore, the presence of TMAH was evaluated by the functional group of the C–N, C–H, and O–H observed at the wavenumbers of 1395, 1508, and 3377 cm⁻¹, respectively [33]. The TMAH acted as a surfactant to cover the magnetic nanoparticles. Finally, the carrier liquid was detected by the functional group of O–H identified at the same position with the stretching band of the TMAH at the wavenumber of 3379 cm⁻¹ [34], broadening the peak for the O–H stretching band. Therefore, all ferrofluid components were perfectly observed originating from the filler, surfactant, and carrier liquid.

Figure 5.

Infrared spectrum of the Mn_1-xZn_xFe₂O₄ ferrofluids.

The magnetic properties of the Mn_1-xZn_xFe₂O₄ ferrofluids were evaluated from the magnetization curves, as shown in Figure 6. The magnetization patterns of the ferrofluids tended to be different, specifically related to saturation magnetization. Theoretically, the smaller the particle size, the greater the magnetic moment on the surface. Under this condition, the magnetic moment on the surface contributes significantly to the magnetic properties of the materials. Kaur et al. explained that the saturation magnetization of magnetic nanoparticles in the spinel system depends on their magnetic moment and exchange interaction [22]. In the spinel structure, the magnetic moment is influenced by the atomic spin interaction mechanism at the A-site and B-site. Therefore, the net magnetic moment can be calculated using Eq. (9) [35].

$${\mu }_{\text{net}}={\mu }_{\text{B}-\text{site}}-{\mu }_{\text{A}-\text{site}}$$ (9)

Figure 6.

Magnetization curves of the Mn_1-xZn_xFe₂O₄ ferrofluids at room temperature.

By substituting the magnetic moment values of Fe²⁺ (4 μ_B), Mn²⁺ (5 μ_B), Zn²⁺ (0 μ_B), Fe³⁺ (5 μ_B), and Mn³⁺ (4 μ_B) into Eq. (9) and Eqs. (1), (2), (3), and (4), the net magnetic moment in the spinel system produced, as shown in Table 3. The calculated magnetic moment value has a different saturation magnetization pattern for each sample. Therefore, the magnetic properties of the ferrofluids are not only influenced by the net magnetic moment and exchange interaction, but also influenced by other factors, including particle dispersion, nanoparticle arrangement, and the energy of dipole interaction of two contacting particles [36]. Thus, the SAXS data provides an important role in explaining the correlation of the structure parameters of the ferrofluids to their magnetic properties.

Table 3.

Magnetic properties of the Mn_1-xZn_xFe₂O₄ ferrofluids.

Sample	Magnetic moment (μB)	Saturation magnetization (emu/g)	Remanent magnetization (emu/g)	Secondary particle (nm)	Polydispersity index
Fe3O4	4.00	0.053 ± 0.004	3.4 ± 0.2	11.1 ± 0.1	0.13 ± 0.03
MnFe2O4	5.00	0.046 ± 0.004	-	10.5 ± 0.1	0.11 ± 0.02
Mn0.75Zn0.25Fe2O4	4.59	0.086 ± 0.007	2.4 ± 0.1	13.9 ± 0.2	0.38 ± 0.05
Mn0.5Zn0.5Fe2O4	7.00	0.188 ± 0.008	4.2 ± 0.2	16.8 ± 0.3	0.41 ± 0.04
Mn0.25Zn0.75Fe2O4	4.41	0.079 ± 0.006	2.0 ± 0.1	13.0 ± 0.2	0.26 ± 0.02
ZnFe2O4	6.04	0.070 ± 0.005	4.1 ± 0.2	12.8 ± 0.1	0.29 ± 0.05

In the ferrofluids, strong inter-particle interactions cause large magnetic particles to form chains. Under an external magnetic field, small magnetic particles can still maintain Brownian motion or link to the end of the chain. This behavior contributes to the change in the coercivity field and remanent magnetization of the ferrofluids. Based on Table 2, the ZnFe₂O₄ ferrofluid sample has a large average aspect ratio (chain correlation length ξ = 68.9 nm with secondary particles = 12.8 nm), which indicates that the sample has a large average anisotropy shape and implies an increase in the remanent magnetization. In this work, ZnFe₂O₄ is ferrimagnetic because the magnetic moments located in the tetrahedral position are opposites within the octahedral position, resulting in unequal magnetic moments in the spinel system. The spinel system can be divided into three types: normal, inverse, and mixed spinel systems. In the previous work, Grasset et al. showed that the ZnFe₂O₄ with a normal spinel exhibits antiferromagnetic character [37]. The diamagnetic Zn²⁺ ions are only at tetrahedral sites and Fe³⁺ ions are only at octahedral sites and they are coupled with each other via a superexchange pathway through tetrahedral sites. Furthermore, other previous works showed that zinc ferrite nanoparticles are antiferromagnetic in a normal spinel system and with bulk materials; however, they show ferrimagnetic behavior at the nanometer scale. Other reports similarly showed that ZnFe₂O₄ does not construct a normal spinel system. ZnFe₂O₄ nanoparticles show ferrimagnetic behavior at room temperature and antiferromagnetic ordering below 9 K [38]. Other showed that the ZnFe₂O₄ nanoparticles have ferrimagnetic behavior at room temperature [39, 40]. Interestingly, the ZnFe₂O₄ ferrofluid sample has a fractal dimension of D ~1, which is interpreted as a chain arrangement resembling a rod. According to the theory, the demagnetization factor of the chain arrangement can be expressed by Eq. (10) [41].

$$D_{\text{factor}}=1-\left(\raisebox{1ex}{$\xi $}\!\left/ \!\raisebox{-1ex}{$2r$}\right.\right){\left[{\left(1+\left(\raisebox{1ex}{$\xi $}\!\left/ \!\raisebox{-1ex}{$2r$}\right.\right)\right)}^2\right]}^{1/2}$$ (10)

The longer the chain arrangement, the smaller the D_factor. When the D_factor is low, the remanent magnetization increases. Furthermore, other ferrofluid samples have larger fractal dimension that interprets a denser chain arrangement with shorter chain lengths. Therefore, the coercivity field and remanent magnetization decrease.

Interestingly, the Mn_0.5Zn_0.5Fe₂O₄ ferrofluids have a superparamagnetic character with the highest saturation magnetization value. However, compared to the bulk samples, the saturation magnetization of the ferrofluids was lower because of the effect of the surfactant and carrier liquid [42]. The surfactant and carrier liquid in the ferrofluids strongly contribute to creating repulsion forces between particles, thereby overcoming aggregation. If the particle interaction force is greater than the electrostatic repulsion force, the ferrofluids will be polydisperse; otherwise, the ferrofluids will be monodisperse. Based on the SAXS data analysis, the Mn_1-xZn_xFe₂O₄ ferrofluids belong to a bidisperse system because they contain two different particle sizes, namely primary and secondary particles. In the ferrofluid system, the small particles have Brownian motion, while the large particles have a stronger coupling interaction and dominate the Brownian motion [43]. Therefore, the saturation magnetization also depends on the behavior of the large particles. High saturation magnetization occurs with samples that have a large particle size and a polydisperse index, which is consistent with previous studies [42, 43, 44, 45].

The performance of the magnetic sensor was investigated by measuring the sensitivity of the Mn_1-xZn_xFe₂O₄ ferrofluids under an external magnetic field. The external magnetic field increased until the magnetic moment of the ferrofluids achieved saturation. Furthermore, the magnetic field was then reduced to obtain an output voltage as a function of the magnetic field, as shown in Figure 7. In general, when the ferrofluids was subject to an increasing external magnetic field, the output voltage also increased and vice versa. For the Fe₃O₄ ferrofluids, the splitting curve was observed to start from the magnetic field of 10 mT. Therefore, the stability of the Fe₃O₄ ferrofluids as magnetic sensors was not optimum. However, the MnFe₂O₄ ferrofluids had high stability, which was identified from the relative absence of the splitting curve. This shows that MnFe₂O₄ ferrofluids have high potential to be used as magnetic sensor materials for a small magnetic field. The results of this work coincide with the magnetic sensor developed by Zhao and co-workers based on ferrofluids combining with the photonic crystal fiber [46]. They observed that the ferrofluids characteristics change rapidly because of the magnetic field. The nearly coinciding curves of the increasing and decreasing magnetic field proves that the sensor performance is ideal. Furthermore, for Mn_0.75Zn_0.25Fe₂O₄ ferrofluids, the magnetic sensor performance of the Mn_0.75Zn_0.25Fe₂O₄ ferrofluids is not as good as the MnFe₂O₄ ferrofluids for fields greater than 35 mT. This difference can be explained by the presence of Zn ions, which substitute the Mn ion to affect the magnetic moment of the sample. Moreover, the sensor performance curve of the Mn_0.5Zn_0.5Fe₂O₄ ferrofluids fluctuates above the 35 mT because of the increased molar fraction of Zn ions. The Mn_0.25Zn_0.75Fe₂O₄ and ZnFe₂O₄ ferrofluids had a splitting curve, although with increasing Zn ion composition, the splitting becomes relatively narrow. Thus, the best magnetic sensor performance was observed with the MnFe₂O₄ ferrofluids, which have excellent stability in both up and down fields.

Figure 7.

Magnetic sensor performance of the Mn_1-xZn_xFe₂O₄ ferrofluids at room temperature.

The particle relaxation time is essential to ensure sensor performance. The output voltage as a function of the particle relaxation time of the Mn_1-xZn_xFe₂O₄ ferrofluids is shown in Figure 8. In a relatively short time, the magnetic particles in the ferrofluids were able to return to the initial state. This improves the sensor performance because the ferrofluids do not require a long time to relax, indicating that the ferrofluids as a magnetic sensor material have excellent flexibility. In general, the magnetic particles of the Mn_1-xZn_xFe₂O₄ ferrofluids, except Mn_0.5Zn_0.5Fe₂O₄ ferrofluids, tended to be easily and quickly stable after a mechanical treatment less than 3 min. We predict that this phenomenon is caused by secondary particles, where the Mn_0.5Zn_0.5Fe₂O₄ ferrofluids are the largest. Because the secondary particles are large, the magnetic particles become easier and faster to precipitate. In this case, the particle relaxation time is defined as the time to of the magnetic particles of the ferrofluids to reach stability. The particle relaxation time is influenced by the particle motion characteristics of the ferrofluids. The closer the particles, the more limited the particle motion under mechanical treatment and it will quickly return to its original state after the treatment is removed [47]. This phenomenon is consistent with research conducted by Zhou and co-workers, demonstrating that ferrofluids have high flexibility [48]. Thus, if the ferrofluids are given an external treatment, then after the treatment is removed, it will quickly return to its original state.

Figure 8.

Particle relaxation time of the Mn_1-xZn_xFe₂O₄ ferrofluids at room temperature.

The radar absorption performance of the Mn_1-xZn_xFe₂O₄ nanoparticles was evaluated using a VNA at room temperature, and its result is presented in Figure 9. The experiment was conducted at a frequency range of 8–12 GHz for the working area of the radar. The reflection loss (RL) as the ability of the samples to absorb the radar was evaluated using Eq. (11):

$$RL=20\text{log}\left|\frac{1-\sqrt{{\mu }_{\text{r}}/{\epsilon }_{\text{r}}}\tanh \left(-j2\pi fd\sqrt{{\mu }_{\text{r}}{\epsilon }_{\text{r}}}\right)}{1+\sqrt{{\mu }_{\text{r}}/{\epsilon }_{\text{r}}}\tanh \left(-j2\pi fd\sqrt{{\mu }_{\text{r}}{\epsilon }_{\text{r}}}\right)}\right|$$ (11)

where μ_r represents the complex permeability of the absorber, ε_r represents the complex permittivity of the absorber, f represents the frequency, d represents the thickness of the absorber, and c represents the velocity of light in a vacuum [49]. In principle, good radar absorbing materials have special characteristics such as lightweight, thin, and the ability to cover a broad frequency [50].

Figure 9.

Reflection loss of the Mn_1-xZn_xFe₂O₄ nanoparticles at a frequency range of 8–12 GHz.

Based on Figure 9, the RL of the samples was −14.1, −15.4, −12.9, −11.0, −12.9, and −11.7 dB for the Fe₃O_4, MnFe₂O₄, Mn_0.75Zn_0.25Fe₂O₄, Mn_0.5Zn_0.5Fe₂O₄, Mn_0.25Zn_0.75Fe₂O₄, and ZnFe₂O₄ samples, respectively. Such RL was observed at frequencies of 10.8, 10.9, 10.8, 10.8, 10.9, and 10.8 GHz, respectively. The maximum peak was observed for the MnFe₂O₄ sample, indicating that this sample exhibited the best performance as a radar absorbing material. Akinay and co-workers identified the radar absorbing performance of a polyvinyl butyral (PVB), Fe₃O₄, and nickel ferrite nanoparticle composite with various thicknesses [51]. The absorption peak was in the frequency range of 1.0–3.0 GHz for the PVB/Fe₃O₄ nanocomposites and 1.0–2.6 GHz for the PVB/NiFe₂O₄ nanocomposites with a minimum thickness of 3 mm. Theoretically, the absorbing phenomenon of the magnetic materials is initiated by the changing energy of the electromagnetic waves when the magnetic dipole moves to rotate in the material [52]. Based on the data analysis, increasing Zn or decreasing Mn in the Mn_1-xZn_xFe₂O₄ nanoparticles decreases the RL because Zn is a diamagnetic material, reducing the energy needed to rotate the magnetic moment [53]. The Mn_0.5Zn_0.5Fe₂O₄ nanoparticles had a minimum RL believed to be the effect of the largest secondary particle (16.8 nm) with the highest polydispersity index (0.41). With a larger particle size, the ratio of the surface area to volume is smaller, causing low absorption of the materials. Interestingly, the MnFe₂O₄ nanoparticles with the highest Mn composition had a maximum RL. Based on the theoretical calculation, Mn²⁺ with a higher magnetic moment (5 μ_B) replaced Fe²⁺ with a lower magnetic moment (4 μ_B). Furthermore, the MnFe₂O₄ nanoparticles with the smallest primary particles as building blocks contributed to the increasing surface area. Therefore, the MnFe₂O₄ nanoparticles more easily absorbed the microwave. The microwave directed to the nanoparticles in the Mn_1-xZn_xFe₂O₄ ferrofluids also interacts with the TMAH surfactant agent and carrier liquid that has dielectric characteristics. Therefore, a Coulomb force appears owing to the interaction between the electric field from the microwave and free radicals from the surfactant and dispersant [54]. Therefore, the microwave stimulates the charge acceleration that produces an electric current. In addition, the magnetic field of the ferrofluids generates destructive superposition with the opposite phase under the microwave [55]. Consequently, the radar that interacts with the Mn_1-xZn_xFe₂O₄ ferrofluids was difficult to detect by the radar receiver. As a result, our Mn_1-xZn_xFe₂O₄ ferrofluids are expected to form a novel platform for advancing radar absorbing materials.

4. Conclusion

In this study, the synthesis of Mn_1-xZn_xFe₂O₄ ferrofluids was performed through a coprecipitation method employing natural iron sand as the main precursor. As the Zn molar fraction increases, the lattice parameters, crystal volume, and particle size of the ferrofluids tended to decrease. In general, the Mn_1-xZn_xFe₂O₄ nanoparticles had a spherical shape that were nanometer in scale. The functional groups for the main components of the Mn_1-xZn_xFe₂O₄ ferrofluids were detected from the metal oxides, TMAH, and H₂O used as the filler, surfactant, and carrier liquid, respectively. The aggregation characteristics strongly contributed to the saturation magnetization of the Mn_1-xZn_xFe₂O₄ ferrofluids. Furthermore, the potential of the ferrofluids as magnetic sensors was demonstrated by excellent performance, especially for the MnFe₂O₄ ferrofluids. For radar absorbing applications, the maximum Mn composition presented the best performance because it was the smallest building block of the magnetic particles. Therefore, the ecofriendly Mn_1-xZn_xFe₂O₄ nanoparticles fabricated from natural sand are potential magnetic sensors and radar absorbing materials.

Declarations

Author contribution statement

Ahmad Taufiq: Conceived and designed the experiments; Analyzed and interpreted the data; Wrote the paper.

Syamsul Bahtiar: Performed the experiments; Analyzed and interpreted the data.

Rosy Eko Saputro: Analyzed and interpreted the data; Wrote the paper.

Defi Yuliantika: Contributed reagents, materials, analysis tools or data.

Arif Hidayat: Analyzed and interpreted the data; Wrote the paper.

Sunaryono Sunaryono: Conceived and designed the experiments.

Nurul Hidayat: Analyzed and interpreted the data.

Samian Samian: Conceived and designed the experiments; Performed the experiments.

Siriwat Soontaranon: Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data.

Funding statement

This work was supported by Kementerian Riset Teknologi Dan Pendidikan Tinggi Republik Indonesia (071/SP2H/LT/DRPM/2018).

Competing interest statement

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.