The Influence of Zn Doping on the Cation Distribution and Antibacterial Activity of CoFe₂O₄

Abstract

Nanoparticles of formula Co_1-xZn_xFe₂O₄ (x = 0.0, 0.3, and 0.5) were prepared successfully using a citrate-auto-combustion method. This work studies the substitution effect of the Zn²⁺ ion on the physical, chemical, and structural properties of CoFe₂O₄. The structure of the prepared samples was determined via X-ray diffraction (XRD) and Fourier transformed infrared spectrometer (FTIR). X-ray diffraction of the investigated samples ensures that all the prepared samples crystallite into single structure. There is a variation of crystallite size with change in Zn concentration as it is observed that the crystallite size increased from 16.01 to 30.56 nm by increasing Zn concentration. The Fourier transform infrared spectra (FTIR) in range (390:4000) Cm⁻¹ were used for studying the elastic properties of the prepared spinel ferrites. It is observed that, by increasing Zn concentration, all elastic moduli increased. The morphological and surface study of the calcined samples was investigated by scanning electron microscopy (SEM) and Gwyddion 2.45 software respectively. The roughness average (R_a) was 35.20 nm at x = 0 and increased to 46.6 nm at x = 0.5. At the room temperature, magnetic behavior of the all studied samples was studied. It is observed that the maximum saturation magnetization was 67.611emu/gm and it was related to Co_0.7Zn_0.3Fe₂O₄ while the highest value of exchange bias (H_EB) was 2.15 Oe for Co_0.5Zn_0.5Fe₂O₄. The antibacterial activity of CoFe₂O₄, Co_0.7Zn_0.3Fe₂O₄, and Co_0.5Zn_0.5Fe₂O₄ was successfully tested against Escherichia coli and Staphylococcus aureus bacteria. The highest inhibition zone of Co_1-xZn_xFe₂O₄ values was 8 and 7.5 mm for E. coli and S. aureus, respectively, and these values were observed for x = 0.5. Generally, these results exhibit a high possible of ferrites for using in antibacterial applications.

1 Introduction

Ferrites are divided into three categories according to their crystal structure as hexagonal ferrites, garnet, and spinel ferrites [1]. The most broadly used family is spinel ferrites. This class shows its importance in new applications in many fields such as gas sensing [2], medicine [3], catalysis [4], and microwave [5]. The significance of spinel ferrites is related to their low cost, high electrical resistivity, high permeability, and distinct magnetic properties; thus, these properties are contingent on charge, the nature of ions besides their distribution between octahedral and tetrahedral sites. Numerous scientists have been developing novel ferrite compositions with looked-for properties suitable for technological applications [6,7,8,9]. The spinel ferrites have formula of MFe₂O₄ where M can be divalent or trivalent cation such as Nickel (Ni²⁺), cadmium (Cd²⁺), aluminum (Al³⁺), and chromium (Cr⁶⁺). A common example of spinel ferrites is CoFe₂O₄, ZnFe₂O₄, MnFe₂O₄, and MgFe₂O₄ [10]. Cobalt–zinc ferrite has a cation distribution with space group Fd3m. It symbolizes as (Zn_x²⁺ Fe_1−x³⁺) [Co_1−x²⁺Fe_1+x³⁺] O₄, where () and [] brackets term the tetrahedral and octahedral locations, respectively. [11] The physical properties related to CoFe₂O₄ are modified by Zn substitution in CoFe₂O₄ whereas, it distorted spinel structures and these adding deviations the microstructure properties as crystalline density, crystal size, lattice constant, bond lengths, and cations distribution among A and B-sites [12,13,14,15]. The most essential parameters that have strong impact on the predictable physical properties of the resultant doped cobalt ferrite are the preparation process beside the amount of the doped cation [16, 17]. It has been reported that TiO₂ nanoparticles has a significant impact at killing Staphylococcus aureus and Escherichia coli, a finding that encouraged research to direct for photo catalytic techniques for the killing of viruses and bacteria by using TiO₂ in aqueous media [18]. The drawback of using TiO₂ is that it needs a UV light for activation to start killing of viruses and bacteria. Hence, there is a need to advance novel nanostructured-based formulations which are steady, tough, and durable, in addition to be effective in the annihilation of viruses and bacteria [19]. The earliest studies have point out that the interaction between nanoparticles and microorganisms is an expanding area of research, which is mainly unexplored yet. The intricacy of their aforementioned crystalline arrangement and faults in it are the primary causes of nanoferrites’ antibacterial activity. Due to the relatively small photonic band gap of − 2 eV, this activity is linked to their optoelectronic as well as photocatalytic properties, i.e., the capacity to produce electron–hole pairs when exposed to visible light. While the holes may interact to hydroxyl groups to erase their charge as well as produce highly reactive radicals, the electrons might be caught with the oxygen molecules to be utilized to create oxyanions, which might aid in the creation of hydrogen peroxide [20]. The Fenton reaction’s equilibrium is shifted toward more receptivity to peroxides as a result of the electrons created having the ability to reduce Fe³⁺ to Fe²⁺ in both the nanoparticle and its biological surroundings simultaneously. Reactivity of oxygen species (ROS) produced by the photoelectrons damages the bacteria’s cell wall as well as other organelles, impairs their growth, and ultimately causes their demise. In agar plate experiments against E. coli, Zn ferrites’ antibacterial activities were validated, and they were distinctly concentration-dependent [19]. The Zn-doped Co-ferrite composition had the strongest antibacterial action, showing prominent inhibitory areas versus S. aureus, Enterococcus columbae, and Aerococcus viridans, according to a significant investigation involving mixed zinc ferrites doped with cobalt. Zn-doped cobalt ferrite nanoparticles cover the way for evolving cost effective, sustainable, and promising antibacterial nanosamples for medicine applications [21,22,23]. In the present work, we study the synthesis procedures of Co_1-xZn_xFe₂O₄ (x = 0.0, 0.3, and 0.5) nanoferrites using Citrate auto-combustion technique. Efforts have been done to find the influence of Zn doping on the structural, magnetic, and antibacterial activity of CoFe₂O₄. Different characterization techniques were carried out, such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM), and vibrating sample magnetometer (VSM). All the investigated samples were tested for killing S. aureus and E. coli, and they showed a great impact of antibacterial effects on many microorganisms. For our knowledge, no study is obtainable in the literature dealing with how the doping amount can be affected on the antibacterial activity.

2 Materials and Techniques

Zinc nitrate [Zn (NO₃)₂·6H₂O], cobalt nitrate [Co (NO₃)₂·6H₂O], iron nitrate [Fe(NO₃)₃·9H₂O], and citric acid [${C}_{4}{\mathrm{H}}_{8}{\mathrm{O}}_{7}$] were obtained from LOBA, India (99.9% pure). Totally, materials were used without additional purifications. Nanoparticles of formula Co_1-xZn_xFe₂O₄ (x = 0.0, 0.3, and 0.5) were prepared using a citrate-auto-combustion method. The synthesis process was occurred through three stages; the first stage is the mixing step which is related to the stoichiometric ratios of the desired ferrites by dissolving nitrates of cobalt (0.1 M), zinc, iron (0.1 M), and (0.7 M) citric acid in a small amount of distilled water. The second step is related to adjusting pH of the resultant solution to 7 by using ammonia solution (purity 95%). Finally, the temperature was raised up to 250 °C till all upcoming fumes over, and the obtained powders were calcinated at 800 °C for 2 h with rate 5 °C/min [24]. The following equations could be used to represent this process for the compositions CoFe₂O₄ and Co_0.5Zn_0.5Fe₂O₄:

$$Co\;(NO_3)_2\;6H_2O+2Fe(NO_3)_3\;9H_2O+C_4H_8O_7\xrightarrow{800\;C}CoFe_2O_4\downarrow$$

(1)

$$\begin{aligned}Co\;(NO_3)_2\;6H_2O+&Zn(NO_3)_2\;6H_2O+2Fe(NO_3)\;9H_2O\\&+C_4H_8O_7\xrightarrow{800\;C}2\;Co_{0.5}Zn_{0.5}Fe_2O_4\end{aligned}$$

(2)

XRD (analytical-x′ pertpro, Cu k_α1 radiation, λ = 1.5404 Å, 45 kV, 40 mA, Netherlands) was carried out to confirm the synthesis of samples in single phase and pure form. The average of the crystallite size was computed through Scherrer’s equation [25]:

$$\mathrm{D}=\frac{0.9\lambda\;}{{\upbeta\;}_\mathrm{{hkl}}\;\mathrm{cos\;\theta}}$$

(3)

where D is the average crystallite size (nm), λ is the X-rays wavelength (nm), and ${\upbeta }_{hkl}$ denotes the full width at half maximum (FWHM) in radians, while θ is the Bragg angle. Fourier transformed infrared spectrometer (Perkin-Elmer 2000) was used for measuring (FT-IR) spectra through wavenumber range of 4000–400 cm⁻¹. The sample morphologies were studied by using a scanning electron microscope (SEM) (model: QUANTA-FEG250, Netherlands) from SEM image, and by using ImageJ software, the histogram of all prepared samples was obtained. Using the software of Gwyddion 2.45 and the micrographs of powdered Co-Zn ferrite samples obtained from FESEM analysis the roughness parameters were obtained and calculated. The magnetic properties of the studied samples were investigated using a vibrating-sample magnetometer (VSM). Antibacterial activity of the prepared samples was determined using a modified Kirby-Bauer disc diffusion method [26]. Briefly, 100 µl of the test bacteria was grown in 10 ml of fresh media until they reached approximately10⁸ cells/ml for bacteria; then 100 µl of microbial suspension was spread onto agar plates corresponding to the broth in which they were maintained. Plates, including Gram ( +) bacteria as S. aureus and Gram ( −) bacteria as E. coli, were incubated at 35–37 °C for 24–48 h; then the diameters of the inhibition zones were measured in millimeters [27]. Standard discs of ampicillin (Antibacterial agent) and filter discs soaked with 10 µl of solvent consisting of (distilled water, chloroform, and DMSO) worked as positive and negative controls, respectively, for antibacterial activity. 8.0 mm blank paper disks were dripped in 10µ of the stock solutions. When a filter paper disc impregnated with a tested chemical is placed on agar, the chemical will diffuse from the disc into the agar. This diffusion will place the chemical in the agar only around the disc. The chemical solubility and its molecular size were used to determine the size of chemical infiltration area around the disc. If an organism is placed on the agar, it will not grow in the area around the disc if it is susceptible to the chemical. This no growth area surrounding the disc is well-known as a “Zone of inhibition” or “Clear zone.”

3 Results and Discussion

3.1 XRD

Figure 1 displays the XRD patterns associated to the prepared samples with formula Co_1-xZn_xFe₂O₄ (x = 0.0, 0.3, and 0.5) nanoparticles. All the indexed peaks could be related to a cubic spinel lattice, with no secondary phases such as Fe₂O₃ and/or ZnO. All presented peaks indexed as (311), (220), (400), (511), and (440) which attributed to all compositions of Co_1-xZn_xFe₂O₄ with no extra peaks, which confirm that all prepared samples crystallite into single structure. Based on the diffraction peaks and using the Debye–Scherrer formula, the average crystallite size (D) was calculated and is listed in Table 1, while the variation of crystallite size with change in Zn concentration is represented in Fig. 2a. From the figure, it is observed that the crystallite size increased from 16.01 to 30.56 nm by increasing Zn concentration. Figure 3 and Table 1 show that the lattice parameter as well as unit cell volume follows the same trend of average crystallite size. The point that larger Zn²⁺ occupies the smaller tetrahedral sites is confirmed by the expansion of the unit cell volume and lattice parameter, though larger ionic radius of Zn (0.74A°) prefers tetrahedral sites replacing and forcing Fe³⁺ (0.67 A°) to transfer into octahedral sites leading to expansion of lattice parameters as well as unit cell volume as shown in Table 1 and Fig. 2b. Previous explanation is in good agreement with Vegard’s law which is based on the variation owing to the ionic radii of the replaced and replacing ions [28]. The value of X-ray density (D_x) was obtained using this equation [29]:

$${D}_{x}=\frac{8M}{N{a}^{3}}$$

(4)

where 8 is related to the number of molecules in a unit cell of spinel lattice, M symbolizes the molecular weight of the sample, N represents Avogadro number, and “a” is the lattice parameter.

Fig. 1

XRD pattern for Co_1-xZn_xFe₂O₄ (x = 0.0, 0.3, and 0.5) nanoparticles

Table 1 Crystallographic data for Co_1-xZn_xFe₂O₄, including crystallite size (D), experimental (a_exp) and theoretical (a_theo) lattice parameter, unit cell volume (Ω), X-ray density (D_x), radii of tetrahedral (r_A) and octahedral (r_B) sites, tolerance factor (t), and oxygen parameters (U)

Fig. 2

Relation between Zn concentration and a average crystallite size and b lattice parameter

Fig. 3

Correlation between tolerance factor and Zn concentration

It was found that X-ray density decreased with increasing Zn concentration as listed in Table 1 from 5.3 to 5.27 g/cm³. This drop in the X-ray density values on increasing Zn²⁺ concentration could be attributed to expansion of the lattice and consequently increasing the unit cell volume.

For the creation of materials with desired qualities, the research on cation dispersion in spinel ferrite is highly helpful. The cation distribution at tetrahedral. Cation distribution refers to the distribution of (A) and [B] sites. The investigation of XRD using the Bertaut method can provide information about the cation distribution in spinel ferrite. Through a comparison between experimentally observed diffraction intensities of fictitious crystal structures with those calculated with a large number, the distribution of cations in spinel ferrite was ascertained. The measured intensity ratios and the theoretically predicted intensity ratios have been compared using this method [28].

$${I}_{hkl}={\left|F\right|}_{hkl}^{2}P{L}_{p}$$

(5)

where the only factor that is dependent on the Bragg diffraction angle (θ) is the Lorentz polarization variable (L_p), P is the multiplicity factor, and F is the structure factor.

$${L}_{p}=\frac{1+{\mathrm{cos}}^{2}2\theta }{{\mathrm{sin}}^{2}\theta \mathrm{cos}2\theta }$$

(6)

The investigated sublattice for a specific spinel compound expands or contracts as the oxygen parameter (u) changes until the A site and B site volume coincides with the ionic radii of the constituent cations. Table 1 provides the cation distribution associated with the spinel ferrite Co_1-xZn_xFe₂O₄ made in this way. Compare observed and estimated intensity ratios for reactions whose intensities (i) are almost independent of the oxygen parameter (u), (ii) in opposing directions change according to the cation distribution, and (iii) do not significantly differ from one other. The reflections that are most appropriate are (440), (220), and (400). Additionally, a value for the oxygen parameter (u) must be assumed in order to determine I_cal. Co²⁺ and Fe³⁺ appear to have a strong B-site in Co_1-x Zn_xFe₂O₄, while Zn²⁺ and Fe³⁺ ions occupy the A sites. This method is valid at 0 K for the calculated integrated intensities. Since the observed values were obtained at room temperature, a proper correction is in theory required for an accurate comparison. However, because spinels are high melting-point compounds, there should not be a significant difference between the thermal vibration of the atoms at ambient temperature and that at absolute zero. As a result, we did not need to compensate for temperature in our intensity computation [29].

The difference in the expansion of octahedral and tetrahedral sites is characterized by a parameter called oxygen parameter (U). In the ideal spinel structure, tetrahedral and octahedral sites are enlarged in the same ratio, and accordingly the distance between the tetrahedral is (000), the oxygen site is 3/8 and the oxygen parameter value in this case is 3/8 (0.375). However, the incorporation of divalent metal ions (Zn²⁺) in tetrahedral sites induced a large expansion of tetrahedral sites, leading to a larger value for U than the ideal value [30]. The results of U listed in Table 1 matched well with the previous explanation.

For the spinel structure, by knowing the ionic radii of the ions occupied the A site (r_A) and the B site (r_B), the theoretical lattice constant (a_th) could be calculated based on cation distribution according to this formula ${({\mathrm{Me}}_{\updelta }^{2+}{\mathrm{Fe}}_{1-\updelta }^{3+})}_{\mathrm{IV}}{[{\mathrm{Me}}_{1-\updelta }^{2+}{\mathrm{Fe}}_{1+\updelta }^{3+}]}_{\mathrm{VI}}{\mathrm{O}}_{4}$ and by using these equations [31, 32]:

$${r}_{A}=xr\left({Zn}^{2+}\right)+\left(1-x\right)r({Fe}^{3+})$$

(7)

$${r}_{B}=\frac{\left(1-x\right)}{2}r\left({Co}^{2+}\right)+\frac{\left(1+x\right)}{2}r({Fe}^{3+})$$

(8)

The ionic radii r (Zn²⁺), r (Co²⁺), and r (Fe³⁺) are given by Shannon [33]. xCo, xZn, and xFe are the ion concentration of Co²⁺, Zn²⁺, and Fe³⁺. The theoretical lattice parameter (a_th) is calculated through Eq. (7) and its values listed in Table 1.

$${a}_{th}=\frac{8}{3\sqrt{3}} {r}_{A-O}+\frac{8}{3} {r}_{B-O}$$

(9)

where r_o represents the ionic radius of oxygen (1.38 A°). Based on the results in Table 1, it is observed that the experimental data were agreed well with the calculated one.

Generally, the distortion occurred in unit cell lattice due to the cation distribution over tetrahedral and octahedral sites for spinel structure could be studied for CFO spinel structure and calculated according to Roderick tolerance factor by using the following equation [33].

$$t=\frac{1}{\sqrt{3}}\left(\frac{{r}_{A}+{R}_{o}}{{r}_{B}+{R}_{o}}\right)+\frac{1}{\sqrt{2}}\left(\frac{{R}_{o}}{{r}_{B}+{R}_{o}}\right)$$

(10)

where r_A, r_B, and R_o are the ionic radii of the A and B cations and the oxygen anion.

In the ideal cubic case, the value of tolerance factor is equal to 1. From Fig. 4 and values of tolerance factor listed in Table 1, we observed that t = 0.99 for CoFe₂O₄ which indicated defect free formation of spinel structure. By increasing Zn concentration, the value of tolerance factor increased. This is attributed to occupation of A-site with cation (Zn²⁺) which has larger ionic radius and this leading to structure distortion.

Fig. 4

FTIR spectra for Co_1-xZn_xFe₂O₄ (x = 0.0, 0.3, and 0.5) nanoparticles

3.1.1 FTIR

As shown in Fig. 4 and Table 2, the FTIR spectra for spinel ferrites in range 390–4000 cm⁻¹ are classified into two ranges. The lower frequency range (ν₂) in range (400: 460 Cm⁻¹) is related to the stretching between oxygen and metallic cation at tetrahedral site and the higher frequency (ν₂) range from (470: 590) Cm⁻¹ corresponding to the stretching between oxygen and metal cation at tetrahedral sites [33,34,35,36]. It is known that the vibrational frequency depends on several factors as the mass of the cation, the distance between the cation and oxygen beside the bonding force, and unit cell parameters. As reported in Table 2, by increasing Zn content from x = 0 to x = 0.5, υ₁ band shifted from 587 to 571 cm⁻¹ and υ₂ band shifted from 401 to 418 cm⁻¹. It could be explained by the insertion of heavier cation Zn²⁺ (Mw = 65.38 g/mol) in tetrahedral site, due to which decrease the bond length between oxygen and metal cation consequently the stretching vibration (υ₁) decreased as well. The frequencies in the band around 3400 Cm⁻¹ attributed to OH group demonstrating absorbed water by the prepared samples [37].

Table 2 The characteristic FTIR peaks for Co_1-xZn_xFe₂O₄ (x = 0.0, 0.3, and 0.5) nanoparticles. All values represent wavenumbers (cm⁻¹)

Table 3 shows force constants k_t and k_o corresponding to tetrahedral and octahedral sites and mean force constant k_m. These values were calculated by using Waldron method [33] as

$${K}_{T}=7.62\times {Mwt}_{1}\times {\nu }_{1}^{2}\times {10}^{-7}(N/m)$$

(11)

$${K}_{O}=10.62\times \frac{{Mwt}_{2}}{2}\times {\nu }_{2}^{2}\times {10}^{-7}(N/m)$$

(12)

$${K}_{AVG}\left(\mathrm{average\;force\;constant}\right)=\frac{\left({K}_{T}+{K}_{O}\right)}{2}$$

(13)

where K_T and K_O are force constant for tetrahedral (A) and octahedral (B) sites, Mwt₁ and Mwt₂ are molecular weights of A and B sites calculating from cation distribution ${({\mathrm{Zn}}_{\mathrm{x}}^{2+}{\mathrm{Fe}}_{1-\mathrm{x}}^{3+})}_{\mathrm{IV}}{[{\mathrm{Co}}_{1-\mathrm{x}}^{2+}{\mathrm{Fe}}_{1+\mathrm{x}}^{3+}]}_{\mathrm{VI}}{\mathrm{O}}_{4}$, and ν₁ and ν₂ are absorption bonds corresponding to A and B sites.

Table 3 Elastic parameters for Co_1-xZn_xFe₂O₄ (x = 0.0, 0.3, and 0.5) such as force constant (K_O, K_T, and K_AVG), longitudinal (${v}_{l})$, transverse (${v}_{t}),$ and mean elastic (${v}_{m})$ wave velocities, Bulk modulus (B), rigidity modulus (R), Young’s modulus (Y), Poisson’s ratio (σ), Debye temperature (${\theta }_{D})$, and lattice energy (${U}_{l})$

The deviation of force constants with Zn content in Table 3 is attributed to the larger molecular weight of Zn as compared to Co and Fe. Hence, the listed increase in mean force constant k_m resulting from replacing Fe and Co ions by Zn ions recommends strengthen of interatomic binding and both bond lengths and cation molecular weight.

Considering elastic properties of ferrites is not only essential for application purposes but improves our thoughtful of the nature of interionic and interatomic forces in the studied material. The elastic constants of any material are important in determination of its response and/or deformation to an applied force. Meanwhile, spinel ferrites are isotropic materials with cubic symmetry, so the elasticity tensor component C₁₁ and C₁₂ are nearly equal. The longitudinal (ν_l), transverse (ν_l), and mean (ν_m) elastic wave velocities, bulk (B), rigidity (R), Young’s modulus (E), Poisson’s ratio (σ), Debye temperature (θ_D), and lattice energy (U_l) were calculated using the following relations:

The elastic stiffness constant (C₁₁):

$${C}_{11}=\frac{{K}_{AVG}}{a}$$

(14)

Bulk modulus (B):

$$B=\frac{1}{3}[{C}_{11}+2{C}_{12}]$$

(15)

Rigidity modulus (R):

$$R={D}_{x}{v}_{t}^{2}$$

(16)

where ${D}_{x}$ is the X-ray density.

$${v}_{t}=\sqrt{\frac{{C}_{11}}{3{D}_{x}}}$$

(17)

Young’s modulus:

$$Y=\frac{9BR}{3B+R}$$

(18)

Poisson’s ratio:

$$\sigma =\frac{3B-2R}{6B+2R}$$

(19)

Longitudinal wave velocity (${\upsilon }_{L})$:

$${\upsilon }_{L}=\sqrt{\frac{{C}_{11}}{{D}_{x}}}$$

(20)

Transverse wave velocity (${\upsilon }_{t})$:

$${\upsilon }_{t}=\sqrt{\frac{{C}_{11}}{3{D}_{x}}}$$

(21)

Mean elastic wave velocity (${\upsilon }_{m})$:

$${v}_{m}={[\frac{1}{3}\left(\frac{2}{{v}_{T}^{3}}+\frac{1}{{v}_{1}^{3}}\right)]}^{-\frac{1}{3}}$$

(22)

Debye temperature of sample (${\theta }_{D}^{*})$:

$${\theta }_{D}^{*}=\frac{hc{v}_{12}}{{K}_{B}}$$

(23)

Lattice energy (${U}_{L})$:

$${U}_{L}=-3.108(Mwt{v}_{m}^{2})\times {10}^{-5}(ev)$$

(24)

where K_AVG is average force constant, a is the lattice parameter, C₁₁ $\approx$ C₁₂ for cubic spinel according to Waldron assumption, C is Poisson’s speed of light, ${K}_{B}$ is Boltzmann’s constant, h is Plank’s constant and ${v}_{12}$ is the average wavenumber, Mwt is the molecular weight of sample, and (${\upsilon }_{m})$ is mean velocity of elestic wave.

All elastic parameters for different Zn contents are calculated and listed in Table 3. It is observed that the elastic parameters increased with the increasing Zn concentration. This may be related to the fact that the elastic moduli depend on the mean force constant which was found to increase with the increasing Zn concentration as mentioned above. Poisson’s ratio σ has constant value equal to 0.35 which means that it is independent on Zn content. It has been stated that Poisson’s value which lies in the range between 1 and 0.5 suggests a good elastic performance and is in agreement with the isotropic elasticity theory [36]. The calculated values of Debye temperature (θ_D) clarified that there is a decrease in its value with increasing Zn content (x) may be attributed to Zn substitution supported lattice vibrations [37]. The difference in elastic moduli for prepared samples is shown in Fig. 5. It is clear that, by increasing Zn concentration, all elastic moduli increased. This behavior is related to the interatomic bonding among several cations in the interior of spinel ferrites.

Fig. 5

Variation of B, R, and Y with Zn content (x) of Co_1-xZn_xFe₂O₄ (x = 0, 0.3, and 0.5) nanoparticles

3.1.2 Surface Study

3.1.2.1 SEM Micrographs

The outcomes of the morphology study of Co_1-xZn_xFe₂O₄ (x = 0, 0.3, and 0.5) nanoparticles from SEM micrographs are displayed in Fig. 6a–c. At x = 0, particles were assumed the form of agglomerated particles, with diameter ranging from 30 to 80 nm (Fig. 6a). The partial replacement of Zn instead of Co, in Co_0.7Zn_0.3Fe₂O₄ and Co_0.5Zn_0.5Fe₂O₄ nanoparticles, directed to the formation of compacted grains with average particle length equals to 170 and 180 nm, respectively. The particle size increased by increasing Zn content owing to the round and small shapes of Zn grains as shown in Fig. 6b, c.

Fig. 6

SEM and histograms of Co_1-xZn_xFe₂O₄: a x = 0, b x = 0.3, and c x = 0.5 nanoparticles

3.1.2.2 Roughness Study

Figure 7a–c exposes the roughness parameters of Co_1-xZn_xFe₂O₄, (a) x = 0, (b) x = 0.3, and (c) x = 0.5 nanoparticles. The roughness parameters such as average, root mean square roughness (R_q), and the maximum height ${(R}_{t})$ are via the given expressions [36].

$${R}_{a}=\frac{1}{l}{\int }_{0}^{l}\left|Z(x)\right|dx$$

(25)

$${R}_{q}=\sqrt{\frac{1}{l}{\int }_{0}^{l}\left|Z(x)\right|dx}$$

(26)

$${R}_{t}={Z}_{p}+{Z}_{v}$$

(27)

where ${R}_{a}$, $l,$ and $Z(x)$ represent the average roughness, sample length, and roughness profile respectively, ${R}_{t}$ is the maximum height, Z_p is defined as the highest profile peak, and Z_v is the lowest depth of the profile valley.

Fig. 7

Surface roughness of Co_1-xZn_xFe₂O₄: a x = 0, b x = 0.3, and c x = 0.5 nanoparticles

As clarified in Fig. 7a–c and Table 4, the roughness parameters were increased by increasing Zn content. For example, the roughness average (R_a) was 35.20 nm at x = 0 and increased to 46.6 nm at x = 0.5. While the surface area has values of 2035 and 2648 µm² for x = 0 and 0.5 respectively. The high values of roughness parameters could be an indication on crystallographic defects in samples. This behavior may be mainly significant for antibacterial and photo catalytic applications.

Table 4 Surface roughness parameters for Co_1-xZn_xFe₂O₄, including roughness average (R_a), root mean square roughness (R_q), a maximum height of the roughness (R_t), maximum roughness valley depth (R_v), maximum roughness peak height (R_p), and surface area (SA)

Magnetic Properties.

The magnetic response in spinel ferrites is due to several parameters like ionic radii, particle sizes, crystallinity, oxygen deficiency, redistribution of the cations, and exchange interactions. [38,39,40]

A vibrating sample magnetometer (VSM) technique was used for studying the magnetic behavior of the synthesized samples at room temperature by using applied field in range of − 4000 to + 4000 Oe. Figure 8 displays the hysteresis plots clarifying the variation of magnetization (M) as a function of the magnetic field (H) for Co_1-xZn_xFe₂O₄ (x = 0, 0.3, and 0.5) nanoparticles. From the data listed in Table 5 we found that as Zn content increases the value of saturation magnetization increased at x = 0.3 and then decreased at x = 0.5. This could be explained by the cation distribution over sublattices. For better understanding of the processes related to the filling of sublattices through the ferrite structure, the value of the calculated effective magnetic moment µ_B (Cal) for the prepared samples was calculated and is listed in Table 5 by using the values of saturation magnetization and the following equation [41]:

$${\mu }_{B}=\frac{{M}_{s}.{M}_{w}}{{N}_{A}.{\mu }_{B}}$$

(28)

where ${M}_{s}$ is the saturation magnetization, ${M}_{w}$ represents the molecular weight of sample, ${N}_{A}$ donates Avogadro’s number, and ${\mu }_{B}$ is Bohr magneton.

Fig. 8

Types of magnetic ordering (collinear magnetic states) [53]

Table 5 Magnetic parameters, including positive and negative saturation magnetization (M_s), coercive field (H_c), squareness ratio (M_r/M_s), effective magnetic moment (µ) the area of hysteresis loop area and the exchange bias field (H_EB), the magnetic anisotropy constant (K), switching field distribution (SDF), the magnetic anisotropy field (H_a), and dM/dH for Co_1-xZn_xFe₂O₄ (x = 0, 0.3, and 0.5)

The variation of magnetic moment (µ_B) with Zn²⁺ concentration x can be explained on the basis of cation distribution and of the strength of the exchange interaction between the ions at tetrahedral (A) and octahedral (B) sites. Zn²⁺ ions with zero magnetic moment have a strong preference to occupy the tetrahedral A sites, and also, Fe³⁺ ions have a stronger preference to occupy the tetrahedral A sites as compared to the octahedral B sites. As zinc is entered in the system, it pushes Fe³⁺ ions from tetrahedral A sites to octahedral B sites. This causes Co_1-xZn_xFe₂O₄'s magnetization to rise. As a result, the magnetic moment of the A site reduces as non-magnetic Zn ions rise in the A site, while the magnetic moment of the B site increases as Fe³⁺ ions increase in the B site. Because of the increased inter-sublattice A-B super-exchange contact between the magnetic ions of the sublattices A and B, total magnetization (M_B-M_A) of Co_1-xZn_xFe₂O₄ NPs increases in the current case as the Zn concentration x grows from 0 to 0.3. Neel’s collinear two-sublattice model and this increase in saturation magnetization with Zn concentration. The saturation magnetization steadily drops when the Zn concentration increases from x = 0.3 to x = 0.5 going forward. The net magnetic moment per formula unit at 0 K is only the difference in sublattice magnetizations due to the antiferromagnetic coupling between the spins on both sides. The magnetic moments of ions on the tetrahedral (A) and octahedral (B) sites are aligned antiparallel to one another, and their spins have a collinear structure, according to Neel’s two-sublattice model of ferrimagnetism. As a result, the theoretical magnetic moment per unit µ_B(x) is defined as where M_B(x) and M_A(x) are the magnetic moments of the B and A sublattices in µ_B, respectively.

$${\mu }_{B}\left(x\right)={M}_{B}\left(x\right)-{M}_{B}(x)$$

(29)

The cation distribution and the ionic magnetic moments of Fe³⁺, Co²⁺, and Zn²⁺ as 5 ${\mu }_{B}$, 3 ${\mu }_{B}$, and 0 ${\mu }_{B}$, respectively, were used to compute the theoretic magnetic moment values, ${\mu }_{B}\left(x\right)$, of the Co_1-xZn_xFe₂O₄ NPs as a function of Zn concentration. It can be observed that both the theoretical magnetic moment “${\mu }_{B} (theo)$” and the experimental magnetic moment “${\mu }_{B}$” grow linearly with Zn content. As seen in Table 5, variation in the saturation magnetization (M_s) with Zn content (x) rises with Zn concentration up to x = 0.3 and then steadily falls with further increase in Zn concentration (x > 0.3). Neel’s collinear two-sublattice model can be used to explain this increase in ${\mu }_{B}$ with Zn concentrations up to x = 0.3. However, for x > 0.3, this model is unable to account for the drop in ${\mu }_{B}$ (and thus Ms) with Zn concentration. On the basis of the three-sublattice model proposed by Yafet and Kittel (Y-K model), it is possible to explain the drop in ${\mu }_{B}$ (and consequently Ms) for x > 0.3 that follows from the presence of the nonlinear spin arrangement in the system. The B lattice can be divided into two sublattices, B₁ and B₂, each of which has magnetic moments of equal magnitude and is oppositely canted at the same angle, a Y-K, with respect to the net magnetization at 0 K, in accordance with the Y-K model. The triangle spin arrangement that results from this is present in the two sublattices B₁ and B₂, and it gets increasingly significant as the concentration changes. By calculating the Y-K angle (aYK), one may observe the presence of canted spin and the behavior of the magnetic moment with rising Zn concentration. In the Y-K model, ${\mu }_{B}$ is determined by

$${\mu }_{B}\left(x\right)={M}_{B}{cos\theta }_{YK}-{M}_{A}$$

(30)

where M_A and M_B are the Bohr magnetons on the A site and B site, respectively, and ${\mu }_{B}$ (x) is the experimental magnetic moment represented in Bohr magneton units. Table 5 lists the values of the Y-K angles for each sample. The magnetization can be described by Neel’s two-sublattice theory for just the sample with x = 0.0 in the current investigation because the Y-K angle is zero for the for the for x = 0. In other words, the CoFe₂O₄ sample exhibits an Neel-type of magnetic ordering. The non-zero Y-K angles for x > 0.0 indicate that Neel’s two-sublattice model cannot explain the magnetization behavior because non-collinear spin structure exists on the B sites, strengthening the B-B interaction while weakening the A-B interaction. The decrease in the A-B exchange interaction and the presence of canted spin arrangements for all of the samples examined in the current study are consistent with the samples with x > 0.0, where the increase in spin canting angles (Y-K angles) with the increase in Zn content suggests an increased preference for triangular spin arrangements on B sites. With x > 0.3, it consequently causes a decrease in Ms and a rise in Zn concentration. This demonstrates that in the current scenario unpredictability and failure increase with increasing Zn content and significantly deviate from the Neel-type collinear magnetic order.

There are three types of magnetic interaction: (a) A-B (J_AB), (b) A-A (J_AA), and (c) B-B (J_BB) interactions. The magnetite of interaction between any two magnetic species depends on different factors such as the distance between the oxygen and these ions and the angle between two magnetic ions depending on the distance between them. Based on the previous discussion, A-B interaction is considered the greatest interaction as it has small distance and great angle value [42]. The resultant magnetic moment is donated by the following equation.

$$M=\left|{M}_{B}-{M}_{A}\right|$$

(31)

where M_A and M_B are the magnetic moment of A and B sublattices.

According to this argument, the saturation magnetization increased at $x$=0.3 because of a partial migration of Fe³⁺ cations to B sites. Leading to A-B exchange interaction became stronger than A-A and B-B interaction and consequently, the net magnetization increased. One uncompensated magnetic moment of Co²⁺ (3 ${\mu }_{B}$) is substituted by two uncompensated Fe³⁺ (5 ${\mu }_{B}$) in the octahedral position [43], while increasing Zn content to x = 0.5 A-B interaction is weaking. As the tetrahedral position is filled with large number of nonmagnetic Zn²⁺ cation leading to spin canting and B-B interaction has greater value and start to establish antiferromagnetic ordering between the magnetic moment in octahedral lattice as clarified in Fig. 9.

Fig. 9

Magnetic hysteresis loops for Co_1-xZn_xFe₂O₄ (x = 0, 0.3, and 0.5) nanoparticles

Relating to the results in Table 5, it is clear that the values of coercivity, remanence, and the squareness ratio follow the same trend of saturation magnetization as their highest value was recorded for x = 0.3 while the lowest values for x = 0.5. Coercivity of any magnetic materials is presenting the demagnetizing force required to reduce the residual indication to zero [44]. Coercivity decrease with Zn concentration can be demonstrated on the base of anisotropy field and the energy of domain wall [45,46,47]. Also, micro-strain, inter-particle interaction, size, shape, and temperature may be factors that the magnetic coercivity depend on [48, 49]. Cation distributions and particle size are parameters that depend on preparation process and affect the magnetic properties like saturation magnetization and coercivity [50].

While the remnant magnetization displays the magnetization left in the media after removing the outside magnetic field, from the values of saturation and remnant magnetization, the squareness ratio (M_r/M_s) can be calculated.

Further, a noticeable hysteresis loop shift is identified and attributed to exchange bias phenomena. The exchange bias field could be expressed as [51]

$${H}_{EB}=\frac{-[H\left(-\right)+H\left(+\right)]}{2}$$

(32)

where $H\left(-\right)$ and $H\left(+\right)$ symbolize the intercepts of magnetization with the –ve and + ve on the field axis. The highest value of H_EB is 2.15 Oe for Co_0.5Zn_0.5Fe₂O₄, while its lowest value is 2Oe corresponded to CoFe₂O₄. This trend could be attributed to the existence of different spin configuration in nanostructure as the magnetic structure of the surface varies from that of the core. On other hand this behavior is assigned to the interaction between the weak ferrimagnetic spins of the surface of the Zn-ferrite grains and the antiferromagnetic spins of their core [52]. This matches with the coreshell model of the grain structure. These magnetic states are represented in Fig. 8 that shows the different magnetic ordering (collinear magnetic states and noncollinear magnetic states): (a) ferromagnet, (b) antiferromagnet and spins oriented along the same line, (d) non-collinear spirals (but coplanar) magnetic spiral state, (e) noncoplanar orders, and (c) adjacent spins form solid angle (Ω) [53, 54].

The anisotropy constant, K (erg/g) as well as anisotropy field (H_a), may be computed via [43].

$$K=\frac{\left[{H}_{c}\times {M}_{s}\right]}{0.96}$$

(33)

$${H}_{a}=\frac{2K}{{M}_{s}}$$

(34)

To better understand the role of magnetic anisotropy, the magnetic anisotropy constant was calculated. The value of the magnetic anisotropy constant depends on coercivity. As a result, its higher value is related to the great resistance of dipoles to undergo annihilation when a reverse magnetic field is applied. Meanwhile, the inferior value of anisotropy constant is attributed to the impact of inter particle interactions causing the relaxation of the magnetization for particles with lower anisotropy [55].

(SFD) switching field distribution can be represented as [55].

$$SDF= \frac{\Delta H}{{H}_{c}}$$

(35)

Here, ΔH is calculated from the halfwidth of the dM/dH curve peak, as SFD represents rectangularity of the H-M loop. It is obvious from Fig. 10 that the derivative curves for all synthesized samples show a double peak behavior, revealing that there is a competition between strong dipolar interaction and exchange coupling. The double peak derivatives are occurred when the dipolar field energy and the energy of the exchange coupling have same order value. The first peak detected before the applied field reached to zero relating to the saturation field; hence, for the prepared samples the dipolar interaction is more dominated. Based on the above discussion, the low value of SDF is owing to the intrinsic magnetic nature as crystallinity as well as substitution uniformity [56]. The last magnetic parameter assessed dM/dH denotes the susceptibility of the substance at room temperature, and theoretically, it is used to differentiate between single- and multi-domain grain structures. For ideal single-domain structure, dM/dH has an infinite value. On the behalf of the results presented in Table 5, dM/dH values at H = 0 were 31, 75, and 76 × 10⁻³ emu/g Oe for x = 0, 0.3, and 0.5, respectively, and the similar trend observed for dM/dH values at H_m. the Co_0.5Zn_0.5Fe₂O₄, has the maximum value, indicating the high magnetic state stability. This is related to the distribution of Co-ferrite magnetic grains inside nonmagnetic Zn-ferrite grains [57] (Figs. 9, 10, and 11).

Fig. 10

Diagram of the magnetic structure of zinc-doped cobalt ferrite [39]

Fig. 11

Magnetic field dependence of dM/dH for Co_1-xZn_xFe₂O₄ (x = 0, 0.3, and 0.5) nanoparticles, including the 2H_m measures of the separation of the forward and the reverse magnetization peaks

3.1.3 Antibacterial Activity

The activity related to the antibacterial for Co_1-xZn_xFe₂O₄ (x = 0, 0.3, and 0.5) was investigated against strains of gram-negative bacteria (E. coli) and gram-positive bacteria (S. aureus) using the modified Kirby-Bauer disc diffusion method. The results displayed that all synthesized samples showed effective antibacterial activity for E. coli as well as S. aureus bacterial strains. The action mode of prepared samples in contrast to bacteria is not entirely understood yet. There are numerous hypotheses that could explain the antibacterial activity related to the examined nanoparticles: (i) creation of reactive oxygen species; (ii) release of Co²⁺, Zn²⁺, and Fe³⁺ ions which change the nature of bacteria proteins by making a bond with sulfhydryl groups; and (iii) attachment of nanosamples on bacteria surface and consequent bacteria damage [58]. The highest inhibition zone of Co_1-xZn_xFe₂O₄ was observed for x = 0.5 as shown in Fig. 12. Its inhibition zone values were 8 and 7.5 mm for E. coli and S. aureus, respectively. While the lowest inhibition zone values were 5.5 and 4.5 for E. coli and S. aureus, respectively, and related to x = 0. Based on the previous interpretation, the antibacterial activity of Co_1-xZn_xFe₂O₄ is predictable to depend on the porosity, grain size, surface structure, oxygen vacancies, and the rate of the degradation. For example, the surface roughness could encourage the chemical interactions on it via atomic and molecular trapping at and nearby the sites of crystallographic defects. All these belongings contribute to growth inhibition of the bacterial [59]. Finally, we concluded that Co_0.5Zn_0.5Fe₂O₄ nanoparticle performs furthermost prospective for the applications related to antibacterial activity. Owing to its unique surface structure dominated by the larger surface roughness, distortion and crystallite size are expected to play a crucial role in letting this interesting antibacterial effect to arise.

Fig. 12

Antibacterial activity corresponding to the inhibition zones around Co_1-xZn_xFe₂O₄ (x = 0, 0.3, and 0.5) after culturing for 24 h

4 Conclusion

Three different compositions of Zn doped Co-ferrites (CoFe₂O₄, Co_0.7Zn_0.3Fe₂O₄, and Co_0.5Zn_0.5Fe₂O₄) were synthesized by using a citrate-auto-combustion method and thermal calcination. XRD pattern confirms the formation of a single-phase spinel structure without any impurities. The crystallite size, lattice parameter, and unit cell volume of the prepared ferrite were increased by increasing the Zn content. FTIR analysis confirms ferrite phase purity. All the elastic moduli for prepared samples increased by increasing Zn concentration. From SEM micrographs, we found that the particle size increased from 55 to 170 nm for x = 0 and 0.5, respectively. Also, the roughness average (R_a) was 35.20 nm at x = 0 and increased to 46.6 nm at x = 0.5, while the surface area has a value of 2035 and 2648 µm² for x = 0 and 0.5, respectively. Based on the results obtained from magnetic study, the magnetic parameters, M_s, M_r, and M_r/M_s, increased by adding Zn to Co_0.7Zn_0.3Fe₂O₄ and then decreased in the Co_0.5Zn_0.5Fe₂O₄ sample. But H_c decreased by adding Zn to investigated samples by about 90% of its value which is an indicator to easy demagnetization for the prepared samples. It was observed that the highest value of H_EB is 2.15 Oe for Co_0.5Zn_0.5Fe₂O₄, while its lowest value is 2Oe corresponding to that for CoFe₂O₄. This trend attributed to the existence of different spin configuration in nanostructure. All the prepared compounds were tested for their bacterial activity against gram-negative and gram-positive bacteria, and they showed their high and promising antibacterial activity.