Effect of samarium doping on the structural, morphological, optical, magnetic, and antibacterial traits of CuFe2O4 nanomaterials

Rohit Jasrotia; Anis Ahmad Chaudhary; Basant Lal; Swati Kumari; Suman; M. Ramya; Hassan Ahmad Rudayni; Chan Choon Kit

doi:10.25259/JKSUS_480_2025

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Research Article

2025

:37;

4802025

doi:

10.25259/JKSUS_480_2025

Effect of samarium doping on the structural, morphological, optical, magnetic, and antibacterial traits of CuFe₂O₄ nanomaterials

Rohit Jasrotia^a,*, Anis Ahmad Chaudhary^b, Basant Lal^c, Swati Kumari^d, Suman^e,f, M. Ramya^g, Hassan Ahmad Rudayni^b, Chan Choon Kit^h

aDepartment of Research and Innovation, Saveetha School of Engineering, SIMATS, Chennai, 602105, Chennai, India

bDepartment of Biology, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh-11623, Saudi Arabia

cDepartment of Chemistry, Institute of Applied Sciences and Humanities, GLA University, Mathura, 281406, India

dSchool of Biotechnology, Shoolini University, Solan, 173229, India

eUniversity Centre for Research and Development, Chandigarh University, Mohali, Punjab, 140413, India

fDepartment of Mathematics, Graphic Era (Deemed to be University), Dehradun, Uttarakhand, India

gDivision of Research and Development, Lovely Professional University, Jalandhar-Delhi G.T. Road, Phagwara, Punjab 144411, India

hFaculty of Engineering and Quantity Surveying, INTI International University, Negeri Sembilan, 71800, Nilai, Malaysia

* Corresponding author E-mail address: rohitsinghjasrotia4444@gmail.com (R Jasrotia)

Received: 2025-03-06, Accepted: 2025-06-25, Epub ahead of print: 2025-08-19, Published: 2025-09-06

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Abstract

The current study aims to fabricate CuSm_xFe_2-xO₄ (x = 0.00-0.02) nanoferrites. The prepared nanomaterials attain a tetragonal structure with a space group of D-I4₁/am. Field emission-scanning electron microscope (FESEM) analysis was incorporated to observe morphology at the surface of the nanoparticles, which confirms the formation of grains with well-defined shape and size. The presence of the six active vibrational modes which further confirms the occupancy of the Cu²⁺, Sm³⁺, and Fe³⁺ ions at interstitial positions. The X-ray photoelectron spectroscopy (XPS) inspection confirms the oxidation states of each element in the prepared samples. The vibrating sample magnetometer (VSM) study predicts the ferromagnetic nature of all prepared nanomaterials. In addition, the CuF1 sample is effective and produced significant zones of inhibition (ZOI) against both Klebsiella pneumoniae and Bacillus subtilis. With excellent magnetic and antibacterial traits, the resulting nanomaterials are efficient for recording media and in biomedical fields. However, due to their good surface properties, the specimens could also be used for photocatalysis.

Keywords

Antibacterial activity

CuFe2O4

Magnetic study

Sm doping

Process innovation

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1. Introduction

In the last few years, nanomaterials have demonstrated their importance in the area of technology because of their excellent physical and chemical traits (Ahmad et al., 2013). For soft ferrites, the magnetic nanoparticles have been employed in research applications (Gul et al., 2020). Due to their excellent microstructural, optical, magnetic, and antibacterial abilities, the nano-dimensional magnetic materials have drawn scientific and commercial interest. Spinel ferrite, a soft magnetic material, is regarded as a significant magnetic material for use in several advanced technologies (Zahid et al., 2023). Its chemical composition is AB₂O₄, where A may be Cu, Co, Ni, Mg, etc. They exhibit excellent traits and have multiple potential applications, including storage devices, wastewater remediation, biomedical, recording media, multi-layer chip inductors, gas sensors, microwaves, high frequency, electromagnets, energy applications, etc (Jasrotia et al., 2020). The closed-packed oxygen lattice that makes up the crystal structure of spinel ferrite is composed of 32 octahedral sites and 64 tetrahedral sites that are partially filled by the metal cations. Among all categories of spinel ferrites, the copper (CuFe₂O₄) spinel ferrite has garnered interest in several research fields because of its excellent semiconducting, magnetic, and antibacterial traits. All these traits of CuFe₂O₄ ferrite, including chemical stability, phase formation, and different morphologies on doping with different transition/non-transition and rare earth metals, have opened a new door for potential research applications. Hence, they have potential applications in various research areas, including wastewater remediation, development of supercapacitor electrodes, carbon dioxide sensing, drug delivery, magnetic storage, recording media, gas sensors, cancer treatment, etc (Masunga et al., 2023a). Many factors influence the various traits and the nature of spinel ferrites, including the synthesis route, type of dopant, calcination and sintering temperature, cation distribution, etc. There are several fabrication techniques for making spinel nanomaterials, like sol-gel auto-combustion (SGAC) (Jasrotia et al., 2025, 2023b), co-precipitation (Jasrotia et al., 2024a), citrate gel combustion (Goud et al., 2024), hydrothermal (Hou et al., 2010; Prakash et al., 2024), solvothermal (Yáñez-Vilar et al., 2009), and solid-state (Mulushoa et al., 2017; Prakash et al., 2025). In the current work, we utilized SGAC rather than the available fabrication routes because it allows control over phase formation, is cheaper and easy to execute, and generates homogenous particles with consistent crystallite/grain size distribution. The SGAC route is classified into two types as metal inorganic and metal organic. The metal inorganic SGAC approach utilized the starting precursors of metal-based chlorides and nitrates, but the metal organic SGAC route utilizes the starting precursors of metal alkoxides. Among these two types, the metal inorganic SGAC pathway is used for the preparation of CuFe₂O₄ ferrites (Jasrotia et al., 2022a).

Many studies have reported on how metal substitutions affect the various traits of copper nanoferrites. Masunga et al., studied the co-precipitation preparation of Sm-doped copper ferrites of composition Sm_xCuFe_2-xO₄, x = 0-0.15. The doped copper ferrites exhibit the spinel cubic phase structure with a saturation magnetization, coercivity, and rentivity of 31.1 to 52.6 emu/g, 30.2 to 58.5 Oe, and 3.52 to 6.91 emu/g, respectively. The doped copper ferrites, on the other hand, exhibit high absorption peaks in the visible light spectrum with a narrow band gap within the range of 1.56 to 1.62 eV. This shows the strong applicability of prepared nanoferrites for visible light based photocatalysis (Masunga et al., 2023a). Priyadharsini et al., reported the hydrothermal route of Cu_1-xNi_xFe₂O₄, x = 0.00-0.05 ferrites for energy storage applications. Structural analysis shows the presence of cubic symmetry with an incline in the crystallite size of the doped nanoferrites. The ferromagnetic nature of the prepared nanoferrites was observed via hysteresis loops, and therefore, all these ferromagnetic and physiochemical traits make them applicable for energy storage and lithium-ion battery applications (Priyadharsini et al., 2024). Samavati et al., reported the co-precitation synthesis of Cu _xCo₁ _−xFe₂O₄ (x = 0.0-1.0) ferrites to investigate the structural and antibacterial properties. It has been observed that the copper doping at the lattice sites of cobalt ferrites improves the antibacterial property of prepared materials (Samavati and Ismail, 2017).

Therefore, based on earlier research studies, we synthesized the samarium-doped copper ferrites of composition CuSm_xFe_2-xO₄ (x = 0.00, 0.01, 0.02) via the metal-inorganic SGAC route. The samarium element was used as a dopant in the synthesis of copper nanoferrites to improve the surface and magnetic properties of nanomaterials. We also reported the structural, optical, antibacterial, and magnetic traits of Sm-doped CuFe₂O₄ nanomaterials.

2. Materials and Methods

2.1 Materials

For the fabrication of CuSm_xFe_2-xO₄ (x = 0.00, 0.01, 0.02) nanoparticles, the AR graded precursors of metal nitrates and citric acid (99%), including copper nitrate (SimSon company, 99%), samarium nitrate (Sigma Aldrich company, 99.9%), and ferric nitrate (SimSon company, 98%) were utilized. Ethylene glycol (SimSon company, 95%) and ammonia solution (Rankem company, 30%) were also used for pH adjustment and gel formation.

2.2 Method for the preparation of CuSm_xFe_2-xO₄ (x = 0.00-0.02) nanomaterials

The Sm substituted copper spinel ferrites were developed using SGAC. The synthesis method started with the preparation of two distinct solutions using predicted stoichiometric amounts of citric acid and all the metal nitrates in 100 mL of distilled water. In the following 3 h, both solutions were subjected to stirring on a hot plate magnetic stirrer until complete dissolution. The metal nitrates’ solution was then put into the solution of citric acid and subjected to continuous stirring at 45°C. To accomplish a neutral pH of 7, the ammonia solution was added. The gel formation was then initiated by adding a stoichiometric amount of ethylene glycol to the solution and stirring at 90°C. At this temperature, the process of auto-combustion occurs, which turns the jelly solution into the black ash material. A mortar pestle was used to crush the resulting ash. In a muffle furnace, the fine powder was calcined, stepwise, at temperature of 800°C for 5 h. Fig. 1 demonstrates the SGAC approach for the development of Sm substituted CuFe₂O₄ nanomaterials.

Scheme for the development of CuSmxFe2-xO4 (x = 0.00-0.02) nanoparticles.

Here, the CuFe₂O₄ (x = 0.00) is named as CuF1, CuSm_0.01Fe_1.99O₄ (x = 0.01) is named as CuF2, and CuSm_0.02Fe_1.98O₄ (x = 0.02) is named as CuF3, respectively.

2.3 Characterization

The detection of crystal structure, phase formation, and crystallite size was reported using the Panalytical’s X’Pert Pro X-ray diffractometer (XRD). The grain size of the prepared copper ferrites was analysed using field emission scanning electron microscopy (FESEM HITACHI, Japan, FESEM SU8010 Series) whereas, the elementary study was reported using the energy dispersive X-ray spectroscopy (EDX). The detection of the stretching vibrations amongst the metal-oxygen (M-O) complexes, Raman active modes, and information regarding oxidation states of each element were reported by using Fourier transform infrared spectrometry (FTIR Perkin Elmer, UV -2450), Raman spectrophotometer (Horiba, Lab RAM HR evolution, with a laser of 785 nm) and X-ray photoelectron spectrophotometer (Thermo Scientific, NEXSA Surface Analysis). Brunauer-emmett-teller (BET) surface area analyzer (Quanta chrome, Autosorb iQ3) was used to analyse the materials’ surface area. In addition, a vibrating sample magnetometer (VSM MicroSense (USA) 2.7 Tesla) was also employed to measure the magnetic traits of the materials at ambient temperature.

2.4 Procedure for testify the antibacterial performance

The antimicrobial activity of produced CuSm_xFe_2-xO₄ (x = 0.00-0.02) nanomaterials was tested using the modified well-diffusion method. The Klebsiella pneumoniae and Bacillus subtilis bacterial strains were used for this investigation. Overnight cultures of each strain were used at 0.5 McFarland standards. Then, 100 µL of the bacterial inoculums were spread on nutrient agar plates using a sterile spreader. Following that, a sterile borer was used to puncture the plates to form 10 mm wells. The bactericidal activity of the samples against both bacterial strains was assessed. Antibiotic ampicillin was used as a positive control. The plates were incubated for 18 to 24 h at 37°C. The tests were attempted thrice. The HiAntibiotic Zone Scale-C was used to measure the inhibition zones.

3. Results and Discussions

3.1 XRD study

The purity, and the crystal structure of Sm doped CuFe₂O₄ nanomaterials were examined using XRD. The room temperature XRD data of prepared CuFe_2-xSm_xO₄ (x = 0.00, 0.01, 0.02) have been depicted in Fig. 2(a). The 2θ peaks at 30°, 30.1°, 34°, 36°, 37°, 44°, 58°, 62°, 64° corresponding to the planes (1 1 2), (2 0 0), (1 0 3), (2 1 1), (2 0 2), (2 2 0), (3 2 1), (2 2 4), and (4 0 0), respectively, were detected from the XRD plots. This confirmed the development of a tetragonal crystal structure having space group D-I4₁/am, which matches with the JCPDS data: 34-0425 (Rathore et al., 2018). The creation of the tetragonal structure can be ascribed to the calcination temperature, as previously stated by multiple investigations (López-Ramón et al., 2018; Modi et al., 2006). Also, exposing the prepared samples from calcining temperature to room temperature is an important factor for the formation of the tetragonal structure (El-Mallawany, 1989). This tetragonal transformation is due to the Jhon-Teller phenomenon of Cu²⁺ ions. The Cu²⁺ ions in the copper ferrite, have a d9 structure with three electrons in the e_g orbitals. As a result, the copper ferrite exhibits more evident John-Teller distortion (Pervaiz and Gul, 2013). Debye-Scherrer’s formula was used to determine the crystallite size of nanomaterials, as stated in Eq. 1.

(1)

D = \frac{0.9 λ}{β \cos θ}

(a) XRD graphs (b) Rietveld refined XRD graphs of Sm doped CuFe2O4 nanomaterials.

where β, θ, and λ represent Full width at half maxima (FWHM) of the respective peaks, the angle of diffraction, and the wavelength of the introduced X-ray source, respectively. The “D” was found to be increasing from 29.41 to 38.89 nm as the doping concentration of Sm increased. As is well known, when bigger ions like Sm³⁺ (0.96 Å) enter the lattice structure of smaller ions like Fe³⁺ (0.65 Å), it causes internal distortion and strain in the lattice. That’s why the crystallite size “D” increase. The lattice parameters were calculated using Eq. (2).

(2)

\frac{1}{d^{2}} = \frac{(h^{2} + k^{2})}{a^{2}} + \frac{l^{2}}{c^{2}}

In which, “d” is inter-planar distance, “a, c” are the lattice parameters, and (h k l) denotes the Miller indices. As noted in Table 1, the values of “a” and “c” decreased from 5.731 to 5.729 Å and 8.674 to 8.326 Å with an increase in the concentration of Sm. This behavior of “a” and “c” was observed because of the replacement of the smaller ions of Fe by the bigger ions of Sm (Himanshi et al., 2025). However, for a more accurate approximation of the purity of samples, we have also done the Rietveld refinement via the Full Prof software. The Rietveld refined XRD plots of prepared samples have been illustrated in Fig. 2(b). The pseudo-Voigt function was employed to understand the peak patterns, followed by subsequent background adjustment to permit cubic and tetragonal interpolation. The estimated values of χ² have been illustrated in Table 1. The values of χ², approaching 1, reveal that all the prepared ferrites are pure (Jasrotia et al., 2022b).

Table 1. Calculated parameters from XRD, W-H and Rietveld refined data of Sm doped CuFe₂O₄ nanomaterials.

Parameters		CuF1	CuF2	CuF3
Crystallite size D (nm)		29.41	30.01	38.89
Lattice Parameters	a=b (Å)	5.731	5.728	5.729
Lattice Parameters	c (Å)	8.674	8.331	8.326
χ²		1.512	1.357	1.079
W-H Plots	Strain	0.0039	0.0022	0.0037
W-H Plots	D_W-H	35.28	62.46	37.85

The Williamson-Hall (W-H) study was utilized for determining the lattice strain and crystallite size of the produced ferrites. Eq. 3 was used to analyse the crystallite size (D_W-H) and strain (ε) produced in the prepared samples as given below.

(3)

β \cos θ = \frac{K λ}{D (W - H)} +   ε (4 \sin θ)

As seen from the W-H plots as shown in Fig. 3, the lattice strain decreased for the CuF2 specimen from 0.0039 to 0.0022, but it again increased to 0.0037 for the CuF3 specimen. This behavior of the lattice strain is responsible for the increase and decrease of the D_W-H values (Jasrotia et al., 2023a). Table 1 shows the calculated values of microstrain and D_W-H.

Hall-William plots of Sm doped CuFe2O4 nanomaterials.

3.2 FESEM, and EDX studies

The FESEM study is carried out for further investigation of the microstructural properties of Sm doped copper ferrites. Fig. 4 contains the FESEM images, grain size histogram plots, and EDX graphs of CuF1 and CuF3 samples. The average grain size for the produced CuF1 and CuF3 samples was calculated using the ImageJ software. The prepared CuF1 and CuF3 ferrites exhibit an average grain size of 397.41 nm and 388.43 nm, respectively. The micrograph of the pure CuF1 ferrite sample clearly demonstrates a strong tendency of fine grains to agglomerate into larger grains. In contrast, the CuF3 sample exhibited a noticeable reduction in grain size, denoting a lower tendency for agglomeration among crystallites. This grain size reduction increases the surface area (effective) of the particles, creating additional active sites for gas-molecule adsorption. Consequently, the Sm doping is expected to significantly enhance the ferrites’ gas sensing traits. As seen from Fig. 4, the EDX analysis shows that the prepared copper ferrites were pure by confirming the existence of Cu, Fe, O, and Sm peaks only. However, in the EDX spectra of CuF₃ sample, the peak of oxygen was not detected due to the instrument error.

FESEM, Grain size and EDX spectra of CuF1 and of CuF3 samples.

3.3 FTIR study

FTIR spectra for the CuFe_2-xSm_xO₄ (x = 0.01, 0.02, and 0.03) ferrites in the scale of 1500 and 350 cm^-1 have been provided in Fig. 5(a). The bonding vibrations of Fe-O complexes at tetrahedral voids are represented by a mode at 600 cm^-1, while the mode at 400 cm^-1 corresponds with the M-O complexes in octahedral voids (El-Mallawany, 1989; Modi et al., 2006). In the observed FTIR spectra, we found a higher frequency band (V₂) and a lower frequency band (V₁) at 538.94 to 543.02 cm^-1 and 414.75-425.02 cm^-1. The band at 1063.12 cm^-1 was detected for all samples. It may correspond to the stretching vibrations of Cu=O. As the concentration of Sm ions increased, the primary M–O mode positions shifted toward the larger frequencies, which can be ascribed to the incorporation of a dopant at the octahedral voids. Using FTIR, we computed the force constant (K) and bond length (R) (Table 2), using Eq. (4) (Ghosh et al., 2009).

(4)

\bar{ν} = \frac{1}{2 π c} \sqrt{\frac{K}{μ}}

(a) FTIR spectra (b) Raman spectra of Sm-doped CuFe2O4 nanomaterials.

Table 2. Calculated parameters from FTIR analysis of Sm doped CuFe₂O₄ nanomaterials.

Parameters	CuF 1	CuF 2	CuF 3
V₁ (cm^-1)	414.75	423.88	425.02
V₂ (cm^-1)	543.02	539.01	538.94
K_o (Ncm^-1)	4.743	4.749	4.973
K_t (Ncm^-1)	8.134	8.146	8.040
R_A (Å)	1.530	1.529	1.506
R_B (Å)	1.278	1.279	1.283

In which “ν” is the wavenumber, “c” is the light velocity, and “μ” is the bond effective mass evaluated via Eq. (5),

(5)

μ = \frac{Mm * Mo}{Mm + Mo}

The “R” is analysed by using Eq. (6) (Modi et al., 2006) as mentioned below.

(6)

R = {(\frac{17}{K})}^{1 / 3}

The “K_t” decreased with an increase in concentration of Sm cations from 8.134 to 8.040 Ncm^-1_, whereas the value of “K_o” increased from 4.743 to 4.973 Ncm^-1, respectively. On the other hand, bond length increases for the octahedral site (R_B), whereas it decreases for the tetrahedral site (R_A) (Table 2).

3.4 Raman study

Fig. 5(b) presents the room-temperature Raman spectra of CuFe₂O₄ ferrites. Based on the group theory, the spinel structure exhibits five distinct Raman modes, while the tetragonal spinel structure is associated with ten Raman modes (Silva et al., 2014a). Larger wavenumber Raman bands in ferrites (600–720 cm^-1) can be ascribed to (M_tet–O) vibrations at A-sites, whereas the lower wavenumber modes (460–660 cm^-1) are correlated with (M_oct–O) vibrations at B-sites (Silva et al., 2014b). In the spectra, six peaks are seen in the Raman spectrum of CuFe₂O₄ ferrites. The values of the Raman active vibrational modes have been illustrated in Table 3. The modes observed align well with the literature on tetragonal copper ferrites. However, slight variations in band positions as compared to the literature can be attributed to the fact that the frequency of phonon Raman bands depends on the particle size, interatomic forces, mass, atomic position, and bond length (Abdellatif and Azab, 2018). It is generally known that the frequency of Raman relies on the Fe(Cu)-O bond length, which changes alongside phase transition or lattice-distortion, cationic redistribution, and ionic radii of ions Fe(Cu) (Ahlawat et al., 2011; Chatterjee et al., 2014; Verma et al., 2013). As a result, the shift of various Raman bands is seen in the synthesized copper ferrites as the Sm concentration increases.

Table 3. Calculated Raman active modes for Sm-doped CuFe₂O₄ nanomaterials.

Raman active modes (cm^-1)	Sample composition
Raman active modes (cm^-1)	CuF 1	CuF 2	CuF 3
T_2g	191.08	189.65	188.20
E_g	278.73	278.36	277.34
T_2g	348.76	350.13	354.93
T_2g	472.29	475.79	474.45
T_2g	534.75	541.68	546.63
A_1g	683.21	684.92	683.26

3.5 XPS study

The XPS method is a sophisticated analytical technique used to analyses the surface properties of materials. The XPS study of the prepared Sm doped CuFe₂O₄ nanomaterials was carried out in the range 0-1200 eV to know about the oxidation state of the elements. The XPS survey for both the CuF1 and CuF3 specimens have been shown in Fig. 6(a) and 6(b). Fig. 7(a-d) confirms the XPS spectra of Fe, Cu, O, and C in the CuF1 specimen. Also, Fig. 8(a-e) shows the XPS spectra of Fe, Cu, O, C, and Sm for the CuF3 sample. The carbon peak is observed at ∼284 for both samples, which is because of the carbon used during the calibration of the instrument. As seen from the plots for the CuF1 sample (Fig. 7(a) & 8(a)), the two main peaks for the Cu2p were observed at 933.20 and 953.19 eV, but for the CuF3, the peaks were observed at 932.84 and 952.74 eV. This confirms the presence of Cu2p_3/2 and Cu2p_1/2, respectively (Kanna et al., 2018, 2017). These peaks and the satellite peaks further confirm the existence of Cu²⁺ ions in the prepared ferrites. Fig. 7(b) & 8(b) illustrate the plots for the Fe2p. The two peaks were observed at 710.07 and 724.03 eV for the CuF1 sample, but for the CuF3 specimen, they were observed at 709.82 and 723.78 eV (Falsafi et al., 2017; Yousaf et al., 2020a). The peaks confirmed the presence of ferric ions in the nanomaterials. Also, the satellite peaks show the presence of Fe²⁺ ions in both specimens (Li et al., 2019). Also, Fig. 7(c) and 8(c) illustrate the O1s spectra for the oxygen binding energies. The peaks were observed at 529.62, 531.15, and 535.14 eV for the CuF1 sample, whereas they were observed at 529.40, 531.19, and 533.49 eV for the CuF3 specimen. These peak positions are associated with oxide, oxide defects, and water present in the prepared ferrites (Fan and Goodenough, 1977). The lower binding energy peak of O1s is due to the migration of O²⁻ ions on its lattice sites, whereas the more intense peak describes the vacant oxygen sites and the loss of the bound oxygen ions (Fan and Goodenough, 1977). Fig. 7(d) and 8(d) represent the spectra for C1s binding energies. The peaks were observed at 284.67, 286.37, and 288.36 eV for the CuF1 sample and at 284.51, 286.28, and 288.54 eV for the CuF3 specimen. The presence of these peaks is associated with the C-C/C-H, C-O, and O-C=O, correspondingly. However, this may be due to the usage of citric acid (C₆H₁₀O₈) during the process of synthesis and due to calibration of the instrument (Lopez-Santiago et al., 2012). However, due to the spin-orbital interaction, the Sm3d peak splits into two peaks, i.e., Sm3d_5/2 and Sm3d_3/2, with a delta energy of 30 eV. Fig. 8(e) illustrates the XPS plot of Sm3d. The two peaks are observed at 1079.06 and 1109.79 eV, and all these peaks are associated with the Sm3d_5/2 and Sm3d_3/2, respectively. This further confirms that the Sm is present in the +3 state in the CuF3 sample (Yousaf et al., 2020b; Zhang and Wen, 2012). The existence and oxidation states of elements in the produced ferrites were confirmed by these data, which offer important insights into the chemical states of the ferrites. The calculated parameters resulting from XPS data of the Sm-doped CuFe₂O₄ nanomaterials have been depicted in Table 4.

Full XPS survey of (a) CuF1 (b) CuF3 nanomaterials.

XPS spectra of (a) Cu2p (b) Fe2p (c) oxides (d) carbon for the CuF1 sample.

XPS spectra of (a) Cu2p (b) Fe2p (c) oxides (d) carbon (e) Sm3d for the CuF3 sample.

Table 4. Overall calculated parameters from the XPS analysis of Sm-doped CuFe₂O₄ nanomaterials.

Elements	Indexed elemental state	Binding energy (CuF 1)	Binding energy (CuF 3)
Copper (Cu)	2p_3/2	933.20	932.84
Copper (Cu)	2p_1/2	953.19	952.74
Iron (Fe)	2p_3/2	710.07	709.82
Iron (Fe)	2p_1/2	724.03	723.78
Oxygen (O)	Oxide	529.62	529.40
	Oxide defects	531.15	531.19
	water	535.14	533.49
Carbon (C)	C-C/C-H	284.67	284.51
	C-O	286.37	286.28
	O-C=O	288.36	288.54
Samarium (Sm)	3d_5/2	-	1079.06
Samarium (Sm)	3d_3/2	-	1109.79

3.6 BET study

Utilizing the N₂ isotherm, which is depicted in Figs. 9(a) and 9(b), the specific surface area of CuF1 and CuF3 samples were determined. Both specimens display the hysteresis loops at relative pressure (P/P₀), which is getting closer to one, as can be seen from the graphs. This type of phenomenon observed from the hysteresis loops confirms the presence of mesopores. According to IUPAC nomenclature, these are the type IV isotherm (Manohar et al., 2023; Somvanshi et al., 2020). Using the BET investigation, we calculated the surface area of both the pristine CuF1 and doped CuF3 specimens, and it was found to be 1.653 and 2.206 m²/g. As one can see that the surface area increases with the addition of Sm doping of the pure CuFe₂O₄ ferrites. Increasing the surface area causes an increase in the number of active sites. So, due to the increasing active sites in the doped CuF3 specimen, it can act as a good catalyst for the catalytic reaction to occur and for gas sensing applications (Ahmed et al., 2024; Balakumar et al., 2024). The pore diameter of the prepared copper materials was evaluated by the Barrett-Joyner-Halenda (BJH) approach, which concludes that it is also increasing from 2.47 to 2.91 nm with Sm doping. The pore diameter plots of the CuF1 and CuF3 samples have been shown in Figs. 9(c) and 9(d). This confirmed that the prepared ferrites were good candidates for catalytic and water purification applications (Qin et al., 2023).

(a & b) The N2 adsorption-desorption isotherms, and (c & d) Pore diameter of CuF1 and CuF3 samples.

3.7 VSM study

The magnetic property of copper ferrites as reported at ambient temperature using the VSM equipment with a magnetic field of ±20 KOe, as exhibited in Fig. 10(a). The computed values of the magnetic factors, including the remanent magnetization (M_r), saturation magnetization (M_s), anisotropy constant (K), squareness ratio (SQR), coercivity (H_c), and magnetic moment (η_β), have been mentioned in Table 5. Fig. 10(b) gives the zoomed-out view of M-H loops of all prepared samples. As we can see from Fig. 10(b), all the synthesized materials showed S-shaped loops with higher values of coercivity, which confirmed the ferromagnetic nature. Fig. 10(c) exhibits the alteration of the different magnetic factors (i.e., H_c, K, n_β, M_s) with the increase in the Sm doping. To get the average value of M_s, the law of approach is used by graphing the curve between the factors, i.e., M_s and 1/H_c², as depicted in Fig. 10(d). The M_s increases from 13.02 to 35.95 emu/g at low Sm doping (x = 0.00-0.01) and decreases with more addition of Sm (x = 0.02) to 21.77 emu/g. It is well known that the M_s will be influenced by the cation interaction on both the octahedral and tetrahedral sites. So here we substituted bigger cations with bigger ionic radii (Sm³⁺ = 0.96 Å) into the smaller cations (Fe³⁺ = 0.65 Å), which produce the crystal deformation and further cause the misalignment of paired and unpaired electrons, ultimately increasing the value of M_s at the low Sm doping (Masunga et al., 2023b). But with further increase in Sm doping, the CuF3 specimen showed a decline in M_s, which is attributed to the crystallite size. Also, one more factor that could be the reason for a decrease in M_s is the spin canting effect. This effect is produced when a larger part of Sm³⁺ ions contributes to Fe³⁺ ions at the octahedral site, which can also decrease the overall M_s value. The overall magnetization was calculated using Eq. (7) (Sharma et al., 2024), as given below.

(7)

N_{μ} = M_{B} - M_{A}

(a) M-H loops (b) Zoom view of Hc and Mr (c) Variation of magnetic parameters (Ms, Hc, K, nβ) as a function of Sm doping (d) M Versus 1/H2 plots of prepared copper nanomaterials.

Table 5. Magnetic parameters calculated from hysteresis loops of Sm doped CuFe₂O₄ nanomaterials.

Sample composition	M_s (emu/g)	M_r (emu/g)	H_c (Oe)	K (erg/Cm^-1)	SQR	η_β	H_M (Oe)	dM/dH (emu/g. Oe) × 10^-3
Sample composition	M_s (emu/g)	M_r (emu/g)	H_c (Oe)	K (erg/Cm^-1)	SQR	η_β	H_M (Oe)	H∼0	H∼H_M
CuF1	13.02	6.22	662.23	4311.12	0.478	0.56	700	5.18	12.32
CuF2	35.95	17.76	687.73	12361.95	0.494	1.55	700	13.86	34.64
CuF3	21.77	11.21	991.22	10789.43	0.515	0.94	1000	5.52	16.22

Here, M_B and M_A give the magnetization at the B- and A-sites. However, the H_c increases with the addition of Sm content from 662.23 to 991.22 Oe. This behavior of coercivity is observed due to the stability of spin-orbital coupling. In case of ferrites, the magnetic anisotropy is controlled by the spin-orbital coupling, and therefore, the H_c of the doped ferrites relies on the anisotropy. This means that higher the value of magnetic anisotropy, higher will be the coercivity (Sharma et al., 2021). The magnetic anisotropy constant (K) was evaluated via Eq. (8) (Jasrotia et al., 2024b) as given below.

(8)

K = (M_{s} . H_{c}) / 2

With the increasing Sm substitution, “K” is seen to be increasing from 4311.12 to 10789.43 emu/g. Oe. Also, M_r shows a similar trend as M_s. The remanent magnetization increased for the CuF2 sample from 6.22 to 17.76 emu/g, and after that, it decreased to 11.21 emu/g. This behavior was attributed to the reduction of defects and distribution of the cation on A- and B-sites. In addition to this, other parameters (i.e., n_β & SQR) were determined using the following relations as given below.

(9)

SQR = M_{r} / M_{s}

(10)

n_{β} = (M . M_{s}) / 5585

Here, M describes the molecular mass. The n_β directly depends upon the values of M_s. So, the observed n_β shows a similar trend to M_s. Also, the SQR values were calculated using Eq. (9). It was observed that the SQR value for the CuF1 and CuF2 samples was below 0.5. This shows that the pure and low Sm-doped copper ferrites attained the multi-domain structure. The SQR for CuF3 sample is crossing 0.5, which means that it is attaining the single domain structure and a more anisotropic nature. The magnetic behavior is also explored and confirmed using the dM/dH study. The dM/dH plots for the prepared specimens have been shown in Fig. 11. Here, 2H_M denotes the separation between two peaks, and H_M shows the applied field at which the maximum dM/dH value was observed. As noted from the plots and the computed parameters, all samples are trying to attain single domain magnetic behavior, as the values of H_c and H_m are virtually similar for all samples. Also, the observed values of magnetic factors, i.e, M_s, H_c, and SQR, also show that the copper ferrites are useful in recording media, sensing, catalytic, and biomedical applications (Saikova et al., 2023).

dM/dH plots for Sm doped CuFe2O4 nanomaterials.

3.8 Antibacterial study

Antimicrobial analysis was performed by using the well diffusion method on the nutrient agar plates against the bacterial strains. The inhibition zones were measured by taking the prepared nanoparticles and ampicillin in different wells. Ampicillin is used as a positive control and in the center of the plate. Inhibition zones around the samples were encircled. Three samples were used in this research, i.e., CuF1 (1), CuF2 (2), and CuF3 (3). The antimicrobial effects of the prepared nanoparticles for the Gram-positive and Gram-negative bacteria were found to be effective. The zones of inhibition (ZOI) were calculated (in mm) using a ruler. All experiments were performed in triplicates. The antibiotic (positive control) shows the inhibition zone for both bacterial strains in the center of each well plate. The diameters of inhibition zones (in mm) of varying sizes have been summarized in Table 6. The ZOI for the CuF1, CuF2, and CuF3 samples have been illustrated in Fig. 12, respectively. In Table 6, it is clearly shown that the CuF1 sample is effective and produced significant ZOI in this assay against both bacterial strains. The CuF2 sample possesses no antibacterial activity on the Klebsiella pneumoniae but shows a more observable inhibition on Bacillus subtilis. However, the CuF3 sample showed no ZOI against any bacterial strain.

Table 6. Inhibition zones of Sm-doped CuFe₂O₄ nanomaterials against Klebsiella pneumoniae and Bacillus subtilis.

Bacteria	CuF1	CuF2	CuF3	Positive control
Klebsiella pneumoniae	28 mm	_	_	33 mm
Bacillus subtilis	25 mm	29 mm	_	35 mm

Antimicrobial effect of Sm-doped CuFe2O4 nanomaterials on (a) Klebsiella pneumoniae and (b) Bacillus subtilis .

The CuFe₂O₄ nanoparticles demonstrated strong antibacterial activity against the different bacterial strains and were found to be the most resistant and sensitive. To increase the reactivity of nanoparticles, the copper ferrite with a large surface area caused the electronic interactions. Antibacterial actions are thought to appear in a variety of ways. It has been shown that the bactericidal nature of nanoparticles is based on and is proportional to the release of ions. Ions connect to the cell membrane’s surface and then pierce the bacteria. After penetration of the cell membranes, the generation of reactive oxygen species (ROS) will occur. The most significant of many characteristics that contribute to the bactericidal activity of nanoparticles is their capacity to produce ROS. The ROS increases, which in turn can damage the vital biomolecules (proteins, DNA, lipids), membrane interaction, ATP depletion, and cause cell death. The diagrammatically antibacterial action of ferrites has been shown in Fig. 13.

Mechanisms of antibacterial activity of the prepared copper ferrites.

4. Conclusion

In the current study, CuSm_xFe_2-xO₄ (x = 0.00-0.02) ferrites were fabricated using SGAC. The XRD study revealed the formation of a tetragonal structure with D-I4₁/am. The crystallite size increased from 29.41 to 38.89 nm. The FESEM images showed the well-defined cubic, spherical, and aggregated grain shape, with an average grain size of 397.41 and 388.43 nm for the CuF1 and CuF3 samples, respectively. Two band positions in the wavelength ranges of 414.75-425.02 cm^-1 and 538.94-543.02 cm^-1 were found from the FTIR spectra of the produced samples. This confirms the M-O complexes stretching vibrations at the interstitial sites. With the addition of Sm into the pure CuFe₂O₄ ferrite, there is an increment in the specific surface area of the prepared samples from 1.653 to 2.206 m²/g. This helps in increasing the number of active sites at the surface of copper nanomaterials, which makes them beneficial for catalytic and sensing reactions to occur. From the magnetic study, it is observed that the low Sm doping helps in the enhancement of the magnetic property of the prepared samples, but at high Sm doping, there is a decrease in the magnetic property. Of all samples, the pure CuF1 sample was effective and produced significant ZOI against both the Gram -ve and Gram +ve bacterial strains. Therefore, due to the high surface area, high magnetic factors, and excellent antibacterial activity, the prepared pure and doped copper nanomaterials are highly useful for catalytic, sensing, and biomedical applications to occur.

Acknowledgement

This work was supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University (IMSIU) (grant number IMSIU-DDRSP2501).

CRediT authorship contribution statement:

Rohit Jasrotia: Writing-original draft, supervision, review and editing, investigation, synthesis, software, visualization. Anis Ahmad Choudhary: Resources and Funding. Basant Lal: Resources. Swati Kumari: Investigation. Suman: Resources. M. Ramya: Resources. Hassan Ahmad Rudayni: Funding and Characterization. Chan Chhon Kit: Funding and Characterization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Declaration of Generative AI and AI-assisted technologies in the writing process

The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript and no images were manipulated using AI.

Funding