Novel Cu-Fe codoped NiO nanocrystalline semiconductors with superior room-temperature ferromagnetism and high dielectric performance for spintronic devices

2.1 Materials

The chemical substances, including Ni(NO₃)₂·6H₂O (Sigma Aldrich, 99.99%), Cu (NO₃)₂·3H₂O (Sigma Aldrich, ≥ 99.9%), and FeCl₂·4H₂O (Sigma Aldrich, 99.0%), were used to prepare the required samples.

2.2 Synthesis

The well-known coprecipitation method was used to synthesize NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O nanopowders at room temperature. Firstly, 500 mL of 2 M NaOH solution was prepared to be used in the precipitation process of different cations. As represented in Table 1, precise quantities of Ni (NO₃)₂·6H₂O, Cu (NO₃)₂·3H₂O, and FeCl₂·4H₂O were dissolved into 100 mL of deionized water in different beakers to obtain the required composition for each sample. The dissolved substances in these beakers were stirred on a magnetic stirrer for 60 min. The precipitates formed after the NaOH solution was gradually added using a graduated glass burette tube while the PH was monitored until it reached 9. By thoroughly washing the precipitates with deionized water numerous times, the unwanted dissolved contaminants, such as sodium ions, are eliminated.

The precipitate that had been formed was separated from the solution through centrifugation and subsequently rinsed with deionized water to eliminate any remaining ions. In order to achieve fine powders, the precipitates were first ground by hand using a mortar and pestle in a drying furnace set at 110°C for 12 h. They were then calcined in an electric furnace set at 600°C for 5 h. The samples are left in the furnace until they come to room temperature after the furnace is turned off. Following that, various physical methods are employed to verify the compositions and describe their characteristics. The preparation process has been schematically diagrammed in Fig. 1.

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Fig. 1.

The schematic diagram covers all steps for the preparation procedure, chemical compositions, and documented parameters

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2.3 Measurements and technical characterization devices

To investigate the purity and phase composition of the synthesized NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O nanopowders, XRD was performed using an XRD PANalytical device (model X′Pert PRO). Scanning (JEOL JEM-2100) and transmission (TEM, JEOL JX 1230 instrument, Japan) electron microscopes were employed to examine the particle size, shape, and surface morphology of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O nanopowders. Samples were analyzed for surface chemical oxidation states using an X-ray photoelectron device (XPS, Thermo Fisher Scientific, USA). The LCR Hi-TESTER 3532-50 device (applied voltage 5 V) was used to measure the frequency of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O specimens at RT in relation to their ac electrical conductivity, dielectric loss, and dielectric constant. The NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O powders were formed into pellets with a diameter of 0.9 cm and a thickness of 0.3 cm for conducting electrical measurements. For 4 hours, the manufactured pellets were sintered at 550°C. A silver contact was used to create the electrical connection between the pellet’s two sides. Magnetic hysteresis loops of the NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O nanopowders were recorded using a vibrating sample magnetometer (VSM, LakeShore 7410), by measuring the magnetization as a function of the applied magnetic field.

3.1 XRD investigation

The crystallinity and phase structure of The NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O nanopowders were characterized using XRD, as shown in Fig. 2. All samples exhibited sharp and well-defined diffraction peaks that were clearly indexed to the cubic NiO phase planes (111), (200), (220), (311), and (222) (space group Fm-3m, JCPDS card no. 47-1049). The absence of secondary peaks related to possible Ni, Cu, or Fe oxides confirmed the high purity and single-phase nature of the synthesized materials. As evident from Fig. 2, the XRD peaks of pristine NiO appear sharper, whereas they become broadened after doping with Cu and co-doping with Cu-Fe ions, suggesting a reduction in crystallite size. MAUD software was used to calculate the lattice parameter a (where a = b = c for cubic symmetry) and analyze the impact of Cu and Cu-Fe ions on the unit cell volume (V = a³), as illustrated in Fig. 3.

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Fig. 2.

NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O XRD patterns

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Fig. 3.

XRD refinement patterns of samples (a) Ni^0.95Cu^0.025Fe^0.025O, (b) Ni_0.95Cu_0.05O, and (c) NiO using MAUD software

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As shown in Table 2, the lattice parameter and, consequently, the unit cell volume increased by 0.12% and 0.36%, respectively, upon Cu doping (to 4.181 Å and 73.087 ų) but decreased by 0.05% and 0.85% when co-doped with Cu²⁺-Fe³⁺ (to 4.174 Å and 72.205 ų) relative to pure NiO. This trend can be attributed to the variation in ionic radii: Ni²⁺ (0.69 Å), Cu²⁺ (0.73 Å), and Fe³⁺ (0.645 Å) in octahedral coordination. Although Fe³⁺ has a smaller radius than Cu²⁺, its incorporation alongside Cu²⁺ causes a lattice contraction due to synergistic charge compensation: Fe³⁺ substitution for Ni²⁺ introduces excess positive charge, promoting V_O formation and partial Ni²⁺ → Ni³⁺ oxidation. Both mechanisms reduce lattice volume, as V_O relaxes local strain and Ni³⁺ (0.56 Å) further contracts the lattice relative to Ni²⁺. The phase purity and homogeneity of all samples were confirmed by Rietveld refinement of XRD patterns (Fig. 3), yielding low R-factors and χ² values. In Fig. 4, we present an illustration of the packing crystal structure of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O compositions.

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Fig. 4.

Pure, Cu-, and Cu-Fe-codoped NiO powder nanoscale packing.

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The Scherrer equation was used to estimate the crystallite size (t) by applying the Bragg angle (θ) and full width at half maximum (β) of the diffraction peaks related to the (111), (200), (220), (311), and (222) planes (Luu et al., 2024):

Where K = 0.9 (shape factor) and λ = 0.15406 nm (Cu Kα radiation). Using this method, the average crystallite sizes of the NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O samples were found to be 23.14 nm, 18.16 nm, and 10.51 nm, respectively. These results clearly demonstrate that codoping with Cu and Fe significantly enhances lattice strain and suppresses grain growth, resulting in a finer nanostructure, which is highly beneficial for improving the magnetic and dielectric characteristics of DMS based on NiO.

3.2 Morphological, compositional, and size analysis

The synthesized NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O powders were examined using EDX instruments and SEM, TEM to determine their surface morphology, particle shape, size distribution, and chemical elemental composition. The images of SEM in Fig. 5 and TEM in Fig. 6 analysis of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O samples, which clearly illustrate that the synthesized powders are composed of quasi-spherical particles with a homogenous surface shape. The distribution histograms of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O samples obtained by using ImageJ software mean sizes D of 23.14, 18.16, and 10.51 nm, respectively, Fig. 7. Particle size decreases due to lattice deformation and the suppression of grain growth by the dopant ions. When Cu and Fe ions are introduced to the NiO lattice during synthesis, they disrupt crystallite formation by increasing strain and altering the local chemical environment (Hassanzadeh-Tabrizi, 2023). This method not only diminishes particle aggregation but also yields smaller, well-faceted, uniform nanoparticles. This progressive reduction in particle size can arise from three main synergistic mechanisms that collectively suppress crystallite growth. First, the lattice strain induced by the mismatch between host (Ni²⁺) and dopant ionic radii (Cu²⁺, Fe³⁺) distorts lattice periodicity during crystallization, inhibiting coherent growth (Liu et al., 2022). Second, dopant segregation at grain boundaries can reduce the boundary mobility and acts as a kinetic barrier to atomic diffusion, thereby suppressing Ostwald ripening (Meng et al., 2023). Third, the presence of dopants increases solution supersaturation during precipitation, elevating nucleation rates and favoring the formation of a higher density of smaller crystallites rather than the growth of existing particles (Thanh et al., 2014). The elemental composition of all samples was analyzed using Energy Dispersive X-ray (EDX), as illustrated in Fig. 8. The EDX analysis of a pure NiO sample verifies the exclusive presence of nickel and oxygen elements. For the Ni_0.95Cu_0.05O sample, the EDX pattern showed peaks for Ni, O, and Cu elements, while the EDX pattern of Ni_0.95Cu_0.05Fe_0.025O powder contains the elements of Ni, O, Cu, and Fe. The weight percentage of Cu dopant inside the Ni_0.95Cu_0.05O sample was estimated to be 4.13 wt%. For the Ni_0.95Cu_0.025Fe_0.025O sample, the detected weight percentages of Cu and Fe dopants are 1.97 and 2.24 wt%, respectively. The obtained wt% % of the dopant ions is acceptable within the detection error of EDX analysis. These findings confirm that the synthesis procedure and the chemicals utilized resulted in almost the exact chemical structures that were intended.

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Fig. 5.

SEM of pristine, Cu, and Cu-Fe codoped NiO nanopowders.

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Fig. 6.

TEM of pristine, Cu and Cu-Fe codoped NiO nanopowders

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Fig. 7.

Histograms of particle size for pure, Cu, and Cu-Fe co-doped nanosized NiO powders. D denotes the mean crystallite size, whereas S_D signifies the standard deviation, reflecting the extent of size dispersion within each sample. Narrower standard deviation values S_D indicate more uniform particle sizes, as in Cu-Fe codoped, whereas larger standard deviation values signify increased variability in nanostructure dimensions, as in pure NiO

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Fig. 8.

(a-c) EDX analysis of pristine, Cu, and Cu-Fe codoped NiO nanoparticles.

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3.3 Surface oxidation state: XPS analysis

The elemental oxidation states and chemical composition of the produced Cu-Fe codoped NiO nanoparticles were determined by XPS analysis. Fig. 9 demonstrates the XPS survey scan spectrum of Cu-Fe codoped NiO nanoparticles, which detects the existence of nickel (Ni), oxygen (O), copper (Cu), and iron (Fe) elements in this composition without observing any impurities. Before analysis, background subtraction was performed using the Shirley method to remove inelastic scattering, and peak deconvolution was carried out using a mixed Gaussian–Lorentzian function to resolve overlapping peaks and assign chemical states with higher accuracy. Fig. 10(a) shows the high-resolution scan spectrum of Ni 2p gives binding energy peaks at 856.92, 859.41, 863.23, 866.4, 874, 876.14, and 881.27 eV related to Ni²⁺ of NiO and satellite, shakeup structure in agreement with previous results (de Brito et al., 2024; Rahman et al., 2018; Thakur et al., 2024). As shown in Fig. 10(b), the scan spectrum of high resolution XPS of O 1s of Cu-Fe codoped NiO nanoparticles reveals the presence of three binding energy peaks at 530.85, 532.61, and 534.33 eV, which are indexed to lattice oxygen and defect state (oxygen vacancy) and chemisorbed oxygen on Cu-Fe codoped NiO nanoparticles, respectively (Zhang et al., 2018). The defect-state peak at 532.61 eV confirms the presence of oxygen vacancies, which are known to enhance exchange interactions and promote RFTM in oxide-based DMS systems (Deák et al., 2010; Singh et al., 2012, 2011). For Cu dopant, Fig. 10(c), the scan spectrum of high-resolution XPS of Cu 2p state gives binding energy peaks at 935.94, 938.55, 943.42, 497.06, 954.58, and 957.34 eV, which are attributed to the oxidation states of +1 and +2 for Cu ions inside Cu-Fe codoped NiO nanoparticles (Wang et al., 2025; Yue et al., 2025). The coexistence of Cu+ and Cu2+ oxidation states suggests partial charge transfer between Cu and the NiO lattice, which can further promote oxygen vacancy formation for charge compensation. As illustrated in Fig. 10(d), the binding energy peaks at 710.50 eV, 717.28, and 725.28 eV are assigned to Fe³⁺ p_3/2, satellite emission, and Fe³⁺ p_1/2, indicating that Fe ions were incorporated as Fe³⁺ inside Cu-Fe codoped NiO nanoparticles (Yamashita and Hayes, 2008). The substitution of Fe3+ for Ni2+ likely generates additional oxygen vacancies to maintain charge neutrality, further supporting the O 1s analysis and linking structural defects to the observed enhancement in both dielectric and magnetic properties.

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Fig. 9.

XPS survey spectrum of Cu-Fe codoped NiO nanoparticles.

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Fig. 10.

High-resolution XPS spectra of (a) Ni 2p, (b) O 1s, (c) Cu 2p, and (d) Fe 2p for Cu–Fe codoped NiO nanoparticles.

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3.4 Properties of dielectrics

The equations employed to determine the parameters of dielectric constant (ε′), dielectric loss (ε′′), and ac electrical conductivity (σ, Ω^-1cm^-1) are presented as follows (Althubiti et al., 2023; Sedky et al., 2023):

The terms “C”, “d”, “A”, “ε₀”, “tanδ”, and “f” used in the above equations are related to capacitance, thickness of the used pellet, area of the pellet, permittivity of a vacuum, loss tangent, and the corresponding applied frequency. For evaluating the dielectric behavior of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O specimens, the frequency-dependent dielectric constant is shown in Fig. 11, and the dielectric loss is plotted in Fig. 12. As illustrated in Fig. 11, the dielectric constant values of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O samples decrease with increasing frequency, and small dielectric constant values were observed in the higher-frequency region. In the low-frequency domain, however, the specimens demonstrate the maximum dielectric constant values. For pure NiO, the dielectric constant reaches nearly 10³ at low frequencies, a phenomenon attributable to interfacial polarization mechanisms, and it gradually diminishes with increasing frequency due to the diminished influence of dipolar and space charge polarization (Gokul et al., 2013). Interestingly, both Ni_0.95Cu_0.05O and Ni_0.95Cu_0.025Fe_0.025O samples show dielectric constant values above 10³. Specifically, the Ni_0.95Cu_0.05O sample approaches 10⁴, while the Ni_0.95Cu_0.025Fe_0.025O sample approaches 10⁵ in the low-frequency range. As shown in Table 3, the dielectric constant values of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O specimens at specific frequencies are illustrated. Fig. 11 illustrates that the Ni_0.95Cu_0.05Fe_0.025O sample exhibits the maximum dielectric constant, highlighting its promise for dielectric energy-storage uses (Dhavala et al., 2023; Moualhi et al., 2024).

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Fig. 11.

The dielectric constant of pure, Cu-doped, and Cu–Fe codoped NiO vs frequency-dependently.

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Fig. 12.

The dielectric loss of pure, Cu-doped, and Cu–Fe codoped NiO vs. frequency-dependently.

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According to these measurements, doping NiO with Cu ions or codoping it with Cu-Fe ions is a significant method of raising the dielectric constant values. The well-established Maxwell-Wagner model is a well-established theoretical approach that explains how the dielectric constant for oxide-based compositions explains the dependence of dielectric constant on frequency and temperature (Amir et al., 2024; Dakhel, 2013; Li et al., 2016; Mingmuang et al., 2022). The Maxwell-Wagner model posits that dielectric oxide materials comprise highly resistive grain boundaries (regions of low conductivity) and low-resistive grains (regions of high conductivity). When an external alternating field is applied, charge carriers traverse the low-resistive grains while accumulating at the high-resistive grain boundaries. The aggregation of charge carriers at the interfacial and grain boundaries produces interfacial polarization, which results in a higher dielectric constant at low frequencies. The dielectric constant (relative permittivity) of the NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O samples decreases with increasing frequency, particularly at high values, since the charge carriers are unable to keep pace with the alternating external field. The dependence of the dielectric loss of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O samples on frequency has been depicted in Fig. 12. The dielectric loss curves for all samples exhibit analogous behavior to the dielectric constant, specifically decreasing with the rise in applied frequency. It is also observed that the dielectric loss of Ni_0.95Cu_0.05O and Ni_0.95Cu_0.025Fe_0.025O is consistently higher than that of pure NiO across the whole frequency range.

In Fig. 13, the frequency dependence of the ac conductivity of NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O samples is shown. For all samples, the measured ac electrical conductivity rises with increasing frequency and is almost constant at low frequencies. In the NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O samples, the highly resistive grain boundaries have a significant influence, as confirmed by the weak ac conductivity at low frequencies. Moreover, the linear behavior at low frequencies suggests that the conduction is due to small polarons, which are related to the localized electrons in 3d-orbitals of Ni 2p. At elevated frequencies, the energy of the polarons escalates, enabling them to surmount the effects of grain boundaries. This allows for greater mobility inside the crystalline grains, which are more efficient in promoting charge transport, resulting in a significant enhancement of ac electrical conductivity. The ac conductivity curves exhibit two regions; at low frequencies, the first region corresponds to dc electrical conductivity, while the second region shows an exponential rise in ac electrical conductivity with the applied frequency, resulting in an approximately constant loss (Al Boukhari et al., 2020). According to the curves in Fig. 13, the ac electrical conductivity increases with co-doping, especially with Cu-Fe dopants. The ac electrical conductivity of the Ni_0.95Cu_0.025Fe_0.025O sample is higher than that of the single-doped Ni_0.95Cu_0.05O sample, which in turn is higher than that of the undoped NiO sample. This could be explained by the increase in free carrier concentration, which is associated with defects and shows that extrinsic conduction predominates over intrinsic conduction (Al Boukhari et al., 2020).

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Fig. 13.

Frequency response of AC conductivity in Cu- and Cu-Fe-doped NiO, fitted by Jonscher’s power law.

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To quantitatively validate the small polaron hopping mechanism, the ac conductivity data ($\sigma$) were fitted to Jonscher’s universal power law (Jonscher, 1977; Pfannstiel et al., 2024):

where $\left({\sigma }_{dc}\right)$ is the DC conductivity, (A) is a temperature-dependent constant, and (s) is the frequency exponent. The extracted $s$ values for NiO, Ni0.95Cu0.05O, and Ni0.95Cu0.025Fe0.025O are 0.89, 0.72, and 0.65, respectively (Fig. 13). As one can note, all frequency exponent values are less than 1 and decrease with codoping, confirming small polaron hopping as the dominant conduction mechanism (Javed et al., 2021). The reduction in s-values correlates with increased defect density (VO, dopants), which lowers the energy barrier for polaron hopping and enhances carrier mobility (Iqbal et al., 2023).

3.5 Magnetic properties at room temperature

The effects of saturation magnetization (M_S) versus magnetic field (H, Oe) for NiO, Ni_0.95Cu_0.05O, and Ni_0.95Cu_0.025Fe_0.025O DMS are plotted in Fig. 14. All specimens have magnetic plots that clearly show room-temperature ferromagnetic behavior with distinct hysteresis loops. The observed positive coercivity (Hc) and retentivity (Mr) values strongly indicate RTFM behavior. The Hc and Mr values of nanoscale pure NiO powder are 411 Oe and 0.074 emu/g, respectively. The M_S of the synthesized pristine NiO semiconductor is found to be 0.47 emu/g, with a calculated squareness value (squareness = retentivity/magnetization) of 0.156. Incorporating Cu/Fe ions into the NiO structure raises the retentivity to 0.24 emu/g and dramatically increases the fully saturated magnetization value to 3.5 emu/g, which is six times higher than that of the pristine NiO sample. Additionally, the measured coercivity and squareness of Ni_0.95Cu_0.05O and Ni_0.95Cu_0.025Fe_0.025O samples were 44.92 Oe and 0.067, respectively. M_S versus H plot of the Ni_0.95Cu_0.05O sample shows a fully saturated magnetic value of approximately 0.69 emu/g, which is higher than that of the pristine NiO sample. The Ni_0.95Cu_0.05O sample has a coercivity of 565.9 Oe, while its enhanced retentivity and squareness values are 0.13 emu/g and 0.18 emu/g, respectively. The magnetization plots indicate that the incorporation of Cu and Cu/Fe ions positively affects and amplifies the saturation magnetization of NiO, even at minimal doping concentrations, despite Cu’s non-magnetic characteristics. This enhancement indicates a strong influence of defect-related and carrier-mediated magnetic interactions in the doped systems. This enhancement trend should also be interpreted in terms of size effects, since TEM analysis confirms that the co-doped samples exhibit smaller average particle sizes, increasing the proportion of surface spins that contribute to ferromagnetic ordering. Additionally, the reduced coercivity in the Cu–Fe codoped sample (44.92 Oe) compared to pristine NiO (411 Oe) suggests easier domain wall motion, which can be linked to the defect-mediated softening of the magnetic anisotropy due to oxygen vacancies and Ni-site substitutions. The impact of Cu and Cu/Fe ions on the magnetic parameters of pure NiO nanoparticles, such as M_S, Hc, and Mr, has been shown in Fig. 15.

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Fig. 14.

M-H curves of pure, Cu-doped, and Cu-Fe codoped NiO nanopowders.

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Fig. 15.

Effects of Cu and Cu-Fe on magnetic parameters of NiO: (a) Ms, (b) Hc, (c) Mr

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The origin of ferromagnetic ordering in these structures is clarified by the characterization analyses of the synthesized samples. XRD analysis verified the pure phase characteristics and single-phase composition of these nanoscale powders, showing no indications of impurities or secondary phases. Rietveld refinement reveals a relationship between lattice volume and the ionic sizes of Cu and Fe ions, which validates the successful co-doping process. EDX analysis confirmed the presence of Cu and Fe dopants in the Ni_0.95Cu_0.025Fe_0.025O specimens. For Ni_0.95Cu_0.025Fe_0.025O, which exhibited the highest magnetic performance, the valence states of the constituent elements were identified as Ni²⁺, Cu²⁺, and Fe³⁺. TEM analysis demonstrates that the smallest particle sizes were achieved in this co-doped sample. In contrast to Fe, which is a magnetic element, Cu is non-magnetic by nature, helping to exclude the possibility of magnetic cluster formation. Based on these characterizations, we attribute the nature of ferromagnetism in the co-doped structures to intrinsic origins, excluding contributions from secondary magnetic phases or clusters. The observed increase in dielectric constant and electrical conductivity upon Cu and Cu-Fe co-doping indicates enhanced charge carrier density and defect-mediated exchange interactions, which directly strengthen the ferromagnetic response measured by VSM. Moreover, the slight lattice variation reflects strain-induced defect formation, further contributing to the significant rise in saturation magnetization values. Moreover, the observed variations in Hc and Mr across the three samples can be correlated with changes in magnetic anisotropy energy, which is sensitive to both dopant-induced lattice strain and defect states. Following the approach in (Dawn et al., 2024), such low-field magnetic softening in the Cu–Fe codoped sample can be viewed as an advantage for spintronic switching applications, as it reduces the energy required for magnetization reversal while maintaining a high M_S. The magnetic properties of nanoscale pure NiO powder can be ascribed to structural defects and uncompensated spins on the nanoparticles’ surface (Chen et al., 2017; Siddique and Tripathi, 2020).

Several models are proposed to explain RFTM in DMS, including indirect Ruderman-Kittel-Kasuya-Yosida (RKKY), double exchange mechanisms, and BMPs. (Gokul et al., 2015; Islam et al., 2024). In the current study, the BMP model can be considered the most plausible mechanism for the observed RFTM in Ni_0.95Cu_0.025Fe_0.025O (Fig. 16), supported by three key experimental observations: (i) First, we have confirmed from XPS measurements the oxygen vacancies at 532.61 eV (Fig. 9) that localize spins to form BMP nuclei (Jaiswar and Mandal, 2017). (ii) Secondly, codoping synergy where Fe³⁺ provides magnetic moments while Cu²⁺ promotes V_O formation via charge imbalance; and (iii) Finally, defect clustering evidenced by Ni vacancies (V_Ni) preferentially located near dopants due to Coulombic attraction. In fact, these V_Ni create hole-mediated impurity bands that enable long-range BMP to overlap through exchange interactions with dopant ions (Cu²⁺/Fe³⁺) and oxygen vacancies. While temperature-dependent magnetization (ZFC/FC) or electron paramagnetic resonance (EPR) data would quantitatively validate BMP percolation thresholds, the convergence of structural, chemical, and magnetic evidence strongly supports this mechanism (Mbarki et al., 2025; Siddique and Tripathi, 2020). Thus, the interplay between particle size reduction, oxygen-vacancy formation, and hole-mediated exchange represents the key mechanism for the remarkable enhancement in M_S and tuning of Hc observed in this work.

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Fig. 16.

Diagrammatic representation of the Cu/Fe codoped nanoscaled NiO DMS BMPs model

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The comparison presented in Table 4 highlights the superior magnetic performance and novelty of the synthesized Cu/Fe co-doped NiO nanoparticles in this work. Notably, the saturation magnetization of the Ni_0.95Cu_0.025Fe_0.025O sample significantly surpasses most reported doped NiO systems, including Fe-doped NiO (0.005–0.772 emu/g) (Krishnakanth et al., 2016), V-Fe co-doped NiO (0.89 emu/g) (Mbarki et al., 2025), and Cu-Mn co-doped NiO (0.31 emu/g) (Jharwal et al., 2022). This enhancement, achieved with only 5% total doping (Cu + Fe), underscores the synergistic effect of Cu/Fe co-doping in amplifying ferromagnetic interactions while maintaining structural stability. Although Co-doped NiO exhibits a higher M_S (Bharathy and Raji, 2018) due to Co’s inherent magnetic nature, the use of non-magnetic Cu in our work introduces a unique, cost-effective strategy to tailor magnetism without relying solely on conventional magnetic dopants. The success of Cu/Fe co-doping lies in its dual functionality: (i) Fe³⁺ introduces localized magnetic moments, while Cu²⁺, despite being non-magnetic, stabilizes the lattice and modulates charge carriers via hole-mediated interactions. In brief, the overall results of this study can be explained through three main mechanisms, as illustrated in the schematic model (Fig. 17): Cu doping generates Ni vacancies, Cu/Fe co-doping promotes oxygen vacancies and initial BMPs, and finally Fe facilitates vacancy clustering and overlapping BMPs that stabilize long-range ferromagnetism.

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Fig. 17.

A schematic model that summarizes the impact of Cu and Fe co-doping on NiO.

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