Ferrite-based materials for anticorrosion: comparative study of ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉

Abstract

Three chitosan ferrite nanoparticles-ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉-were synthesized via an ultrasound-assisted PEG route, yielding phase-pure products with controlled morphologies. Structural and compositional analyses confirmed phase purity, tailored morphology, and mesoporosity across systems for cubic spinel ZnFe₂O₄ and cuprospinel CuFe₂O₄. In contrast, SrFe₁₂O₁₉ exhibited coexistence of hexagonal M-type ferrite and rhombohedral α-Fe₂O₃, indicating a multiphase nature. These nanoparticles were incorporated into chitosan-ferrite nanocomposites and evaluated as corrosion inhibitors for carbon steel in 1.0 M HCl via potentiodynamic polarization (PDP), electrochemical frequency modulation (EFM), and electrochemical impedance spectroscopy (EIS). All of the techniques revealed concentration-dependent inhibition, with ZnFe₂O₄-based composites consistently demonstrating the highest efficiencies (up to 98.73% by PDP, 94.35% by EFM, and 97.38% by EIS). The inhibition mechanism was identified as mixed-type, primarily affecting the cathodic reaction, supported by causality factors and impedance parameters such as increased R_ct and decreased C_dl. Adsorption modeling showed strong monolayer behavior with spontaneous composite–metal surface interaction, validated by Langmuir fitting and values (∼−28 kJ mol⁻¹). These results highlight the performance of ultrasound-engineered ferrite nanocomposites in forming protective films and reducing acid-induced corrosion, underscoring their application potential in advanced coating systems.

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1. Introduction

Ferrites are a broad class of magnetic oxides with versatile crystal structures, most notably spinel and hexagonal, that have traditionally found use in magnetic recording, permanent magnets, and power electronics. In recent years, however, nanostructured ferrites have emerged as promising anticorrosion materials, particularly when incorporated into protective coatings for metallic substrates. Their chemical inertness, thermal stability, and ability to form passive barrier layers make them ideal candidates for corrosion inhibition in aggressive environments.¹ The nanoscale morphology of ferrites enhances surface reactivity and dispersion within polymeric matrices, improving coating adhesion and reducing electrolyte permeability.²

Spinel ferrites such as ZnFe₂O₄ and CuFe₂O₄, and hexagonal ferrites like SrFe₁₂O₁₉, exhibit tailored cation distributions that influence their electrochemical behavior and corrosion resistance. Through composition engineering and controlled synthesis, ferrite nanoparticles can be optimized to suppress anodic and cathodic reactions, promote passivation, and extend the service life of coated metals.³ These attributes position ferrites as environmentally friendly alternatives to toxic pigments like chromates, offering multifunctional protection in industrial, marine, and infrastructure applications. Zinc ferrite (ZnFe₂O₄) is a normal spinel ferrite with a cubic crystal structure, exhibiting ferromagnetic behavior and a Néel temperature of approximately 858 K. Beyond its magnetic characteristics, ZnFe₂O₄ has gained attention as a promising anticorrosion pigment due to its chemical stability, thermal resistance, and ability to inhibit corrosion when incorporated into protective coatings.⁴ The spinel structure, comprising Zn²⁺ and Fe³⁺ ions distributed over tetrahedral and octahedral sites, contributes to its durability and passivation behavior in aggressive environments. Recent studies have demonstrated that ZnFe₂O₄ nanoparticles, when embedded in epoxy or styrene-acrylate matrices, enhance the corrosion resistance of coated metal substrates by forming hydroxide layers that suppress electrochemical degradation.⁵ Additionally, its nanoscale morphology and high surface area improve pigment dispersion and barrier properties, making ZnFe₂O₄ a viable candidate for multifunctional coatings.⁶

Copper ferrite (CuFe₂O₄) is an inverse spinel ferrite with a tetragonal crystal structure, known for its thermal stability, magnetic properties, and chemical inertness. These attributes make CuFe₂O₄ a compelling candidate for anticorrosion coatings, particularly in harsh environments. The unique cation distribution – Cu²⁺ ions occupying octahedral sites and Fe³⁺ ions distributed across both tetrahedral and octahedral positions – contributes to its structural robustness and passivation behavior. Recent studies have demonstrated that CuFe₂O₄ nanoparticles, when incorporated into silicone-based or epoxy resin matrices, significantly enhance the corrosion resistance of coated metal substrates by forming compact barrier layers and promoting hydrophobicity.^7,8 The presence of Cu²⁺ ions may also contribute to localized cathodic protection, while the ferrite matrix impedes electrolyte penetration. Furthermore, CuFe₂O₄'s nanoscale morphology and magnetic recoverability offer additional advantages for smart coating systems and multifunctional surface protection.⁹

Strontium hexaferrite (SrFe₁₂O₁₉) is an M-type hexagonal ferrite known for its high coercivity, thermal stability, and chemical inertness. These properties make it a strong candidate for anticorrosion coatings, especially in environments requiring long-term durability. The magnetoplumbite structure of SrFe₁₂O₁₉, with Fe³⁺ ions occupying five distinct crystallographic sites, contributes to its robust lattice and resistance to chemical attack. When incorporated into polymeric matrices such as epoxy or polyaniline composites, SrFe₁₂O₁₉ nanoparticles enhance barrier performance by reducing electrolyte permeability and promoting passive layer formation on metal surfaces.¹⁰ Recent studies have shown that SrFe₁₂O₁₉-based nanocomposites exhibit excellent adhesion, low charge-transfer resistance, and high cyclic stability, making them suitable for multifunctional coatings that combine magnetic and protective functions.¹⁰ Additionally, its compatibility with conductive polymers and carbon-based additives allows for tailored electrochemical behavior, further improving corrosion resistance.¹¹

Traditionally, the solid-state reaction technique has been widely employed for ferrite synthesis; however, it presents several limitations, including high temperature requirements, large crystallite sizes, and poor compositional homogeneity.¹² To overcome these drawbacks, recent studies have investigated various wet chemical methods for synthesizing ferrite materials such as ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉ – notably sol–gel, co-precipitation, and microwave-assisted hydrothermal techniques. Among these, ultrasound-assisted synthesis has emerged as a mild, energy-efficient, and versatile approach for producing high-purity, crystalline, and compositionally homogeneous ferrites. For example, Chen et al. synthesized ZnFe₂O₄@TiO₂ core–shell structures via ultrasonic treatment, achieving enhanced phase control and photocatalytic activity.¹³ Meenu et al. reported the ultrasound-enabled fabrication of CuFe₂O₄–Ag nanocomposites within hydrogel matrices, demonstrating improved dispersion and dye degradation performance.¹⁴ Similarly, Palomino et al. achieved monodisperse SrFe₁₂O₁₉ nanoparticles through sonochemical processing, highlighting the method's efficacy for complex hexaferrites.¹⁵ These findings underscore the adaptability of ultrasound-assisted synthesis across both simple binary oxides and structurally intricate spinel and hexaferrite systems.

Herein, we report the synthesis of ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉ nanoparticles via a versatile ultrasound-assisted polyethylene glycol (PEG) route. This method enabled the formation of phase-pure, crystalline ZnFe₂O₄ and CuFe₂O₄ ferrites with controlled morphology and dispersion, while SrFe₁₂O₁₉ was obtained as a multiphase material comprising dominant hexagonal magnetoplumbite and a minor α-Fe₂O₃ phase. The structural characteristics of the synthesized nanoparticles were systematically investigated, and their performance as corrosion inhibitors was evaluated. To comprehensively assess their anticorrosion potential, electrochemical techniques and adsorption modeling were employed, complemented by density functional theory (DFT) calculations to elucidate the molecular interactions and reactivity at the metal–inhibitor interface.

2. Experimental Section

2.1 Materials

All reagents used were commercially available and directly employed without further purification. Iron(III) nitrate nonahydrate (99%) was purchased from Riedel-deHAaen, sodium hydroxide (99%), zinc acetate-2-hydrate (99%) from FARCO, copper(II) acetate monohydrate (99%), strontium nitrate (99%), ethanol (p.a.), polyethylene glycol 6000 (PEG 6000) (99%) from Sigma-Aldrich.

2.2 Synthetic procedures

2.2.1 Synthesis of ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉. Spinel ZnFe₂O₄, CuFe₂O₄, and hexaferrite SrFe₁₂O₁₉ were synthesized using a PEG-assisted sonochemical precipitation approach. Stoichiometric amounts of Fe(NO₃)₃·9H₂O (0.33, 0.4, and 0.6 g), Zn(CH₃COO)₂·2H₂O (0.12 g), Cu(CH₃COO)₂·H₂O (0.1 g), and Sr(NO₃)₂ (0.2 g) were individually dissolved in 5 mL of deionized water containing PEG 600 (0.5 g), followed by stirring for 10 min in sealed glass vessels at room temperature. Sodium hydroxide (0.25 g) was then introduced to each solution, and the mixtures were stirred vigorously for an additional 30 min. Each reaction mixture underwent sonication for 3 h in an ultrasonic bath (LUC-405, DAIHAN LABTECH Co. Ltd; 60 kHz, 350 W). The resulting precipitates were separated by centrifugation, thoroughly washed with distilled water, and dried at 100 °C for 3 h. Finally, calcination in air at 500 °C for 3 h yielded phase-pure ZnFe₂O₄ and CuFe₂O₄. SrFe₁₂O₁₉ required higher thermal treatment and was calcined at 700 °C for 3 h to achieve the desired hexaferrite phase.

2.2.2 Synthesis of chitosan/metal oxide nanocomposites. For the preparation of chitosan/metal oxide nanocomposites, 1 g of chitosan was dissolved in 50 mL of deionized water containing 2.5 mL of 5% acetic acid. The solution was stirred continuously for 4 h until a homogeneous viscous gel was formed. Subsequently, 0.3 g of ZnFe₂O₄, CuFe₂O₄, or SrFe₁₂O₁₉ powder was separately added to the chitosan solution and stirred for 24 h to ensure uniform dispersion. The mixture was then neutralized using 100 mL of 2% NaOH, followed by centrifugation and repeated washing with distilled water. The resulting Ch–Oxide nanocomposites were dried in an oven at 100 °C for 3 h.

2.3 Characterization

The phase composition and structural properties of the metal oxide nanoparticles were determined using X-ray diffraction (XRD), performed on a Seifert 3003TT diffractometer with copper Kα radiation as the source.

Transmission Electron Microscopy (TEM), conducted with a JEOL GEM-1010 system, provided high-resolution imaging of nanoparticle morphology. Elemental analysis was carried out concurrently using Energy-Dispersive X-ray spectroscopy (EDX).

The specific surface area and adsorption–desorption characteristics of the sample were assessed at cryogenic temperatures using a Quantachrome instrument (USA), featuring TouchWin software for data acquisition and analysis.

2.4 Electrochemical measurements

Electrochemical tests were conducted using a Gamry REF600-16084 potentiostat with data processed using Echem Analyst 2 (Framework v7.10.4). A standard three-electrode setup (100 mL capacity) was used, consisting of a polished steel working electrode (1.0 cm²), platinum wire counter electrode, and saturated Ag/AgCl reference electrode. Tests were conducted in 1 M HCl at 30 ± 1 °C, with varying concentrations (40 to 400 ppm) of chitosan/metal oxide nanocomposites. Prior to testing, the working electrode was immersed in the test solution and left to stabilize for 3600 seconds to reach a stable open circuit potential (OCP). Electrochemical Frequency Modulation (EFM) was performed with a foundational frequency of 0.1 Hz, along with multipliers of 2.0 and 5.0, and an amplitude set at 10 mV.¹⁶ The utilization of these parameters facilitated the examination of inhibitor adsorption kinetics and non-faradaic phenomena.¹⁷ Concurrently, Electrochemical Impedance Spectroscopy (EIS) was executed at the open circuit potential (OCP) employing a 10 mV alternating current (AC) signal across a frequency spectrum ranging from 100 kHz to 0.01 Hz. Potentiodynamic polarization (PDP) was carried out by scanning the potential ±250 mV with respect to OCP at a scan rate of 0.5 mV s⁻¹. Inhibition efficiency was calculated from the following equations:¹⁸

2.5 Theoretical methodology and methods

Plane-wave Kohn–Sham density functional theory (KS-DFT) calculations with pure PBEPBE exchange–correlation functional,¹⁹ implemented into Quantum Espresso program package, version 7.1,²⁰ were used to optimize the geometries of the NPs. The van der Waals correction (DFT-D) was applied to realistically represent van der Waals forces in KS-DFT calculations.²¹ The plane-wave energy cut-off was set to 75 Ry for the zinc-containing system and 45 Ry for all other systems. Due to the accuracy limitations of pure functionals, the global reactivity parameters and partial atomic charges were deliberately obtained via hybrid density functional theory (HDFT). The M11 exchange–correlation meta-GGA functional was hereby used.²² To solve d-element-containing compositions, we employed the Stuttgart/Dresden effective core potentials. The dispersive attraction was included inherently.^23,24 The convergence criterion within the self-consistent field procedure was set to 10–7 hartree. The implicit solvent water was used because the simulated NPs are expected to neutralize corrosion promoters in their aqueous environment. The partial atomic electrostatic charges were derived by fitting the HDFT-derived electrostatic potential in the system using the Merz–Kollman algorithm. The HDFT calculations were conducted in Gaussian’09D.²⁵ The reported calculations were carried out using an implicit water model, which represents the solvent as a matterless polarizable continuum at effectively low ionic strength. In particular, the 1 M HCl environment of the corrosion experiments is not hereby explicitly modeled. No hydronium cations and no chloride anions are present. Thereby no electric double layer is formed at the metal/solution interface. The modeled inhibitor is treated in its neutral form. In tun, under the strongly acidic experimental conditions it is expected to exist predominantly in protonated and fractionally ion-paired states. As a consequence, the computed electronic descriptors and adsorption-related properties should be regarded as qualitative indicators of the intrinsic reactivity of the inhibitor molecules. A fully quantitative description of the 1 M HCl medium requires explicit treatment of H⁺/H₃O⁺ and Cl⁻, high ionic strength, and interfacial charging, which is beyond the current scope.

3. Results and discussion

3.1 Morphology, crystallinity, and porosity of ferrite nanoparticles

Powder X-ray diffraction (XRD) analysis was employed to assess the phase composition and purity of the synthesized samples, as illustrated in Fig. 1. The diffraction pattern of ZnFe₂O₄ matched perfectly with the reference data (JCPDS Card No. 01-082-1042), confirming the formation of cubic spinel zinc ferrite without any detectable secondary phases or impurity peaks. Similarly, the XRD pattern of CuFe₂O₄ revealed that the dominant phase was cuprospinel, with all diffraction angles corresponding to the standard card [JCPDS No. 034-0425], and no evidence of extraneous crystal phases. Notably, no peak splitting, broadening, or asymmetry-typically associated with tetragonal distortion-was observed in the diffraction pattern. Detailed peak analysis of SrF₁₂O₁₉ indicated that the majority of reflections aligned with the hexagonal space group P6₃/mmc, while a subset of peaks matched the rhombohedral space group R3̄c. This coexistence of reflections suggests the presence of two distinct crystalline phases within the synthesized material. Specifically, the lattice planes (110), (112), (107), (114), (201), (203), (205), (206), (300), (217), (2011), (220), and (2013) are characteristic of M-type hexaferrites with a hexagonal structure (JCPDS Card No. 79-1411). The second phase, attributed to α-Fe₂O₃ with rhombohedral symmetry, is evidenced by peaks at (012), (113), (024), (211), (018), and (224), corresponding to the R3̄c space group (JCPDS Card No. 33-0664). By comparing the integrated intensities of the α-Fe₂O₃ reflections to those of the dominant SrFe₁₂O₁₉ peaks, the α-Fe₂O₃ phase was estimated to constitute approximately 11 wt% of the total crystalline content. The average crystallite size of the synthesized composite materials was calculated using Scherrer's equation (eqn (2)):where D = crystallite size, k = shape factor, λ = wavelength of X-ray, β = (FWHM) full width at half maximum of the peak in radians, θ = Bragg diffraction angle. The estimated crystallite sizes were approximately 11.70 nm for ZnFe₂O₄, 15.80 nm for CuFe₂O₄, and 38.00 nm for SrFe₁₂O₁₉.

Fig. 1 XRD patterns recorded for the ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉ samples.

The elemental composition of the synthesized ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉ samples was evaluated using energy dispersive X-ray spectroscopy (EDX). As shown in Fig. 2, the spectra confirm the presence of the respective constituent elements: Zn, Cu, Sr, Fe, and O, consistent with the expected stoichiometry of each ferrite system. Importantly, no extraneous impurity bands were detected in any of the spectra, affirming the phase purity of the synthesized samples. Minor C peaks were observed, attributed to the carbon support film used in the TEM sample preparation, and are not indicative of contamination from synthesis.

Fig. 2 EDX spectra recorded for the ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉ samples.

The TEM was conducted to investigate the morphology, crystallite dimensions, and agglomeration behavior of the synthesized ferrite samples (Fig. 3). ZnFe₂O₄ nanoparticles (Fig. 3a) exhibit predominantly spherical to quasi-spherical morphologies, with diameters ranging from ∼5 to 20 nm and a notable concentration within the 10–15 nm range. Individual crystallites frequently assemble into chain-like and flower-shaped polycrystalline aggregates with average sizes of ∼100–120 nm, formed through oriented attachment and surface energy minimization. CuFe₂O₄ nanoparticles (Fig. 3b) display nearly spherical to faceted morphologies, reflecting shape anisotropy likely influenced by local growth conditions. Primary particle sizes measure ∼10–30 nm, while TEM images reveal densely packed clusters with average dimensions of ∼120–140 nm, suggesting stronger agglomeration compared to ZnFe₂O₄. This clustering is likely driven by magnetic dipole interactions, which promote particle–particle attraction and reduce dispersion. SrFe₁₂O₁₉ particles (Fig. 3c) exhibit plate-like and slightly elongated morphologies, with occasional faceted edges. These features align with the intrinsic hexagonal magnetoplumbite structure, where anisotropic growth along specific crystallographic axes dominates. Particle sizes span ∼30–80 nm, and the relatively well-defined edges suggest high crystallinity. However, the presence of a secondary α-Fe₂O₃ phase, confirmed by XRD, indicates that the observed morphology may also include interspersed hematite crystallites. Hematite typically forms smaller, pseudo-plate or granular particles that can adhere to or embed within the larger hexaferrite plates, subtly altering surface texture and particle boundaries. As a result, the morphology of SrFe₁₂O₁₉ should be understood as a composite of dominant hexaferrite plates with embedded or attached hematite crystallites, a structural complexity that may influence surface accessibility, particle–particle interactions, and ultimately electrochemical behavior.²⁶ Overall, TEM analysis confirms distinct morphological characteristics across the ferrite systems: moderate agglomeration in ZnFe₂O₄, stronger clustering in CuFe₂O₄, and relatively uniform dispersion in SrFe₁₂O₁₉. The hierarchical structures observed are expected to play a critical role in determining surface accessibility, pigment packing, and electrolyte diffusion, thereby influencing inhibition efficiency and overall coating performance. Furthermore, the particle sizes observed through TEM analysis were found to be in good agreement with the crystallite sizes estimated from XRD data, supporting the reliability of the measurements.

Fig. 3 TEM images of ZnFe₂O₄ (left), CuFe₂O₄ (middle) and SrFe₁₂O₁₉ (right) NPs.

The N₂ adsorption–desorption isotherms of ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉ uniformly exhibit type IV profiles with H3 hysteresis loops, consistent with mesoporous structures containing slit-like pores formed via particle agglomeration (Fig. 4). These hysteresis loops, arising from the divergence between adsorption and desorption branches, affirm the presence of interconnected pore networks that facilitate capillary condensation and surface accessibility-key factors in optimizing coating performance. In all systems, initial uptake at low relative pressures (P/P₀ < 0.3) corresponds to monolayer adsorption, followed by a steep increase near P/P₀ ≈ 0.8–0.9 associated with capillary condensation in mesopores.

Fig. 4 N₂ adsorption–desorption of the of (a) ZnFe₂O₄, (b) CuFe₂O₄ and (c) SrFe₁₂O₁₉ samples.

For ZnFe₂O₄, the BET surface area was measured at 65.8 m² g⁻¹, which, although lower than some reported maxima – such as the 78.9 m² g⁻¹ for ZnFe₂O₄ obtained via ultrasound-assisted synthesis using glucose precursors²⁷ – remains comparatively high and exceeds many values reported for conventional synthesis routes. For instance, Jadhav et al. reported a BET value of only 2.27 m² g⁻¹ for ZnFe₂O₄ prepared by a sol–gel auto-combustion method using urea as a chelating agent.²⁸ Similarly, Tomina et al. obtained a BET surface area of approximately 26 m² g⁻¹ for ZnFe₂O₄ synthesized via a precipitation method assisted by citric acid as a capping agent.²⁹ The slightly reduced surface area observed in our study is attributed to particle agglomeration evident in TEM images, which limits external surface exposure and pore accessibility. Nevertheless, the material exhibits a well-developed mesoporous structure, and the achieved surface area is sufficient to support its intended anticorrosion application.

CuFe₂O₄ displayed a BET surface area of 54.1 m² g⁻¹, which lies within the broad literature range (9–160 m² g⁻¹) and is higher than several values reported for conventional methods such as thermal decomposition (18.2 m² g⁻¹) or precipitation (24.1 m² g⁻¹).³⁰ The relatively small BJH-derived average pore diameter of 1.93 nm, though lower than the typical 4–8 nm range, is consistent with slit-like mesopores indicated by the H3 hysteresis loop. This discrepancy is explained by synthesis-specific factors-rapid nucleation, restricted grain growth, and magnetic dipole-driven clustering-that reduce interparticle spacing and limit pore expansion. Larger mesopores reported in literature generally arise from template-assisted or high-temperature calcination routes, which differ significantly from the present synthesis conditions.^31–33

SrFe₁₂O₁₉ exhibited a BET surface area of 41.7 m² g⁻¹ and a BJH pore size of 1.92 nm. While the nearly identical pore size values for CuFe₂O₄ and SrFe₁₂O₁₉ appear statistically unusual, they are more likely artifacts of the BJH method, which assumes cylindrical pore geometry and is less accurate for slit-like or irregular pores.³⁴ In SrFe₁₂O₁₉, the low pore volume (0.12 cm³ g⁻¹) and plate-like morphology suggest minimal mesoporosity, with the measured pore size reflecting surface voids or edge effects rather than intrinsic pore structure.³⁵

Correlation between TEM and BET analyses confirms that particle agglomeration plays a decisive role in reducing surface area compared to literature maxima. TEM revealed moderate clustering in ZnFe₂O₄, stronger aggregation in CuFe₂O₄, and relatively uniform dispersion in SrFe₁₂O₁₉. These morphological traits directly influenced BET values, as agglomeration reduces accessible surface area and narrows pore distributions, consistent with prior reports.

To provide quantitative insight, representative BJH adsorption pore volume data points are presented in Table 1. These values highlight the evolution of pore volume across different regimes: ZnFe₂O₄ and CuFe₂O₄ exhibit higher pore volumes and narrower distributions, consistent with their dispersed nanoparticle morphologies, whereas SrFe₁₂O₁₉ shows broader pores and lower overall volume, in agreement with its aggregated plate-like structure. Although ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉ were synthesized under identical ultrasound-assisted PEG conditions, the observed differences in BET surface area and pore size distribution arise from the intrinsic crystallographic structures, cation chemistry, and agglomeration tendencies of each ferrite system. ZnFe₂O₄, with its cubic spinel framework, favors quasi-spherical crystallites that assemble into moderate aggregates, yielding relatively high surface area. In contrast, CuFe₂O₄ exhibits stronger magnetic dipole interactions that promote clustering, thereby reducing accessible surface area and narrowing pore dimensions. SrFe₁₂O₁₉, dominated by anisotropic plate-like growth and the coexistence of α-Fe₂O₃, shows minimal mesoporosity and lower pore volume due to structural packing constraints. Thus, the textural properties are not solely determined by external synthesis parameters but by the interplay between synthesis conditions and material-specific growth mechanisms. These differences in morphology and porosity directly influence pigment dispersion, interfacial bonding, and electrolyte diffusion, thereby shaping the anticorrosion performance of the resulting nanocomposites.^24,25

Table 1 Textural properties derived from BET and BJH analyses

Pore radius (nm)	Pore volume (cm^3 g^−1)
	ZnFe2O4	CuFe2O4	SrFe12O19
1.92	0.0085	0.0105	0.0076
2.58–2.59	0.0207	0.0232	0.0150
3.72–3.76	0.0454	0.0444	0.0246
6.51–6.72	0.1596	0.1067	0.0365
56–71	0.2036	0.2014	0.1242

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FTIR analysis was performed to investigate the chemical interactions between chitosan and ferrite nanoparticles in the synthesized composites: Chit-ZnFe₂O₄, Chit-CuFe₂O₄, and Chit-SrFe₁₂O₁₉ (Fig. 5). The spectra were recorded in the range of 4000–400 cm⁻¹ and compared with pure chitosan (Chit) to identify characteristic functional groups and confirm successful incorporation of ferrite phases. All samples exhibited a broad absorption band around 3400 cm⁻¹, corresponding to the stretching vibrations of hydroxyl (O–H) and amine (N–H) groups, which are intrinsic to the chitosan backbone. The bands near 2900 cm⁻¹ were attributed to C–H stretching vibrations of aliphatic groups. A prominent peak around 1650 cm⁻¹ was observed in all samples, associated with the amide I (C=O) stretching vibration. Notably, this band showed slight shifts in the ferrite-modified samples, indicating possible interactions between chitosan's carbonyl groups and the metal ions of the ferrite nanoparticles. In the fingerprint region, distinct bands appeared between 500 and 600 cm⁻¹ in the Chit-ZnFe₂O₄, Chit-CuFe₂O₄, and Chit-SrFe₁₂O₁₉ spectra, which were absent in pure chitosan. These bands are characteristic of metal–oxygen (Fe–O) stretching vibrations and confirm the presence of ferrite phases within the chitosan matrix. The variation in peak positions and intensities among the different composites reflects the influence of the specific metal ions (Sr²⁺, Cu²⁺, Zn²⁺) on the structural configuration and bonding environment. Overall, the FTIR results demonstrate successful integration of ferrite nanoparticles into the chitosan matrix and suggest chemical interactions between the polymer and the ferrite surfaces, which may influence the electrochemical behavior observed in subsequent EIS measurements.

Fig. 5 FTIR spectra of Chit, Chit-ZnFe₂O₄ NPs, Chit-CuFe₂O₄ NPs, Chit-SrFe₁₂O₁₉ NPs.

3.2 Electrochemical measurements

3.2.1 Potentiodynamic polarization (PDP). The electrochemical behavior of carbon steel (CS) in 1.0 M HCl solution in the absence and presence of different concentrations (40, 100, 200, 300, and 400 ppm) of the synthesized Chit-ZnFe₂O₄, Chit-CuFe₂O₄, and Chit-SrFe₁₂O₁₉ nanocomposites was investigated systematically by potentiodynamic polarization (PDP) measurements. The resulting polarization curves (Fig. 6a–c) and the extracted electrochemical parameters (Table 2) clarify the corrosion kinetics and inhibition efficiency of the composites being studied. Examination of the PDP curves indicates that addition of the chitosan–ferrite composites considerably changes the corrosion behavior of CS relative to the uninhibited acid solution. The corrosion current density (i_corr) drops considerably with increasing inhibitor concentration for all three composites (Table 2). This implies a considerable reduction of the overall corrosion rate, validating the effectiveness of these materials as corrosion inhibitors.^36–38 At the same time, the inhibition efficiency (η_p%) derived from the i_corr values (by using the formula given in the Experimental section) improves with concentration to arrive at impressive figures of 98.13%, 98.55%, and 98.73% for Chit-SrFe₁₂O₁, Chit-CuFe₂O₄, and Chit-ZnFe₂O₄, respectively, at the highest concentration of 400 ppm. The corrosion potential (E_corr) shows variation in response to the addition and concentration of inhibitors. That is, for Chit-ZnFe₂O₄ and Chit-CuFe₂O₄, E_corr exhibits a slight shift towards more negative (cathodic) potentials as the concentration is increased, showing a notable influence on the cathodic reaction (e.g., hydrogen evolution).^39,40 However, the shift for Chit-SrFe₁₂O₁₉ is relatively less. The Tafel slopes (β_a and β_c) generally exhibit close value to that of the blank sample, with minor deviations based on the concentration and nature of the inhibitor. The results suggest that the inhibition mechanism probably has a mixed-type nature, having a primary influence on the cathodic process without significantly altering the inherent reaction mechanisms.^41,42 The higher efficiency of Chit-ZnFe₂O₄, followed by Chit-CuFe₂O₄ and Chit-SrFe₁₂O₁₉, is in accordance with the expected trends based on the textural properties and intrinsic characteristics of the ferrite nanoparticles.⁴³ The significant surface area and mesoporosity of ZnFe₂O₄ nanoparticles are expected to favor greater adsorption and better spreading of the inhibitor over the metal interface, thus forming a more efficient protective film.⁴⁴ Though CuFe₂O₄ has a lower surface area, its spinel structure and redox properties are likely to be responsible for its high inhibition efficiency. In spite of having the lowest surface area and pore volume, SrFe₁₂O₁₉ still manifests excellent inhibition, which can be related to its unique plate-like morphology and the chemical stability imparted by its hexagonal structure, possibly providing effective barrier coverage.⁴⁵

Fig. 6 Potentiodynamic polarization curves for the corrosion of carbon steel in 1.0 M HCl in absence and presence of different concentrations of (Chit-SrFe₁₂O₁₉ (a), Chit-CuFe₂O₄ (b) and Chit-ZnFe₂O₄ (c)) composites at 30 °C.

Table 2 Electrochemical parameters for carbon steel dissolution in 1.0 M HCl solution containing different concentrations of the (Chit-SrFe₁₂O₁₉, Chit-CuFe₂O₄ and Chit-ZnFe₂O₄) composites obtained from polarization measurements at 30 °C^a

Inhibitor name	Conc. (ppm)	Ecorr vs. SCE (mV)	icorr (µA cm^−2) ± SD	βa (mV dec^−1)	−βc (mV dec^−1)	k (mpy)	θ	ηp%
a Ecorr, is the corrosion potential; icorr, is the corrosion current density: βa and βc are Tafel constants for both anode and cathode; k, is the corrosion rate; θ, is the surface coverage; ηp, is the inhibition efficiency.
Blank	—	−333.7	1579.00 ± 11.04	104.1	136.4	721.5	—	—
Chit-SrFe12O19	40	−378.6	349.30 ± 7.99	202.9	113.3	159.6	0.7788	77.88
	100	−390.9	245.30 ± 7.12	173.7	105.9	112.1	0.8446	84.46
	200	−355.7	94.46 ± 5.35	79.49	99.65	43.16	0.9402	94.02
	300	−383.1	38.03 ± 4.52	73.72	96.14	17.38	0.9759	97.59
	400	−367.9	29.59 ± 2.29	83.32	121.3	13.52	0.9813	98.13
Chit-CuFe2O4	40	−381.0	339.70 ± 6.52	183	183	155.2	0.7849	78.49
	100	−369.2	225.00 ± 7.77	131.3	117.3	102.8	0.8575	85.75
	200	−350.6	75.80 ± 4.85	82.29	141.9	34.63	0.9520	95.20
	300	−377.0	35.36 ± 4.87	90.66	115	16.16	0.9776	97.76
	400	−389.7	22.82 ± 3.11	76.86	103.4	10.43	0.9855	98.55
Chit-ZnFe2O4	40	−368.2	313.40 ± 6.45	168.7	115.1	143.2	0.8015	80.15
	100	−378.6	216.40 ± 6.29	103.2	116.1	98.87	0.8630	86.30
	200	−354.2	53.92 ± 4.34	75.38	134.3	24.64	0.9659	96.59
	300	−394.0	34.68 ± 2.15	102.5	129.3	15.85	0.9780	97.80
	400	−373.9	20.05 ± 2.03	78.01	119	9.161	0.9873	98.73

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The PDP data validate that the chitosan–ferrite nanocomposites synthesized are good corrosion inhibitors for carbon steel in 1.0 M HCl. The inhibition efficiency is concentration-dependent, and the activity order (Chit-ZnFe₂O₄ ≥ Chit-CuFe₂O₄ > Chit-SrFe₁₂O₁₉ at higher concentrations) aligns with the physicochemical characteristics of the ferrite nanoparticles incorporated. The inhibition process seems to be through the adsorption of a protective layer onto the steel surface, inhibiting anodic dissolution and, more pronouncedly, the cathodic evolution of hydrogen.

3.2.2 Electrochemical frequency modulation (EFM). In order to get more information about the inhibition mechanism of corrosion and confirm the PDP results, Electrochemical Frequency Modulation (EFM) measurements were made. EFM is a non-destructive DC method that superimposes two small-amplitude sine waves, producing intermodulation products with amplitudes and phases dependent on the corrosion current density (i_corr) and Tafel parameters, without the need for previous knowledge of β_a and β_c to interpret data.^46,47 The intermodulation spectra recorded for carbon steel in 1.0 M HCl solution, in the absence and presence of different concentrations (40, 100, 200, 300, 400 ppm) of Chit-ZnFe₂O₄, Chit-CuFe₂O₄, and Chit-SrFe₁₂O₁₉, are shown in Fig. 7, S1, S2 and tabulated in Table 3. The spectra generally exhibit current density responses at different frequencies, including the base frequencies (f₁, f₂) and their combinations (e.g., 2f₁, 2f₂, f₁ + f₂, f₁ − f₂).^48,49 The amplitude of these responses is directly related to the corrosion activity. EFM-derived causality factors (CF-2 and CF-3) compare measured intermodulation currents to theoretical, with ideal values of CF-2 ≈ 2.0 and CF-3 ≈ 3.0.⁵⁰ The blank solution values (CF-2 = 1.574, CF-3 = 3.465) were near ideal, confirming the validity of the EFM measurements.⁵¹ With chitosan–ferrite composites addition, CF-2 and CF-3 varied around their theoretical values. These changes signify the composites affect interfacial electrochemical processes beyond simple physical blocking, suggesting kinetic modifications or complex layer formation. Examination of the EFM data shows that there are drastic changes in the corrosion behavior with the addition of inhibitors. The calculated i_corr values (Table 3) show a steady reduction with increasing concentration of the inhibitors for the three nanocomposites, similar to those found in PDP measurements. This is a clear indication of the ability of the chitosan–ferrite composites to minimize the corrosion rate of carbon steel in the acidic medium.⁵² At the same time, the inhibition efficiency (η_EFM%), calculated from the i_corr values, rises with concentration. Interestingly, at the highest concentration examined (400 ppm), inhibition efficiencies of 91.99%, 92.72%, and 94.35% were achieved for Chit-SrFe₁₂O₁₉, Chit-CuFe₂O₄, and Chit-ZnFe₂O₄, respectively. EFM-derived Tafel constants (β_a and β_c) (Table 3) are also informative. For chitosan–ferrite composites, β_c and β_a values exhibit slight changes relative to the blank. The variations of β_a and β_c indicate that the inhibitors affect the kinetics of both the anodic dissolution and, more pronouncedly, the cathodic reduction process.^53,54 The EFM data validates the efficacy of the synthesized chitosan–ferrite nanocomposites as corrosion inhibitors for carbon steel in 1.0 M HCl. The inhibition efficiency is concentration-dependent, in the order Chit-ZnFe₂O₄ > Chit-CuFe₂O₄ > Chit-SrFe₁₂O₁₉ at high concentrations, which is in agreement with the trends in PDP and is consistent with the physicochemical characteristics of the included ferrite nanoparticles. The EFM measurements also indicate a mixed-type inhibition mechanism with prevailing influence on the cathodic process.

Fig. 7 Intermodulation spectra for carbon steel in 1.0 M HCl in absence and presence of different concentrations from Chit-ZnFe₂O₄ composite at 30 °C.

Table 3 Electrochemical kinetic parameters obtained by EFM technique for carbon steel in the absence and presence of various concentrations of (Chit-SrFe₁₂O₁₉, Chit-CuFe₂O₄ and Chit-ZnFe₂O₄) composites in 1.0 M HCl at 30 °C^a

Inhibitor name	Conc. (ppm)	icorr (µA cm^−2) ± SD	βa (mV dec^−1)	βc (mV dec^−1)	CF-2	CF-3	k (mpy)	θ	ηEFM%
a Ecorr, is the corrosion potential; icorr, is the corrosion current density: βa and βc are Tafel constants for both anode and cathode; k, is the corrosion rate; θ, is the surface coverage; ηEFM, is the inhibition efficiency.
Blank	—	739.3 ± 5.18	124.2	162.0	1.574	3.465	337.80	—	—
Chit-SrFe12O19	40	437.3 ± 5.37	137.6	216.5	1.861	2.601	199.80	0.4085	40.85
	100	307.7 ± 6.29	84.9	100.0	2.008	3.114	140.60	0.5838	58.38
	200	193.5 ± 5.42	100.6	115.6	1.883	3.368	88.40	0.7383	73.83
	300	67.0 ± 3.04	111.1	120.6	1.873	2.950	30.62	0.9094	90.94
	400	59.2 ± 3.65	117.4	140.2	2.224	3.198	27.04	0.9199	91.99
Chit-CuFe2O4	40	334.8 ± 6.44	115.9	247.2	2.022	2.492	153.00	0.5471	54.71
	100	302.3 ± 5.99	132.1	158.8	1.869	2.129	138.10	0.5911	59.11
	200	88.9 ± 4.07	110.0	138.6	1.840	2.059	40.60	0.8798	87.98
	300	64.4 ± 3.99	114.3	148.7	1.830	3.721	29.42	0.9129	91.29
	400	53.8 ± 2.22	138.6	147.8	1.489	3.640	24.60	0.9272	92.72
Chit-ZnFe2O4	40	327.2 ± 5.35	115.9	194.6	1.975	3.616	149.50	0.5574	55.74
	100	261.4 ± 5.57	103.8	162.2	1.973	2.422	119.40	0.6464	64.64
	200	75.9 ± 3.76	100.4	127.6	2.483	3.520	34.67	0.8974	89.74
	300	61.5 ± 2.11	137.5	151.9	1.906	2.811	28.10	0.9168	91.68
	400	41.8 ± 2.64	124.9	144.3	1.824	2.366	19.10	0.9435	94.35

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3.2.3 Electrochemical impedance spectroscopy (EIS). EIS is useful for understanding the interfacial processes and resistive and capacitive behavior of the electrode–electrolyte system.^55,56 The EIS data were fitted to a modified equivalent circuit, which comprises solution resistance (R_s), film resistance (R_f) and film capacitance (CPE_f), charge transfer resistance (R_ct), and double-layer capacitance (CPE_dl) (inset of Fig. 8). Low χ² values (<10⁻³) indicate good agreement between the experimental data and the fitted equivalent circuit model.⁵⁷ The utilization of Constant Phase Elements (CPE) rather than pure capacitors explains the non-ideal behavior and surface heterogeneity widely encountered in corrosion systems.^58,59 The representative Nyquist and Bode plots for carbon steel in 1.0 M HCl with chitosan–ferrite nanocomposites are displayed in Fig. 8. Examination of Nyquist plots (Fig. 8a–c) shows drastic modification of impedance response with the addition of chitosan–ferrite nanocomposites. The blank solution shows one capacitive loop with a comparatively small diameter, which signifies low polarization resistance and high corrosion activity.⁶⁰ However, with the addition of chitosan–ferrite nanocomposites, the diameter of the capacitive loop increases considerably and increases with increasing concentration of the inhibitor. This directly signifies an increase in overall impedance of the system and represents the inhibitive effect of the composite.⁶¹ The loop shape further indicates the presence of more than one time constant, which corroborates the proposed equivalent circuit with both a film and a charge transfer resistance. The Bode plots (magnitude and phase angle, Fig. 8d–f) also complement these observations. The impedance magnitude (|Z|) at low frequencies rises significantly with chitosan–ferrite nanocomposites concentration, reinforcing the increased barrier properties.⁶² The phase angle plots exhibit a shift to more negative angles in the intermediate frequency range with increasing inhibitor concentration, pointing towards increasingly capacitive interfacial behavior and the formation of the protective film.^63,64 The EIS parameters derived from fitting experimental data using the equivalent circuit are listed in Table 4. The solution resistance (R_s) is relatively constant for all measurements, as can be expected for a fixed concentration of the electrolyte. One of the main observations is the large increase in charge transfer resistance (R_ct) with increasing inhibitor concentration for all three composites. For example, for Chit-ZnFe₂O₄, R_ct rises from 19.05 Ω cm² for the blank to 646.42 Ω cm² at 400 ppm. This large increase in R_ct indicates a decrease in the rate of the charge transfer process (corrosion reaction), demonstrating the efficiency of the chitosan–ferrite nanocomposites.⁶⁵ At the same time, the double-layer capacitance (C_dl, calculated from CPE_dl) decreases noticeably with increasing inhibitor concentration (e.g., from 406.90 µF cm⁻² for the blank to 28.39 µF cm⁻² for Chit-ZnFe₂O₄ at 400 ppm). The decrease in C_dl is usually explained by the adsorption of inhibitor molecules on the metal surface, decreasing the effective area for charge transfer and/or thickening the electrical double layer by forming an adsorbed layer.^66–69 The inhibition efficiency as determined using the EIS data η_z% (based on [R_P = R_ct + R_f] values using the formula given in the Experimental section) follows the expected trend and increases with the concentration of the chitosan–ferrite nanocomposites. At the highest concentration examined (400 ppm), inhibition efficiencies of 97.16%, 97.29%, and 97.38% for Chit-SrFe₁₂O₁₉, Chit-CuFe₂O₄, and Chit-ZnFe₂O₄, respectively, were achieved. Such high efficiencies are a strong indication of the formation of efficient protective layers. Also, the surface coverage values (θ) tend towards unity (0.9738 for Chit-ZnFe₂O₄ at 400 ppm), reflecting almost complete surface coverage by the inhibitor film at the highest concentration. The EIS data also enables the examination of the properties of the film formed itself. The resistance of the film (R_f) is seen to increase appreciably with chitosan–ferrite nanocomposites concentration (e.g., from 13.90 Ω cm² for Chit-ZnFe₂O₄ at 40 ppm to 79.91 Ω cm² for Chit-ZnFe₂O₄ at 400 ppm), reflecting the formation of a resistive barrier layer. The values of film capacitance (C_f) are typically lower than C_dl, in line with the formation of a thicker, more dielectric layer than the electric double layer.⁷⁰ The EIS findings validate that the prepared chitosan–ferrite nanocomposites are good inhibitors for the corrosion of carbon steel in 1.0 M HCl through the formation of protective films. The inhibition efficiency is concentration-dependent for all composites, with Chit-ZnFe₂O₄ having the highest efficiency, followed by Chit-CuFe₂O₄ and Chit-SrFe₁₂O₁₉. The EIS measurements establish that the inhibition process is through the formation of a resistive film (rise in R_f) that suppresses both electrolyte access and charge transfer (rise in R_ct), resulting in a notable decrease in corrosion. The surface area and morphology are the key physicochemical attributes of the individual ferrite nanoparticles that determine the overall composite inhibition performance.

Fig. 8 Nyquist plots, Bode and phase angle plots for steel in 1.0 M HCl solution without and with different concentrations of (Chit-SrFe₁₂O₁₉ (a and d), Chit-CuFe₂O₄ (b and e) and Chit-ZnFe₂O₄ (c and f)) composites at 30 °C.

Table 4 EIS parameters for corrosion of steel in 1.0 M HCl in the absence and presence of different concentrations of (Chit-SrFe₁₂O₁₉, Chit-CuFe₂O₄ and Chit-ZnFe₂O₄) composites at 30 °C^a

Inhibitor	Conc. (ppm)	Rs (Ω cm^2)	Rf (Ω cm^2)	CPEf		Cf (µF cm^−2)	Rct (Ω cm^2)	CPEdl		Cdl (µF cm^−2)	Chi squared (χ^2)	Rp (Rf + Rct)	θ	ηz%
				Y01 (µΩ^−1 s^n cm^−2)	n1			Y02 (µΩ^−1 s^n cm^−2)	n2
a Rs = solution resistance, Rct = charge transfer resistant, Y0, n = constant phase elements, Cdl = double layer capacitance, θ = surface coverage, ηz = inhibition efficiency.
Blank	—	0.5409					19.05	736.27	0.8780	406.90	9.04 × 10^−3	19.05	—	—
Chit-SrFe12O19	40	0.6385	9.17	694.30	0.8789	346.00	79.56	689.00	0.8049	340.83	3.78 × 10^−4	88.73	0.7853	78.53
	100	0.6649	16.55	520.40	0.8429	214.53	97.31	384.60	0.8717	237.14	6.29 × 10^−4	113.86	0.8327	83.27
	200	1.0340	42.03	213.70	0.8338	83.53	113.55	221.60	0.8627	123.32	9.21 × 10^−4	155.58	0.8775	87.75
	300	1.5000	56.40	116.90	0.8328	42.65	350.40	174.70	0.8627	111.98	3.39 × 10^−4	406.80	0.9532	95.32
	400	0.8146	63.90	63.75	0.8131	17.99	607.93	126.00	0.8712	86.17	1.76 × 10^−4	671.83	0.9716	97.16
Chit-CuFe2O4	40	0.6408	12.62	607.50	0.8999	353.38	95.83	475.50	0.8819	314.43	8.62 × 10^−4	108.45	0.8243	82.43
	100	0.5712	17.20	516.30	0.8466	219.36	97.37	384.30	0.9227	291.83	7.14 × 10^−4	114.57	0.8337	83.37
	200	1.8370	44.08	144.10	0.9155	90.34	294.12	206.30	0.8624	131.90	2.67 × 10^−4	338.20	0.9437	94.37
	300	0.9596	59.55	87.82	0.9999	87.77	412.10	164.00	0.8716	110.28	4.14 × 10^−3	471.65	0.9596	95.96
	400	0.8649	69.84	47.81	0.8518	17.73	633.66	108.60	0.8532	68.52	1.50 × 10^−4	703.50	0.9729	97.29
Chit-ZnFe2O4	40	0.7041	13.90	571.50	0.8599	259.94	95.27	401.80	0.8999	279.50	9.57 × 10^−4	109.17	0.8255	82.55
	100	0.5518	28.28	276.00	0.8408	110.12	96.30	291.50	0.8747	174.72	6.50 × 10^−4	124.58	0.8471	84.71
	200	0.8497	45.56	119.40	0.8254	39.63	321.55	199.10	0.8750	134.44	3.98 × 10^−4	367.11	0.9481	94.81
	300	0.8728	62.18	64.99	0.7994	16.30	510.86	142.40	0.8713	96.70	7.07 × 10^−4	573.04	0.9668	96.68
	400	1.3630	79.91	17.17	0.8087	3.61	646.42	47.50	0.8713	28.39	2.98 × 10^−4	726.33	0.9738	97.38

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3.2.4 Adsorption considerations. The degree of surface coverage (θ) gained from the electrochemical measurements (PDP, EFM, EIS) isotherm data fitted in several theoretical adsorption models, such as Langmuir, Freundlich, Temkin, Frumkin, Flory–Huggins, and El-Awady. The parameters and correlation coefficients (R²) for the different adsorption models are summarized in Table 5. The analysis of the various isotherm models indicates that the Langmuir model fits the adsorption data best, with the largest correlation coefficients (R² values close of 1 were determined) for all three composites.⁷¹ The linearized Langmuir plot (Fig. 9) of Chit-ZnFe₂O₄, Chit-CuFe₂O₄ and Chit-SrFe₁₂O₁₉, shows excellent linearity of R² values of 0.9996, 0.9997, and 0.9995, respectively. The Langmuir model assumes monolayer adsorption of modest no interaction between the adsorbed species on a homogeneous surface with a finite number of identical sites. By using the linear plot of C/θ versus C, intercept provide the reciprocal of K_ads.⁷² The K_ads values calculated from the Langmuir model were 0.0782 M⁻¹, 0.0727 M⁻¹ and 0.0537 M⁻¹, for Chit-ZnFe₂O₄, Chit-CuFe₂O₄, and Chit-SrFe₁₂O₁₉, respectively. The corresponding standard free energy of adsorption was calculated using the expression: , wherein R is the gas constant, T is the absolute temperature in degrees Kelvin (303 K), and 10⁶ ppm is the water concentration.⁷³ The resulting values of −28.38 kJ mol⁻¹, −28.20 kJ mol⁻¹, and −27.44 kJ mol⁻¹ were for Chit-ZnFe₂O₄, Chit-CuFe₂O₄, and Chit-SrFe₁₂O₁₉, respectively. The negative values indicate that the adsorption process is spontaneous.⁷⁴ The magnitude of values from −20 to −40 kJ mol⁻¹ indicates the adsorptive process involved physical adsorption (physisorption, that is, by electrostatic interaction) and chemical adsorption (chemisorption, which can be thought of as charge sharing or transfer) involving the chitosan–ferrite nanocomposites and the metal surface.⁷⁵ The higher fit of the Langmuir model for all three composites provides solid evidence that the chitosan–ferrite composites form a monolayer on the carbon steel surface. The order of calculated K_ads and the magnitudes of (Chit-ZnFe₂O₄ > Chit-CuFe₂O₄ > Chit-SrFe₁₂O₁₉) correlated well with the achieved inhibition efficiencies and the physico-chemical properties of the ferrite nanoparticles.

Table 5 Adsorption isotherms models of the inhibitors with values of R², slopes, intercepts, K_ads, and ΔG_ads obtained by using data from electrochemical measurements^a

Adsorption isotherm model	Linear form equation	Technique	Inhibitor	Slope	Intercept	R^2	Kads M^−1	ΔGads kJ mol^−1
a R^2 = regression correlation coefficient, K = binding constant, θ = surface coverage, c = concentration.
Freundlich	log θ = log K + 1/n log C	PDP	Chit-SrFe12O19	0.10810	−0.28294	0.97877	0.5213	−33.16
			Chit-CuFe2O4	0.10535	−0.27330	0.97736	0.5330	−33.22
			Chit-ZnFe2O4	0.09774	−0.25275	0.95955	0.5588	−33.34
Langmuir		EFM	Chit-SrFe12O19	0.89962	73.84235	0.99019	0.0135	−23.97
			Chit-CuFe2O4	0.94619	49.12175	0.98715	0.0204	−24.99
			Chit-ZnFe2O4	0.94931	42.64592	0.99396	0.0234	−25.35
		EIS	Chit-SrFe12O19	0.99261	18.61154	0.99769	0.0537	−27.44
			Chit-CuFe2O4	0.99553	13.76444	0.99916	0.0727	−28.20
			Chit-ZnFe2O4	0.99480	12.78497	0.99938	0.0782	−28.38
		PDP	Chit-SrFe12O19	0.97828	16.02054	0.99950	0.0624	−27.82
			Chit-CuFe2O4	0.97708	14.85207	0.99967	0.0673	−28.01
			Chit-ZnFe2O4	0.97858	13.40201	0.99960	0.0746	−28.27
Frumkin		PDP	Chit-SrFe12O19	1.18111	−2.10323	0.40612	7.8844 × 10^−3	−22.60
			Chit-CuFe2O4	1.46607	−2.31054	0.51726	4.8917 × 10^−3	−21.40
			Chit-ZnFe2O4	1.74358	−2.51981	0.58694	3.0213 × 10^−3	−20.19
Temkin		PDP	Chit-SrFe12O19	10.28473	−4.24152	0.97753	0.6621	−33.76
			Chit-CuFe2O4	10.49258	−4.50646	0.97792	0.6508	−33.72
			Chit-ZnFe2O4	10.97046	−5.02587	0.95867	0.6325	−33.65
Flory–Huggins		PDP	Chit-SrFe12O19	0.72422	−1.36808	0.92221	4.2847 × 10^−2	−26.87
			Chit-CuFe2O4	0.69302	−1.36228	0.94004	4.3423 × 10^−2	−26.90
			Chit-ZnFe2O4	0.68194	−1.33621	0.93478	4.6110 × 10^−2	−27.05
El-Awady		PDP	Chit-SrFe12O19	1.24518	−1.57383	0.93477	0.054457	−27.47
			Chit-CuFe2O4	1.31841	−1.67360	0.94854	0.053777	−27.44
			Chit-ZnFe2O4	1.33708	−1.65761	0.94447	0.057581	−27.61

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Fig. 9 The Langmuir adsorption model for (Chit-SrFe₁₂O₁₉ (a), Chit-CuFe₂O₄ (b) and Chit-ZnFe₂O₄ (c)) composites on the steel surface in 1.0 M HCl using data obtained from PDP measurements at 30 °C.

3.3 Global reactivity parameters

The standard set of global reactivity descriptors provides a practical framework for assessing the fundamental characteristics of chemical compounds under study.⁷⁶ These parameters are valuable for comparing structures and drawing essential insights into their chemical reactivity and thermodynamic stability. The descriptors are derived from the electronic structure of the molecule, specifically the energies of the highest occupied (HOMO) and lowest unoccupied (LUMO) molecular orbitals.⁷⁷ The ionization potential is defined as the minimum energy needed to remove the highest-energy electron from an isolated molecule. The electron affinity describes the accommodation of an excess electron corresponding to the LUMO energy. Molecular electronegativity is calculated as follows:

The electronic chemical potential equals:

The chemical hardness and chemical softness originate from the ionization potential, I, and electron affinity, A:

The system's electrophilicity index equals:

In this work, the DFT calculations were used to characterize the intrinsic electronic structure of representative chitosan/ferrite fragments in aqueous environment, rather than to reproduce individual electrochemical observables. Global reactivity descriptors, band gap, chemical hardness/softness, and electronegativity together with population analysis quantify the tendency of the respective units to donate and accept charge and identify the most nucleophilic and electrophilic regions that are expected to interact with the steel surface and aggressive ionic species. These quantities are defined for isolated molecular units. The inhibitor formulations studied were unraveled to be chemically similar, so the numerical variation in the computed band gaps and hardness values is relatively small compared with the experimental scatter of the electrochemical data. To recapitulate, no formal regression between global reactivity descriptors and impedance or polarization parameters was attempted. Instead, the DFT results are interpreted qualitatively and comparatively.

Table 6 presents a set of parameters determined for the computed systems composed of the NPs and chitosan monomer (Fig. 10). SrFe₁₂O₁₉ (9.111 eV) and CuFe₂O₄ (9.003 eV) have the highest IP values, meaning it is harder to remove an electron from these systems compared to ZnFe₂O₄ (7.734 eV) and SrFe₂O₄ (7.553 eV). This indicates slightly stronger electron binding in SrFe₁₂O₁₉ and CuFe₂O₄.⁷⁸ It is consistent with the observed electronic stabilization. CuFe₂O₄ (4.397 eV) and SrFe₁₂O₁₉ (4.386 eV) have the highest EA values, reflecting their ready acceptance of the electron. ZnFe₂O₄ and SrFe₂O₄ show lower affinities, suggesting less tendency toward reduction. SrFe₁₂O₁₉ (2.363 eV) and CuFe₂O₄ (2.303 eV) are more electronegative than ZnFe₂O₄ (2.096 eV). This observation indicates a stronger electron-attracting capability of the structure. Electronic chemical potential (µ) is, expectedly, negative in all cases. Herewith, SrFe₁₂O₁₉ has the most negative µ, and therefore must gain extra electron density to decrease the potential energy.

Table 6 Global reactivity parameters – ionization potential, electron affinity, electronegativity, and electronic chemical potential – for the NP + chitosan systems

Nanoparticle	Ionization potential, eV	Electron affinity, eV	Electronegativity, eV	Electronic chemical potential, eV
CuFe2O4	9.003	4.397	2.303	−2.303
ZnFe2O4	7.734	3.541	2.096	−2.096
SrFe2O4	7.553	3.116	2.218	−2.218
SrFe12O19	9.111	4.386	2.363	−2.363

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Fig. 10 The optimized structures of CuFe₂O₄ nanoparticle + chitosan (a), SrFe₂O₄ nanoparticle + chitosan (b), ZnFe₂O₄ nanoparticle + chitosan (c), SrFe₁₂O₁₉ nanoparticle + chitosan (d). The copper atoms are rosy, the strontium atoms are brown, the iron atoms are violet, the zinc atoms are yellow, the oxygen atoms are red, the carbon atoms are grey, and the hydrogen atoms are white.

Table 7 summarizes additional global reactivity descriptors. Hardness reflects resistance to charge transfer. SrFe₁₂O₁₉ (2.363 eV) and CuFe₂O₄ (2.303 eV) are the hardest species, while ZnFe₂O₄ (2.096 eV) is the softest. This suggests ZnFe₂O₄ is more chemically reactive due to easier charge redistribution.⁷⁹ Global chemical softness is inversely related to hardness. Thus, ZnFe₂O₄ (0.239 eV⁻¹) is the softest (most polarizable and reactive). On the contrary, SrFe₁₂O₁₉ is the hardest (0.212 eV⁻¹) out of the investigated set. Note that the observed differences are fairly modest.

Table 7 Global reactivity parameters – global chemical softness, global chemical hardness, electrophilicity index, and band gap – computed for the investigated systems

NP	Global chemical softness, eV^−1	Global chemical hardness, eV	Electrophilicity index, eV	Band gap, eV
CuFe2O4	0.217	2.303	1.152	4.606
ZnFe2O4	0.239	2.096	1.048	4.193
SrFe2O4	0.225	2.218	1.109	4.437
SrFe12O19	0.212	2.363	1.181	4.725

---

Electrophilicity index reflects the system's ability to accept electrons. Values are all in the range 1.05–1.18 eV. CuFe₂O₄ and SrFe₁₂O₁₉ appeared to be slightly more electrophilic. This observation aligns with their high electron affinities discussed above. SrFe₁₂O₁₉ exhibits the widest band gap (4.725 eV), making it relatively insulating and least conductive. Whereas ZnFe₂O₄ has the narrowest band gap (4.193 eV), making it relatively electronically active in terms of possible semiconductor behavior. Yes, the analysis of the global reactivity parameters confirms that all four systems exhibit similar performance in the context of their chemical activities against a corrosion promoter.

The spatial distribution of the frontier molecular orbitals was analyzed (Fig. 10–12). The analysis revealed distinct localization patterns depending on the nanoparticle's composition. In the CuFe₂O₄ + chitosan system (Fig. 11), the HOMO (E_HOMO = −9.003 eV) is localized on the organic chitosan fragment, while the LUMO (E_LUMO = −4.397 eV) is centered on the inorganic nanoparticle. This indicates that chitosan acts as an electron donor, and the copper nanoparticle acts as an acceptor.^80,81

Fig. 11 The HOMO and LUMO distribution in CuFe₂O₄ nanoparticle + chitosan. The copper atoms are rosy, the iron atoms are violet, the oxygen atoms are red, the carbon atoms are grey, the nitrogen atoms are blue and the hydrogen atoms are black.

Fig. 12 The HOMO and LUMO distribution in ZnFe₂O₄ nanoparticle + chitosan. The zinc atoms are yellow, the iron atoms are violet, the oxygen atoms are red, the carbon atoms are grey, the nitrogen atoms are blue and the hydrogen atoms are black.

In contrast, the picture changes for the zinc and strontium systems. In both ZnFe₂O₄ + chitosan (Fig. 12) and SrFe₂O₄ + chitosan (Fig. 13), both orbitals—the HOMO (E_HOMO = −7.734 eV and −7.553 eV, respectively) and the LUMO (E_LUMO = −3.541 eV and −3.116 eV, respectively)—are localized predominantly on the inorganic nanoparticle core. In the strontium system, a minor contribution to the HOMO is observed on the nitrogen atom of chitosan. This distribution demonstrates that in these systems, the nanoparticle itself serves as both the donor and acceptor center, governing its interaction mechanism with the metal surface. The observed differences in orbital localization are consistent with the calculated global reactivity parameters and confirm the distinct nature of the inhibitory action of the investigated composites.

Fig. 13 The HOMO and LUMO distribution of SrFe₂O₄ nanoparticle + chitosan. The strontium atoms are brown, the iron atoms are violet, the oxygen atoms are red, the carbon atoms are grey, the nitrogen atoms are blue and the hydrogen atoms are black.

3.4 Electrostatic potential charges

Computed electrostatic potential (ESP) charges and Hirshfeld charges for the investigated NPs are collected in Tables 8 and 9 correspondingly. In the system SrFe₂O₄ + chitosan, the ESP charges on Sr are +1.526e, +1.615e, +1.619e, and +1.254e on the atom closest to the OH group of chitosan. The nearest oxygen in this OH group carries a charge of −0.675e. Compared to −1.143e on the oxygen of the other OH group. The distance between the closest Sr and O atoms is 262 pm. On the Fe nanoparticle, the charges are +0.699e, +0.778e, +0.921e, +0.955e, +1.073e, +1.638e, and +0.484e. The Fe atom closest to the nitrogen of chitosan is nearly neutral, +0.093e. The corresponding N atom carries a charge of +0.296e. The distance between the nearest Fe and N atoms is 207 pm. The charges on the oxygen atoms of the NP range from −0.613e to −1.527e.

Table 8 Electrostatic potential charges (e) computed for the investigated nanoparticles

SrFe2O4
Sr	Fe	O
+1.619	+0.093	−0.188
+1.615	+1.073	−0.882
+1.254	+0.955	−0.613
+1.526	+0.921	−1.352
	+0.778	−1.527
	+1.638	−0.880
	+0.484	−1.021
	+0.699	−0.820
		−0.906
		−0.621
		−0.799
		−0.841
		−0.954
		−0.970
		−0.559
		−0.614

---

ZnFe2O4
Zn	Fe	O
+1.330	+1.134	−1.029
+1.372	+1.135	−1.136
+1.267	+1.652	−1.026
+1.462	+1.293	−0.597
	+1.341	−0.942
	+1.181	−0.745
	+1.378	−1.629
	+1.470	−0.876
		−1.221
		−0.947
		−1.164
		−1.048
		−0.672
		−1.121
		−0.862
		−1.066

---

CuFe2O4
Cu	Fe	O
+1.370	+1.284	−0.895
+1.152	+1.241	−0.699
+0.786	+1.284	−0.841
+1.078	+1.178	−0.944
	+1.142	−0.809
	+1.323	−0.847
	+1.242	−0.749
	+1.064	−1.210
		−0.893
		−0.849
		−0.854
		−1.033
		−0.817
		−1.002
		−1.084
		−0.680

---

Table 9 Hirshfeld charges (e) computed for the investigated nanoparticles

SrFe2O4
Sr	Fe	O
+0.532	+0.171	−0.303
+0.457	+0.401	−0.371
+0.521	+0.217	−0.254
+0.502	+0.413	−0.365
	+0.457	−0.263
	+0.579	−0.342
	+0.075	−0.447
	+0.418	−0.414
		−0.295
		−0.282
		−0.350
		−0.330
		−0.316
		−0.483
		−0.308
		−0.319

---

ZnFe2O4
Zn	Fe	O
+0.241	+0.398	−0.385
+0.505	+0.441	−0.366
+0.518	+0.506	−0.285
+0.592	+0.754	−0.325
	+0.667	−0.315
	+0.358	−0.422
	+0.237	−0.967
	+0.897	−0.356
		−0.418
		−0.382
		−0.324
		−0.322
		−0.378
		−0.508
		−0.332
		−0.404

---

CuFe2O4
Cu	Fe	O
+0.673	+0.529	−0.412
+0.607	+0.458	−0.314
+0.526	+0.404	−0.376
+0.596	+0.426	−0.411
	+0.351	−0.350
	+0.458	−0.415
	+0.377	−0.354
	+0.448	−0.334
		−0.373
		−0.362
		−0.378
		−0.369
		−0.294
		−0.462
		−0.315
		−0.338

---

The ESP charges on the Zn atoms in the system with ZnFe₂O₄ nanoparticle are +1.267e, +1.330e, and +1.462e. The closest Zn atom to the nitrogen of chitosan carries a charge of +1.372e. For the Fe atoms in the nanoparticle, the charges are +1.134e, +1.135e, +1.293e, +1.341e, +1.378e, +1.470e, and +1.652e, with the Fe nearest to the hydrogen of chitosan's –OH group, having a charge of +1.181e. The hydrogen in this –OH group carries a charge of −0.517e, whereas the hydrogen in the remote –OH group, farther from the nanoparticle, has a charge of +0.580e. The Fe⋯H distance between the closest atoms is 249 pm. The oxygen atom with a charge of −1.164e competes with Fe for the interaction with the same H, as evidenced by a shorter O–H distance of 197 pm. The charges on the oxygen atoms within the nanoparticle range from −0.597e to −1.629e.

The ESP charges on the Cu atoms in the CuFe₂O₄ nanoparticle are +0.786e, +1.078e, +1.152e, and +1.370e. The charges on the Fe atoms are +1.064e, +1.142e, +1.178e, +1.241e, +1.242e, +1.284e, +1.284e, and +1.323e. The charges on the oxygen atoms of the nanoparticle range from −1.002e to −0.699e, with the oxygen closest to the –NH₂ group of chitosan carrying a charge of −0.817e. The corresponding atoms of this –NH₂ group exhibit charges of +0.616e (H), −1.311e (N), and +0.485e (H). For comparison, the charges on a different –NH₂ group amount to −1.059e (N), +0.449e (H), and +0.389e (H). The smallest distance between the NP (O site) and chitosan (H site) is 230 pm. The wide distribution of the ESP charges on the SrFe₁₂O₁₉ NP is exemplified by +1.488e on the Sr atom and +0.293e to +1.308e on the Fe atoms. The oxygen atoms in the nanoparticle possess charges varying from −0.068e to −0.867e. The Sr is closest to the chitosan molecule, with distances to its hydrogen atoms amounting to 463 pm and 493 pm.

4. Conclusion

This study demonstrates the successful synthesis of ZnFe₂O₄, CuFe₂O₄, and SrFe₁₂O₁₉ nanoparticles via an ultrasound-assisted PEG route, yielding morphologically tailored ferrites with mesoporous characteristics. XRD analysis confirmed single-phase formation for ZnFe₂O₄ and CuFe₂O₄, while SrFe₁₂O₁₉ exhibited coexistence of hexagonal M-type ferrite and rhombohedral α-Fe₂O₃, indicating a multiphase nature. Incorporation into chitosan-based nanocomposites enabled high-performance corrosion inhibition of carbon steel in acidic media, with inhibition efficiencies exceeding 98% at optimal concentration. The comprehensive electrochemical evaluation-spanning PDP, EFM, and EIS techniques-confirmed a mixed-type inhibition mechanism, predominantly impacting the cathodic process. Increased charge transfer resistance, reduced double-layer capacitance, and near-complete surface coverage underscore the formation of resistive protective films. Adsorption analyses supported spontaneous, monolayer composite–metal interactions with both physisorptive and chemisorptive contributions. Among the systems, Chit-ZnFe₂O₄ exhibited the highest inhibition efficiency, attributed to its favorable textural properties and interfacial activity. These results validate the use of ultrasound-engineered ferrites as multifunctional additives for corrosion-resistant coatings and highlight their potential in advanced material formulations.

Author contributions

T. A., M. O., F. A.: conceptualization, methodology, investigation, synthesis, writing – original draft, resources. M. A. B., A. M. A., M. A. A.: electrochemical analysis, writing – review & editing, validation, visualization, data curation. N. A. A., V. V. C.: computational methodology, software, writing – original draft.

Conflicts of interest

The authors hereby declare no financial interests and professional connections that might bias the interpretations of the obtained results.

Data availability

The data supporting this article have been included in the publication.

Supplementary information (SI) is available. See DOI: https://doi.org/10.1039/d5ra08173d.

Acknowledgements

The authors are thankful to the Deanship of Graduate Studies and Scientific Research at the University of Bisha for supporting this work through the Fast-Track Research Support Program. The results of the work were obtained using the computational resources of Peter the Great Saint-Petersburg Polytechnic University Supercomputing Centre (https://www.spbstu.ru/). This work was also supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. KFU260913]. During the preparation of this work the author(s) used QUILBOT to improve readability and language of the work. After using this tool/service, the author(s) reviewed and edited the content as needed and took(s) full responsibility for the content of the publication.

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48. M. A. Bedair, S. A. Soliman, M. F. Bakr, E. S. Gad, H. Lgaz, I.-M. Chung, M. Salama and F. Z. Alqahtany, Benzidine-based Schiff base compounds for employing as corrosion inhibitors for carbon steel in 1.0 M HCl aqueous media by chemical, electrochemical and computational methods, J. Mol. Liq., 2020, 317, 114015,  DOI:10.1016/j.molliq.2020.114015.
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51. M. A. Bedair, Q. A. Yousif, Z. Fadel, S. Melhi, F. A. Al-Odail and A. M. Abuelela, Experimental and theoretical analyses of the corrosion inhibition efficacy of new penicillanic acid derivatives for carbon steel in hydrochloric acid environment, J. Mol. Struct., 2025, 1328, 141282,  DOI:10.1016/j.molstruc.2024.141282.
52. Q. A. Yousif, M. A. Bedair, Z. Fadel, F. Al-Odail and A. M. Abuelela, Evaluating the efficacy of newly synthesized amino acid derivatives as corrosion inhibitors in acidic solutions, Inorg. Chem. Commun., 2024, 164, 112454,  DOI:10.1016/j.inoche.2024.112454.
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54. M. A. Bedair, In-depth assessment of new coumarin derivative based on azo dye and Schiff base as an effective corrosion inhibitor for steel in 1 M HCl solution and anti sulphate reducing bacteria: Insights from computational and experimental techniques, Inorg. Chem. Commun., 2024, 167, 112693,  DOI:10.1016/j.inoche.2024.112693.
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56. M. A. Abbas, E. I. Arafa, M. A. Bedair, A. S. Ismail, O. E. El-Azabawy, S. A. Baker and H. I. Al-Shafey, Synthesis, Characterization, Thermodynamic Analysis and Quantum Chemical Approach of Branched N, N′-bis(p-hydroxybenzoyl)-Based Propanediamine and Triethylenetetramine for Carbon Steel Corrosion Inhibition in Hydrochloric Acid Medium, Arabian J. Sci. Eng., 2023, 48, 7463–7484,  DOI:10.1007/s13369-022-07520-y.
57. Q. A. Yousif, S. S. Malhotra, M. A. Bedair, A. Ansari and A. K. Hadi, Safflower plant extract as a sustainable corrosion inhibitor for carbon steel in acidic media: a combined electrochemical and computational study, RSC Adv., 2025, 15, 21006–21025,  10.1039/D5RA03333K.
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60. M. A. Bedair, A novel coumarin-azo Schiff base for dual corrosion inhibition for steel in acidic environments and anti-SRB protection: Experimental and computational insights, Results Surf. Interfaces, 2025, 19, 100511,  DOI:10.1016/j.rsurfi.2025.100511.
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62. M. Ragab and M. A. Bedair, The effect of permanent magnet stirring on the corrosion resistance of Sn-2.0Ag-0.5Cu-2Zn solder alloys in NaCl solution, Mater. Chem. Phys., 2023, 302, 127774,  DOI:10.1016/j.matchemphys.2023.127774.
63. A. M. Abuelela, J. Kaur, A. Saxena, M. A. Bedair, D. K. Verma and E. Berdimurodov, Electrochemical and DFT studies of Terminalia bellerica fruit extract as an eco-friendly inhibitor for the corrosion of steel, Sci. Rep., 2023, 13, 19367,  DOI:10.1038/s41598-023-45283-0.
64. S. D. Kotabagi, S. K. Rajappa, R. L. Minagalavar, M. R. Rathod, J. G. Suma and A. M. Sajjan, Expired Lircetam drug as a corrosion inhibitor for low-carbon steel in 1 M HCl: Experimental, theoretical, and quantum chemical insights, Results Surf. Interfaces, 2025, 18, 100459,  DOI:10.1016/j.rsurfi.2025.100459.
65. M. M. Y. Modwi, H. Feng, M. K. Hadi, N. Chen, J. Hou, E. Kamal and K. Yang, Eco-friendly corrosion inhibitor of Q235 carbon steel in 1.0 M HCl by Isatin/Chitosan Schiff base, J. Mol. Struct., 2025, 1321, 139592,  DOI:10.1016/j.molstruc.2024.139592.
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68. M. A. Bedair, H. M. Elaryian, A. H. Bedair, R. M. Aboushahba, A. El-Aziz and S. Fouda, Novel coumarin-buta-1,3-diene conjugated donor–acceptor systems as corrosion inhibitors for mild steel in 1.0 M HCl: Synthesis, electrochemical, computational and SRB biological resistivity, Inorg. Chem. Commun., 2023, 148, 110304,  DOI:10.1016/j.inoche.2022.110304.
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72. S. Melhi, M. A. Bedair, E. H. Alosaimi, A. A. O. Younes, W. H. El-Shwiniy and A. M. Abuelela, Effective corrosion inhibition of mild steel in hydrochloric acid by newly synthesized Schiff base nano Co(II) and Cr(III) complexes: spectral, thermal, electrochemical and DFT (FMO, NBO) studies, RSC Adv., 2022, 12, 32488–32507,  10.1039/D2RA06571A.
73. A. M. Ashmawy, R. Said, I. A. Naguib, B. Yao and M. A. Bedair, Anticorrosion Study for Brass Alloys in Heat Exchangers during Acid Cleaning Using Novel Gemini Surfactants Based on Benzalkonium Tetrafluoroborate, ACS Omega, 2022, 7, 17849–17860,  DOI:10.1021/acsomega.2c01119.
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77. F. Al-Odail, M. A. Bedair, M. A. Alkhalifah and A. M. Abuelela, Comprehensive structural insights and electrochemical evaluation of rhamnose and salicin for green corrosion protection of carbon steel in acidic medium, RSC Adv., 2025, 15, 37429–37446,  10.1039/D5RA06243H.
78. Q. A. Yousif, M. A. Bedair, A. M. Abuelela, A. Ansari, S. S. Malhotra and Z. Fadel, High-performance corrosion inhibitors for carbon steel in hydrochloric acid: electrochemical and DFT studies, RSC Adv., 2025, 15, 28666–28688,  10.1039/D5RA04952K.
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80. M. Gab-Allah, M. Bedair, A. Elged, S. Soliman, E. Badr and M. Bakr, Empirical and Computational Investigation of Cationic Gemini Surfactants as Anti-Corrosive Inhibitors for Mild Steel in Acid Medium and its silver Nano Structure synthesis and Analysis., Egypt, J. Chem., 2023, 66(13), 2013–2031,  DOI:10.21608/ejchem.2023.222841.8256.
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