Synthesis and characterization of Sr-doped Ce/Mn nanocomposites for fuel cell applications

2.1 Chemicals and reagents

Strontium nitrate Sr(NO₃)₂ (99.9% pure), cerium nitrate hexahydrate Ce(NO₃)₃.6H₂O (99.9% pure), manganese nitrate hexahydrate Mn(NO₃)₂.4H₂O (99.9% pure), citric acid, ethanol, ammonia solution, and deionized water of analytical grade were purchased from Sigma Aldrich and used for synthesis process without any further reaction/purification.

2.2 Synthesis of Sr doped Ce-Mn nanocomposites

The Sr_xCe_1-xMn_y (x= 0.03, 0.05, and 0.07, y=1) nanocomposites were synthesized using the sol-gel method. The prepared samples were named SCM1, SCM2, and SCM3 for x = 0.03, 0.05, and 0.07, respectively. The strontium nitrate [Sr(NO₃)₂], cerium nitrate hexahydrate [Ce(NO₃)₃.6H₂O], manganese nitrate hexahydrate [Mn(NO₃)₃.4H₂O], and citric acid were used as precursors. The stoichiometric amount of the material was dissolved in deionized water. This reaction mixture was subjected to ultrasonication to homogenize the solution. The mixed solution was continuously stirred and heated at 80°C until the formation of a gel. The pH value was maintained around 7 by the addition of NH₄OH solution. As the final step, the whole mixture was constantly stirred at 120°C to allow for the sol-gel auto-combustion process to obtain the final product. The powder product was collected, ground, and calcined at 800°C for 5 h to release the remaining nitrates and organics gel (Fig. 1). For further investigation, scanning electron microscopy (SEM) and XRD were employed for the desired crystalline structure and surface morphological analysis (Ahmad et al. 2017).

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Fig. 1.

Schematic diagram for the synthesis of Sr-doped Ce/Mn Nanocomposites.

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2.3 Fuel cell construction and performance

The cathode, anode, and solid electrolyte materials are the basic parts of a fuel cell. The electrolyte, which is the central part of a fuel cell, plays a crucial function in a solid oxide fuel cell as an electrode, allowing oxide ions to migrate via oxygen vacancies. The materials must have high conductivity of oxide ions and high density as well to avoid gas mixing and low electronic conductivity (Ferkhi et al., 2016). For understanding of single-cell performance, the power density of the membrane plays an important role in cell performance. The power density must be calculated via a particular voltage, RH, and temperature. However, in a reported fuel cell study, the overall calculated performance density at high temperature was recorded comparatively high, which is costly and hard to achieve the required temperature in portable devices (Wang et al., 2024). Further details have been shown in the given schematic 1.

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Schematic 1.

Working diagram of solid oxide fuel cell

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The basic principle of a fuel cell depends upon the galvanostatic mechanism, as shown in the schematic diagram. Two types of conductivities are involved in a solid oxide fuel cell. Electronic conductivity and ionic conductivity are involved in a fuel cell. Self-explained fuel cell schematic depicts the open merit process via electrolyte and electronic conduction (Hao et al., 2017). Many young researchers focusing on the efficacy of fuel cells are facing challenges as well. One basic/crucial challenge in a solid oxide fuel cell is the achievement of a high desired temperature of 700-750°C. The second crucial challenge of the fuel cell is the efficacy of the fuel cell. Till now, 68.6% of fuel cell efficacy has been reported (Ferkhi et al., 2016).

3.1 Structural analysis

The phase and crystallinity of the deposited form of Sr-doped Ce/Mn Nano-composites determine the dependency of the working efficiency of the fuel cell. In this part of the experimental analytical approach, the structural analysis of Sr-doped Ce/Mn nanocomposites has been performed, as depicted in Fig. 2.

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Fig. 2.

XRD graph of 3% Sr-doped, 5% Sr-doped, and 7% Sr-doped with CeMnO₃.

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The crystal structure of CeMnO₃ nanoparticles was identified by XRD patterns, which have been presented in Fig. 2. Graphs of 3% Sr-doped, 5% Sr-doped, and 7% Sr-doped nanomaterials synthesized by the sol-gel method, namely SCM-3, SCM-5, and SCM-7, respectively. Well-matched XRD peaks of the Cubic crystal system, Fm-3m Space group confirmed using JCPDS# 00-034-0294 and Miller indices (111), (200), (220), (311), (400), and (331), respectively. Some other peaks, 29.77 and 30.92 of the Orthorhombic Phase of Mn₈O_16, confirmed by using JCPDS# 96-210-5816 and miller indices (040) and (026), respectively (Jianshen et al., 2024). XRD pattern confirmed the successful synthesis material and shows a decreasing trend in intensities by increasing doping concentration. In addition, a decreasing trend in crystallite size was also recorded by adopting 3% Sr-doped, 5% Sr-doped, and 7% Sr-doped nanomaterials with Ce/Mn composites. Crystallite size of Sr-doped Ce/Mn composites has been calculated by using the Scherrer formula, and the value of the shape factor is 0.90. Values of Crystallite size, Miller indices (hkl), and d-spacing at the high intensity peak have been shown in Table 1. One diffraction peak of CeO₂ at (111) existence of CeO₂ in CeMnO₃ nanoparticles. After doping Sr, the intensities become weaker and broader. Hu et al. (2019) reported that some secondary phase at * marked peaks of Mn₂O₃ are visible. According to J. Wang et al (2024), Weaker and border peaks were observed low crystallinity caused by smaller crystal size and more structural defects (Yue et al., 2019). Barelli et al. (2022) observed this behavior in SEM results.

3.2 Analysis of surface morphology

The surface morphology of synthesized Sr_xCe_1-xMn_y (y=1) samples with varying strontium (Sr) concentrations (x=0.03, 0.05, 0.07) was investigated using SEM at magnifications of 25,000× and 50,000×, as presented in Fig. 3. For the sample with x=0.03 (images 1a and 1b), the microstructure exhibits agglomerated particles with relatively large grain clusters and irregular morphologies. The observed particles appear densely packed, indicating moderate porosity. A heterogeneous distribution of particle sizes is evident, with average grain dimensions in the submicron range. The compact morphology may hinder electrolyte penetration but suggests good particle connectivity, beneficial for electrical conductivity.

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Fig. 3. (a)

1a, 1b.SEM images of prepared sample Sr_xCe_1-xMn_y (x=0.03, y=1), 2a, 2b. SEM images of prepared sample Sr_xCe_1-xMn_y (x=0.05, y=1), 3a, 3b. SEM images of the prepared sample Sr_xCe_1-xMn_y (x=0.07, y=1) at different scales.

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Fig. 3. (b)

The conductivity behavior of prepared samples (Sr_xCe_1-xMn_y, where x= 0.03, 0.05, and 0.07, y=1).

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As the Sr concentration increases to x=0.05 (images 2a and 2b), the morphology undergoes noticeable transformation. The particles become more refined and less agglomerated compared to the x=0.03 sample. Smaller grains are well distributed with slightly increased surface roughness, indicating a higher degree of surface area exposure. The reduction in agglomeration and increase in nano-structuring may enhance active surface sites, favoring applications in catalysis or electrochemical systems.

For their highest doping level, x=0.07 (image 3a and 3b), the sample exhibits a more porous structure with well-developed granular morphology. The particles are loosely packed and display a higher degree of porosity and fragmentation. Sharp-edged grains are observed alongside more spherical particles, possibly due to varied nucleation and growth mechanisms at higher Sr content. The morphology can significantly improve electrolyte diffusion and ion transport, indicating the potential for improved performance in energy storage or sensing applications.

Overall, the SEM analysis reveals that increasing SR contents in the Sr_xCe_1-xMn_y system leads to reduced particle agglomeration and enhanced porosity. The morphological evolution from a compact porous nanostructure as x increases from 0.03 to 0.07 suggests tunable microstructural features that can be tailored for specific functional applications.

According to the results of the SEM analysis, the structure of the grains and their grain boundaries in the sample are not distinguishable and do not have a similar size across the surface. These boundaries may play a particular role in determining the nature of electrical conduction; certainly, the grain boundaries may impede the flow of charges within the material and, consequently, the properties of the material. Moreover, the percentage yield of the sample and the quantitative determination of the elements present in it also play an important role in seeing whether the synthesized material can be used for different purposes or not. Fig. 3(a) (H-1, H-2, H-3) highlights quantitative analysis on the sample, including the chemical content as well as the details of the elements in the sample. This verification is crucial for establishing the observed physical characteristics with the chemical makeup of the material and to fine-tune the synthesis process to obtain the state of the art. Altogether, the structural, elemental, and purity data present a holistic picture of the material to the researcher. These kinds of synergistic approaches are important to design ultra-coherent nano-composite materials that can be used within high-technology industries, giving a solid basis for further investigation of the subject (Knight et al., 2015; Pasierb et al., 2021; Lee et al., 2013; Mai et al., 2015; Sailaja et al., 2016; Stockford et al., 2015).

4.3 Analysis of current-voltage

The investigations investigations of the said properties have revealed that the conductivity of the synthesized samples enhances with the enhanced concentration of Ce and Mn dopants in the sample, and the resistivity of the synthesized sample decreases with time. As it was expected, the investigated materials are semiconductors as the resistivity of the films has decreased and the drift motion of the electric ions carriers increased. From the graph, it can be inferred that as dopant content rises, conductivity rises as well, which implies the possibility of use in circuitry. Verwey hopping mechanism describes electrical conduction in ferrites as the result of electron displacement between the ions of different valency being located in the lattice sites at random. Fig. 3(b) indicates that the high resistance range is 10⁵-10⁸ Ω; nevertheless, this may be because of the high conductivity of material (Perry et al. 2018). This high conductivity is due to the hopping of electrons between ferric (Ce³⁺) and ferrous (Mn²⁺) ions in B-sites. The observed behavior supports the hypothesis that the synthesized materials may possess suitable characteristics for electrical applications (Yarahmadi et al., 2021); (Lv et al., 2015). The electrical behavior of the compound SrxCe1-xMny (where x is 0. 03, 0. 05, 0. 07 and y is 1) can be well elucidated based resistivity (ρ) measurements with the specimen at room temperature as depicted in Fig. 4(a). The results indicate that all samples possess exactly opposite behaviors for conductivity as well as resistivity (Hung et al. 2019).

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Fig. 4.

(a) Plot (αhv)² versus energy band gap (eV) of Sample (Sr_xCe_1-xMn_y, where x= 0.03, y=1), (b) (Sr_xCe_1-xMn_y, where x= 0.05, y=1), (c) (Sr_xCe_1-xMn_y, where x= 0.07, y=1).

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4.4 UV-Visible spectroscopy

Energy gap (eV), transmittance, absorbance, and reflectance are the primary study areas of current experimental analysis. The optical properties of synthesized nanomaterials can be explained via UV-visible spectra from the range (200 nm to 1100 nm Absorption wavelength) as well as the Tauc plot (optical bandgap of synthesized nanomaterials plotting absorption coefficient (α) against photon energy (hν). Although optical research may take many different forms of analysis, UV-visible spectroscopy is one of the important, intriguing techniques for studying functional properties. The energy band gap and particle size of the material have an inverse relationship with the absorption wavelength. The given formula is utilized to calculate the absorption coefficient α and energy band gap (Ali et al., 2022).

$\begin{array}{c}\alpha \text{hv}=\text{A}{(}^{\text{h}}\\ {\text{E}}_{\text{g}}=\text{hc}/\lambda \end{array}$

Where n is an index that can take on the values of 1/2, 3/2, 2, or 3, based on the kind of transition of electrons causing the reflection, and Eg is the energy gap, constant A, which varies for various transitions. Direct transition assessed by the all-energy gap. Figs. 4(a-c) shows the UV spectra, which were measured between 1.62-1.98 eV. At x=0.70 and y=1, the absorption spectra with Ce and Mn substitution have a minimum band gap of 1.62 eV, which is appropriate for better optical qualities. The synthesized materials’ band gap decreased steadily as their composition grew, which is characteristic of semiconductor materials. Particle size also impacts optical qualities, with smaller particles often having superior optical properties (Yarahmadi et al., 2021). The absorbance measurements indicate sunlight absorption, making these materials appropriate for solar cell as fuel cell applications. Specifically, the composition Sr_xCe_1-xMn_y (x=0.07, y=1) is ideal for Solar cell as fuel cell production and energy storage devices. It is clear from the plots that if the molar concentration of Sr increases from 0.03 to 0.07, y=1, the energy bandgap value decreases from 1.98 to 1.62, as shown in Figs. 4(a and c) (Bhushan et al. 2010).

From Table 2. As long as the dopant concentration of Sr_x increases from 0.03, 0.05, and 0.07 molarity ratios, Sr_xCe_1-x Mn_y (x=0.03, 0.05, 0.07, y=1), the energy bandgap decreases from 1.98 to 1.62 finally. This demonstrates that if the minimal ratio of Sr increases, materials become increasingly conductive (Yarahmadi et al., 2021).

4.5 Dielectric analysis

The dielectric characteristics of Ce³⁺ substituted Sr_xCe_1-xMn_y; (x=0.03, 0.05, 0.07, y=1) at room temperature were determined with the frequency ranges of 4 Hz to 8 MHz (Mazumder et al., 2019). From the results presented in Figs. 5 and 6, it may be concluded that for all samples, the dielectric constant decreases with increasing frequency and starts to level off at frequencies above 10 kHz. At low frequencies, the behavior of the dielectric is dependent on the space charge and dipolar polarization. In the Ce³⁺ substituted Sr samples, oxygen and Ce vacancies cause the formation of space charges. In lower frequencies, dipoles can orient themselves along the direction of the electric field, whereas in higher frequencies, phase retardation takes place, and dipoles are unable to follow the oscillations of the electric field. In this case, the obtained results are in good agreement with the descriptions of the dipole relaxation in the literature (Li et al., 2016). On the same note, the positive dielectric constant value recorded in the samples may be due to free oscillating electrons that create a plasmonic state that resembles that of metal plasma oscillations when an electric field is applied. Furthermore, Figs. 5 and 6 demonstrate that the dielectric constant is maximum for the sample of Sr_xCe_1-xMn_y (x=0.07, y=1) at low frequencies. The tangent loss (tan δ) first drops as frequency increases up to 10 kHz, after which it rises. The minimum loss is recorded for Sr_xCe_1-xMn_y (where x=0.05 and y=1). This behavior supports the concept proposed by Koop and the two-layer model of Maxwell-Wagner for magnetization, electrical conduction, and electron and grain responses at different frequencies (Bellino et al., 2016; Tahir et al., 2023; Munir et al., 2023). Similar studies for biomedical applications have been conducted and successfully applied (Ahmed et al., 2025; Badshah et al., 2025).

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Fig. 5.

(a) Dielectric constant of prepared sample (Sr_x Ce_1-x Mn_y where x = 0.03, y=1, (b) Dielectric constant of prepared sample (Sr_x Ce_1-x Mn_y where x = 0.05.

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Fig. 6.

Dielectric loss and tangent loss of prepared samples (Sr_xCe_1-xMn_y, where x=0.03, 0.05, 0.07, y=1).

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4.6 Electrochemical behavior

At normal temperature, the electrochemical study was conducted with a scan rate of 1 mVsec^-1. The computed values have been compiled in Table 2, and the cyclic voltammetry (CV) has been visually depicted in Fig. 7. As the applied potential difference (V) increased, variations in the form of the CV curves were seen. Using a slurry approach, the as-prepared H-1, H-2, and H-3 samples were put onto nickel foam electrodes for use in energy storage applications. A potentiostat with three electrodes, the functioning electrode, the counter electrode, and the reference electrode (Ag/AgCl) was used to investigate electrochemical studies. To calculate specific capacitance (C_sp), use the formula C_sp=I×Δt/m×3600, where I(A) is the current discharge, Δt is the discharge period, and m(g) is the mass of the active specimen. The specific capacitance of all synthetic samples was determined to be (382.39, 436.97, and 500.312) F/g. The C_sp value was greatest for sample H-3 and lowest for sample H-1. A similar tendency was previously noted by several researchers. They have all been displayed as computed values in Table 3. The substantial dependency of this outcome may be explained by an increase in electrochemical activity. The electrochemical function of the electrode can be developed by storing more electrolytic ions during the intercalation process, which is made feasible by this kind of porous nanostructure. Therefore, the unique pseudocapacitive property is ascribed to the intrinsic electrochemical activity of transition metal sites, which might be greatly enhanced by generating anion vacancies, thus offering a possible material response to future energy storage requirements (Elanthamilan & Wang, 2023; Dastgir et al., 2025; Li et al., 2024).

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Fig. 7.

CV curves of prepared samples Sr_xCe_1-xMn_y, (where x=0.03, 0.05, 0.07 and y=1).

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