Study of the Structure and Catalytic Activity of B-Site Doping Perovskite for an Inferior Anthracite Coal Combustion

Abstract

The unique structure and physical properties of perovskite-type catalysts make them highly promising for catalyzing efficient coal combustion. Mesoporous perovskite LaNi_xFe_1−xO₃ (x = 0.2, 0.4, 0.6, 0.8) coal combustion catalysts were synthesized using the sol–gel method. The effects of the doping amount of B-site doped nickel on both the crystal structure and catalytic performance were investigated. X-ray diffraction, scanning electron microscopy, and nitrogen adsorption–desorption tests were used to characterize the catalyst samples. Thermogravimetric analysis (TG) and activation energy (E_a) calculations were used to assess the catalyst’s activity for the catalytic combustion of anthracite coal (JF coal, originating from Shanxi, China). Results revealed that nickel doping created lattice distortion and Ni-Fe alloy interactions. The difference in nickel doping significantly affects the morphology and catalytic activity of perovskite. The addition of LaNi_0.6Fe_0.4O₃ (NI6) with a mass fraction of 5% resulted in the highest average burning rate value (v_a = 4.52%/min) of JF coal among all synthesized catalysts. The E_a of JF coal catalytic combustion, calculated using the Coats–Redfern method and the Doyle method, showed a good agreement with the TG curves. The LaNi_xFe_1-xO₃ series catalysts were found to significantly decrease the E_a of JF coal combustion, with a maximum reduction of 42% compared to the case without any catalyst added. Among the synthesized catalysts, NI6 exhibited a favorable catalytic combustion performance and is thus a promising candidate for the clean and efficient utilization of coal resources.

1. Introduction

Coal currently plays a major role in fulfilling global energy demand [1]. With a focus on energy conservation and carbon reduction, the clean and efficient use of coal resources is now an urgent issue. Achieving this objective can improve energy use efficiency and reduce the global environmental burden [2]. Catalysts have emerged to promote clean coal resource utilization. These catalysts facilitate efficient coal utilization by promoting complete coal combustion or upgrading coal combustion waste by-products into high-calorific-value hydrocarbons. For instance, the catalytic upgrading of coal tar using MgO-supported Pt-Ni bimetallic nanoparticles can yield valuable hydrocarbon compounds [3,4]. Despite their benefits, these catalysts have some drawbacks such as catalyst loss, equipment corrosion, poor thermal stability, and high cost [5,6,7]. In the current context of energy conservation and carbon reduction, finding new coal combustion catalysts that are highly efficient and cost-effective has become a hot research topic. Perovskite is considered the most promising catalyst or catalyst carrier for clean coal utilization, thanks to its high catalytic activity, low cost, and excellent thermal stability [2].

The perovskite has a chemical formula of ABO₃, where A represents a rare or alkaline earth metal ion and B represents a transition metal ion [8]. Elements with similar radii can replace A/B in the perovskite structure. The various metal combinations in perovskites promote their catalytic activity and stability [9]. Typically, the catalytic activity of perovskites is determined by B-site doping, while the A-site cation is believed to be responsible for their thermal stability and anti-coke properties [10]. Dingshan Cao et al. [11] increased the yield of direct chemical cycle hydrogen from coal by using BaMnO₃ as an oxygen carrier. Shenglong Liu et al. [12] utilized 3D-LaNiO₃ as a catalyst to produce hydrogen from bio-oil and achieved notable improvements in both hydrogen yield and resistance to coke deposition.

Coal produced in the JiaFeng (JF) region of China is classified as inferior coal due to its high carbon content and low volatile matter, resulting in low combustion efficiency. However, the stable production and cost advantages of JF coal have attracted the attention of many coal-fired enterprises and scholars in China. It is evident that direct combustion of JF coal does not align with the industry trend of clean and efficient utilization of coal resources. Therefore, the application of high-performance perovskite catalysts to the catalytic combustion of JF coal may achieve the clean utilization of JF coal, injecting affordable and clean power into coal-fired enterprises.

The determination of kinetic and thermodynamic parameters is the foundation for understanding the catalytic mechanism and clean utilization of coal resources. This paper will begin by utilizing the sol–gel method to synthesize a series of LaNi_xFe_1−xO₃ (x = 0.2, 0.4, 0.6, 0.8) perovskite catalysts, followed by investigating their physicochemical properties and morphological structures through various advanced characterization techniques. Subsequently, the catalytic performance of the perovskite catalysts will be evaluated via thermogravimetric analysis (TG). Finally, the combustion activation energy (E_a) of JiaFeng (JF) coal will be calculated using the Coats–Redfern (CR) and Doyle methods. For ease of reading, LaNi_0.2Fe_0.8O₃ catalysts will be referred to as NI2, where “NI” represents nickel doping and the digit “2” indicates the doping amount X = 0.2. Additionally, NI4, NI6, and NI8 will be used to refer to the other catalysts correspondingly.

2. Method and Experiments

Scanning electron microscopy (SEM), X-ray diffraction (XRD), and nitrogen adsorption–desorption experiments were conducted to characterize the catalyst structure. TG was performed on samples without catalyst addition and four samples with 5% mass fraction catalyst addition. In addition, the CR method and the Doyle method were used to investigate the kinetic parameters of JF coal combustion. The proximate analysis and ultimate analysis of JF coal are provided in

Table 1. Proximate analysis and Ultimate analysis of primary JF coal.

Sample	Proximate Analysis (%)				Ultimate Analysis (%)					Calorific Value /MJ Kg−1
	Mad	Vad	Aad	FCadb	Car	Har	Oar	Nar	St,ar	Qnet,p,ar
JF Coal	3.89	5.54	18.53	72.04	66.96	2.17	1.54	0.89	0.45	21.51

M_ad: Moisture, as air dried basis; V_ad: Volatile matter, as air dried basis; A_ad: Ash, as air dried basis; FC_ad^b: Fixed carbon, as air dried basis, with a correction for mineral matter; C_ar: Carbon, as received basis; H_ar: Hydrogen, as received basis; O_ar: Oxygen, as received basis; N_ar: Nitrogen, as received basis; S_t,ar: Sulfur, total, as received basis; Q_net,p,ar: Net calorific value, proximate basis, as received basis.

. Based on the table, it can be observed that JF coal has a lower volatile matter content and a higher carbon content, resulting in poor combustion performance under conventional burning conditions.

2.1. Preparation of Perovskite Samples

The sol–gel method has been widely used for synthesizing perovskites in many studies [13,14]. In this study, a series of LaNi_xFe_1−xO₃ (x = 0.2, 0.4, 0.6, 0.8) perovskite catalysts were synthesized using the sol–gel method and with citric acid as the complexing agent. The reagents used in the synthesis included Ni(NO₃)₃-6H₂O (Xilong Scientific Co., Ltd., Shantou, China; Analytical Reagent), Fe(NO₃)₃-9H₂O (Sinopharm Chemical Reagent Co., Ltd., Shanghai, China; Analytical Reagent), La(NO₃)₃-6H₂O (Shanghai Aladdin Bio-Chem Technology Co., Ltd., Shanghai, China; Analytical Reagent), and citric acid monohydrate (Sinopharm Chemical Reagent Co., Ltd.; Analytical Reagent).

First, the required amounts of Ni(NO₃)₂-6H₂O, Fe(NO₃)₃-9H₂O, citric acid monohydrate, and La(NO₃)₃-6H₂O were weighed and dissolved in a small amount of deionized water by stirring. Next, the appropriate amount of ethylene glycol was added to the solution, followed by stirring for 30 min at 40 °C. Then, the appropriate amount of ammonia (Guangdong Guanghua Sci-Tech Co., Ltd.; Shantou, China, Analytical Reagent) was added to adjust the pH value of the solution to around 7, and stirring was continued for 30 min at 80 °C. The solution was subsequently calcined in a muffle furnace for 30 min at 200 °C, followed by further calcination at 800 °C for 4 h. The resulting catalyst was then ground, crushed, and sieved to obtain catalyst powder with particle sizes ranging between 45 μm and 75 μm.

2.2. Material Characterisation

The crystal structure of the catalyst was characterized by using the XRD technique using a Bruker D8 device with Cu-Kα radiation. The operating voltage was set at 35 kV with a current of 30 mA, and the diffraction angle (2θ) ranged from 0° to 90° with a step size of 0.02°. To observe the catalyst surface structure, SEM images were obtained using a Philips XL30 microscope scan. In addition, to characterize the specific surface area (SSA) and average pore size of the synthesized LaNi_xFe_1−xO₃ catalysts, nitrogen adsorption–desorption tests were performed using an Autosorb series microporous physisorption/chemisorption analyzer from the USA. Finally, a TG analysis was performed using a thermogravimetric analyzer (PerkinElmer STA6000) to analyze the combustion characteristics of JF coal both with and without a catalyst at a 5% mass fraction.

The TG procedure was conducted as follows: First, the coal was mixed with a 5% mass fraction of the catalyst using an agate mortar for 60 min to ensure a thorough mixture. Next, specimens weighing 10 ± 0.01 mg were weighed and spread out flat in the crucible. Air with a flow rate of 100 mL/min was set as the inlet gas, and the temperature was raised from 25 °C to 900 °C at a heating rate of 15 K/min. TG-DTG curves of each sample were then recorded.

2.3. Methods and Formulas

When the heating rate is constant, the CR and the Doyle methods can fit the kinetic parameters of coal combustion more precisely. These methods are straightforward and rapid to calculate [15]. In the 1930s, Valette introduced the concept of $\beta =\frac{dT}{dt}$ (heating rate) in the kinetic equations [16]. Therefore, the kinetic equation of the indefinite temperature and heterogeneous reaction can be written as:

$$\frac{d\alpha }{\mathrm{dT}}=\frac{1}{\beta }k\left(T\right)f\left(\alpha \right)$$

(1)

Here, α represents the conversion rate, and k(T) represents the temperature-dependent equation.

When the heating rate is constant, the conversion rate α can be expressed as:

$$\alpha =\frac{m_0-m}{m_0-m_{\infty }}$$

(2)

Here, m₀ refers to the initial mass of the original coal, m refers to the mass of the sample at a certain time t during combustion, and m_∞ refers to the residual mass after combustion is complete.

According to Arrhenius’s equation:

$$k=A{e}^{\frac{-E}{RT}}$$

(3)

Here, T refers to the temperature in the Kelvin scale, A refers to the frequency factor, E refers to the activation energy, and R refers to the ideal gas constant.

In the CR method, the function f(α) is assumed to be:

$$f\left(\alpha \right)={\left(1-\alpha \right)}^n$$

(4)

Here, n refers to the number of reaction stages. By combining this with the previous equation, we can obtain the following expression:

$$\frac{d\alpha }{\mathrm{dT}}=\frac{A}{\beta }\exp \left(-\frac{E}{RT}\right)\cdot {\left(1-\alpha \right)}^n$$

(5)

The above equation can be integrated to obtain:

$$\ln \left[\frac{-\ln {\left(1-\alpha \right)}^{}}{T^2}\right]=\ln \left[\frac{AR}{\beta E}\left(1-\frac{2RT}{E}\right)\right]-\frac{E}{RT}\left(n=1\right)$$

(6)

$$\ln \left[\frac{1-{(1-\alpha )}^{1-n}}{T^2\left(1-n\right)}\right]=\ln \left[\frac{AR}{\beta E}\left(1-\frac{2RT}{E}\right)\right]-\frac{E}{RT}\left(n\ne 1\right)$$

(7)

Let the left side of the equation be the y-value and $X=\frac{1}{T}$, get $Y=aX+b$. The slope $a=-\frac{E}{R}$, the intercept $b=\ln \left[\frac{AR}{\beta E}\left(1-\frac{2RT}{E}\right)\right]$. Therefore $E=-aR$, and by default $1-2\frac{RT}{E}=1$. Then have the frequency factor $A=\beta \frac{E}{R}\exp \left(b\right)$.

In the Doyle method, the function f(α) is [17]:

$$f\left(\alpha \right)={{\displaystyle \int }}_0^{\alpha }\frac{d\alpha }{{\left(1-\alpha \right)}^n}$$

(8)

Simplifying the integral results in:

$$\ln \left[-\ln \left(1-\alpha \right)\right]=\ln \left(\frac{AE}{\beta R}\right)-5.314-0.1278\frac{E}{T}\left(n=1\right)$$

(9)

$$\ln \left[\frac{{\left(1-\alpha \right)}^{1-\mathrm{n}}-1}{\mathrm{n}-1}\right]=\ln \left(\frac{AE}{\beta R}\right)-5.314-0.1278\frac{E}{T}\left(n\ne 1\right)$$

(10)

Let the left side of the equation be the y-value and $X=\frac{1}{T}$, can rewrite the equation as $Y=aX+b$. Then, $E=-a/0.1278$ and the frequency factor $A=\frac{\beta R}{E}\exp \left(b+5.314\right)$.

By utilizing these two methods, the kinetic parameters of JF coal combustion under a specific heating rate can be obtained through the fitting.

3. Results and Discussion

3.1. X-ray Diffraction Analysis

To determine the crystal structure of the LaNi_xFe_1−xO₃ catalysts synthesized by the sol–gel method, XRD analysis was performed on the catalyst powders (Figure 1).

As shown in the figure, the diffraction peaks of the synthesized catalysts match well with the perovskite-type structure (JCPDS PDF # 74-2203) at crystal planes (100), (110), (200), and (310). This confirms that the desired perovskite phase was formed and demonstrates that the nickel doping did not alter the main perovskite crystal structure. However, as the nickel doping increases, the overall XRD diffraction peaks shift towards higher diffraction angles. Compared to the strongest diffraction peak of NI2 (2θ = 31.92°), the strongest diffraction peak of NI8 (2θ = 32.4°) shifts 0.48° towards a higher diffraction angle. This phenomenon can be attributed to cell shrinkage caused by the replacement of Fe³⁺ (64 pm) with Ni³⁺ (62 pm), which has a smaller radius. Following Bragg’s Law, cell shrinkage causes a move of the diffraction peaks to the right and high-angle diffraction peaks are more visibly affected. Furthermore, macroscopic residual stress can cause lattice distortion and reduce the crystal plane spacing [18,19]. In this case, the diffraction peak will also shift slightly towards the higher diffraction angles.

Moreover, the diffraction peaks of all synthesized catalysts exhibit different levels of splitting at 2θ = 32.25°, 46.24°, and 57.49°. This is due to the efficient synthesis of the mixed Ni-Fe crystalline phase. The anisotropy of the Ni-Fe crystal structure could increase the local oxygen vacancy concentration on the perovskite surface [20]. The increase in the number of oxygen vacancies facilitates the migration of lattice oxygen and enhances the catalytic activity [21,22,23,24].

3.2. SEM Analysis

SEM was utilized to examine the surface characteristics of each sample (Figure 2). The results show that all catalyst samples possess a homogeneous porous structure. Small particles are uniformly distributed on the surface of the porous skeleton formed by the large particles. The synergistic effect of Ni-Fe alloy is beneficial for the uniform distribution of active metals in perovskite structures [25]. Meanwhile, the appropriate amounts of nickel doping can effectively reduce particle size. As shown in Figure 2c, among all the synthesized catalysts, NI6 has a significantly smaller particle size. This indicates that NI6 has more reactive sites, which improve the ability of oxygen adsorption on the surface and enhance catalytic performance [26,27].

3.3. Nitrogen Adsorption–Desorption Analysis

Nitrogen adsorption–desorption experiments were conducted to analyze the pore structure and SSA of each sample. The pore size distribution of the adsorption isotherms was calculated using the Barrett–Joyner–Halenda (BJH) method. As shown in Figure 3, the synthesized perovskite catalysts exhibit hysteresis loops with increasing relative pressure due to the capillary cohesion effect. According to the IUPAC classification, all synthesized perovskite isotherms were classified as type IV, characterized as a mesoporous material [28,29]. Meanwhile, the hysteresis loop still maintains a large adsorption capacity at relative pressures greater than 0.6. According to the Brunauer–Deming–Deming-Teller (BDDT) classification [30], all synthesized perovskite isotherms were classified as type H3. At a relative pressure of 0.95, the isotherm of all synthesized catalysts still did not show adsorption saturation. This was likely due to the irregular pore structure created by the buildup of lamellar particles such as flat slits and fissures. The SEM images demonstrate the lamellar particle stacking structure. The pore size distribution curves in Figure 3 revealed that all catalysts had a concentrated pore size distribution [31]. The majority of the pore sizes were distributed in the range of 2–5 nm. In summary, the synthesized catalysts were mesoporous materials with a large number of mesoporous structures.

As shown in

Table 2. Characterization of LaNi_xFe_1−xO₃ Catalysts: SSA, Total Pore Volume, and Average Pore Diameter.

Samples	Specific Surface Area/m2 g−1	Total Pore Volume/cm3 g−1	Average Pore Diameter/nm
NI2	22.84	0.0915	2.454
NI4	14.84	0.0955	2.60
NI6	14.99	0.0928	2.45
NI8	22.58	0.0794	2.276

, all catalyst samples had SSA greater than 14 m²/g. As the nickel doping decreases from NI8 to NI4, the SSA decreases, the average pore size increases, and the pore volume increases. NI4 has the smallest SSA (14.84 m²/g), the largest average pore diameter (2.6 nm), and the largest pore volume (0.0955 cm³/g). Lattice distortion and defects caused by nickel doping were important reasons factors contributing to variations in SSA, average pore size, and pore volume. The first ionization energy of nickel (737.1 KJ/mol) was lower than that of iron (762.5 KJ/mol). This means that Ni-O covalent bonds were easier to form than Fe-O covalent bonds. After doping with nickel, some of the generated Ni-O covalent bonds replace Fe-O, causing lattice distortion. Thus, the catalyst particle SSA, average pore size, and pore volume were changed. Moreover, compared to the NI4 pore volume (0.0955 cm³/g), the NI8 pore volume (0.0794 cm³/g) dropped significantly by 16.86%. The high nickel content leads to agglomerative sintering of the perovskite phase [32] and collapse of the support pores on Ni³⁺.

Overall, nickel doping had a significant impact on the SSA and pore parameters of the catalyst particles. A moderate amount of nickel doping did not lead to extensive agglomerative sintering of the catalyst particles. In contrast, lattice distortion increased the strength of the basic sites and produced more oxygen vacancies, resulting in a marked increase in catalyst activity [25,33,34,35].

3.4. Thermal Analysis and Catalytic Activity

Figure 4 illustrates the TG-DTG curves for coal samples with and without a 5% mass fraction of perovskite catalyst.

Table 3. TG Characteristic Parameters of JF Coal Combustion with and without 5% LaNi_xFe_1-xO₃ Catalysts.

Samples	Ti/°C	Tf/°C	vp/(%/min)	Tp/°C	αo/%	va/(%/min)
JF Coal	524.37	720.12	5.37	628.81	32.52	3.84
JF Coal + NI2	519	695.17	5.54	611.17	31.46	4.32
JF Coal + NI4	515.95	690.14	5.38	616.86	34.17	4.29
JF Coal + NI6	511.05	694.65	5.52	602.55	28.91	4.52
JF Coal + NI8	511.2	710.32	5.41	617.64	27.64	4.38

summarizes the characteristic parameters of JF coal combustion obtained from the TG, including ignition temperature (T_i), final combustion temperature (T_f), maximum combustion rate temperature (T_p), mass fraction of residue (α_o), maximum burning rate (v_p), and average burning rate (v_a). The v_a is calculated using the following equation:

$$v_a=\beta \times \frac{{\alpha }_i-{\alpha }_f}{T_f-T_i}$$

(11)

Here, $\beta$ refers to the heating rate, which is set at 15 K/min, ${\alpha }_i$ refers to the percentage of the remaining sample corresponding to the ignition temperature point, and ${\alpha }_f$ refers to the percentage of the remaining sample corresponding to the final combustion temperature point.

The addition of the synthesized catalyst has been found to significantly optimize the JF coal combustion process [36,37,38]. After adding the catalyst, the maximum burning rate peaks of DTG curves were shifted to lower temperatures. As shown in Figure 4, the addition of NI6 showed the lowest T_p value (602.65 °C), which was 26.2 °C lower than that of JF coal (628.81 °C). Additionally, the addition of NI6 showed the highest v_a value (4.52%/min), representing a 17.7% increase compared to JF coal. Furthermore, the data in Table 3 indicates that the addition of NI6 has the lowest T_i value which is 13.32 °C lower than that of JF coal. Catalytic performance enhancement can be attributed to the synergistic effect of Ni and Fe present in the catalyst particles. The substitution of the metal in the B-site of the perovskite catalyst resulted in a reduction in the bond energy of the B-O lattice bond [39]. This led to the release of lattice oxygen and the generation of more oxygen vacancies in the perovskite, which ultimately enhanced the rate of coal combustion.

Moreover, the XRD analysis, as depicted in Figure 2, reveals that the diffraction peak intensity of NI6 was the weakest among all the synthesized catalysts, indicating that NI6 has the smallest particle size. It was confirmed by the calculation of Xieler’s formula that the average particle size of NI6 was the smallest among the synthesized catalysts, which is 9.9 nm. Generally, smaller particle sizes and larger SSA were more favorable for catalytic combustion. As NI6 showed the best combustion-promoting effect, it is considered that the influence of particle size on v_a was more significant than the influence of SSA.

In summary, adding synthetic catalysts has been shown to enhance the combustion of JF coal. By adjusting the amount of nickel doping, the synergistic action of Ni and Fe, lattice bond energy, and particle size can be modified, leading to improved combustion efficiency. Of all the synthesized catalysts, NI6 was found to be the most efficient catalyst for catalyzing JF coal combustion, likely due to its small particle size and unique combination of Ni and Fe.

4. Thermal Analysis Kinetics

The interval selected for the TG curve ranges from the ignition temperature point to the maximum combustion rate point. The combustion E_a of JF coal was calculated using the CR and the Doyle methods as shown in

Table 4. Activation Energy for JF Coal Combustion with and without 5% LaNi_xFe_1−xO₃ Catalysts.

Samples	Coats–Redfern’s Method			Doyle’s Method			N	Ea,m/kJ mol−1
	Ea/kJ mol−1	A/s−1	R2	Ea/kJ mol−1	A/s−1	R2
JF Coal	125.44	6.36 × 107	0.9979	130.49	3.82 × 108	0.9984	2	127.96
NI2	82.5	1.63 × 105	0.9874	90.07	1.44 × 106	0.9900	1	86.28
NI4	72.33	3.45 × 104	0.9794	80.43	3.84 × 105	0.9843	1	76.38
NI6	75.06	4.95 × 104	0.9870	83.08	5.22 × 105	0.9899	1	79.07
NI8	79.8	1.08 × 105	0.9899	87.53	1.01 × 106	0.9920	1	83.66

. Both the CR and the Doyle methods fit the TG curve well. Among all combustion samples, the coefficient of determination (R²) of the CR method was greater than 0.9794, while the R² of the Doyle method was greater than 0.9843. The research of other scholars has also proven that the CR and the Doyle methods were effective in fitting the TG curve of combustion [40,41].

Compared to the group without the addition of a catalyst, the E_a required for JF coal combustion was significantly reduced after the addition of a 5% mass fraction of synthetic catalyst. This was attributed to a large amount of mobile lattice oxygen in perovskite catalysts, which facilitates the activation of C-C and C-H bonds [42,43]. NI4 catalyst has the most obvious effect in reducing E_a. As the CR method calculation shows, the E_a after adding NI4 was 72.33 kJ/mol, a decrease of 42.34% compared to the E_a without a catalyst (125.44 kJ/mol). The Doyle method also shows that the E_a with the addition of NI4 (80.43 kJ/mol) was 38.36% lower than that without the catalyst (130.49 kJ/mol). Ni has a higher electronegativity (1.88) than Fe (1.8), making it weaker in combination with oxygen. Further, the doping of nickel facilitates the migration of lattice oxygen. Thus, the doping of Ni increases the oxygen mobility of the catalyst, activated the C-C bond, and reduces the E_a required for combustion. Other researchers’ studies have confirmed that during catalytic methane conversion, Ni exhibits a strong covalent nature on the catalyst, which enhances its catalytic performance. At the same time, appropriate Fe inhibited the thermal agglomeration of Ni particles, which was conducive to improving the catalytic performance [44,45,46,47].

5. Conclusions

The LaNi_xFe_1−xO₃ catalyst synthesized displays a distinct perovskite structure and performs well in catalyzing the combustion of JF coal. The difference in nickel doping significantly affects the lattice distortion and Ni-Fe alloy interactions. These had a significant impact on the catalysts’ surface structure and led to an improved catalytic performance. Due to its smallest crystal particles and excellent chemical properties of activating C-C bonds, NI6 shows good performance in catalyzing JF coal combustion. The excellent catalytic combustion performance of the NI6 catalyst offers a feasible option for the clean and efficient utilization of coal resources.

6. Prospects

This article utilized a single catalyst mass fraction of 5% and investigated the catalytic mechanism at this specific mass fraction. It is evident that varying the catalyst mass fraction can have a certain impact on the performance of catalytic combustion. In future studies, the research can be extended by varying the catalyst mass fraction to explore its effects on catalytic combustion.

Moreover, this study revealed the significant catalytic combustion effect of the LaNi_xFe_1−xO₃ catalyst on JF coal. However, there are significant differences in the physicochemical properties of coal from different sources, which poses greater challenges to the universality of catalysts. Therefore, in our subsequent studies, we will collect more types of inferior anthracite coal and conduct catalytic combustion experiments using perovskite catalysts of this kind. This will allow for further research to explore whether other coal types exhibit the same exceptional catalytic combustion performance.