Cu-Based Praseodymium-Modified γ-Al₂O₃ Oxygen Carrier for Chemical Looping Combustion Process Optimization

Abstract

Chemical looping combustion (CLC) emerges as a cost-effective CO₂ capture technology, demonstrating high competitiveness for both industrial and energy applications. This study explores the synthesis of a Cu-based, praseodymium (Pr)-modified gamma-alumina-supported (20CuPA) oxygen carrier (OC) through the wet impregnation method and investigates its performance in CLC. The characteristics of the synthesized OC were investigated using field emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, temperature-programmed reduction analysis, and X-ray diffraction analysis. The CLC of methane gas was performed in a thermogravimetric analyzer (TA-Q50). The oxygen transport capacity (OTC) of the 20CuPA-based OC was investigated for 10 redox cycles. The impact of temperature and time as process variables in determining the OTC of OCs was studied. The TGA results indicated that the most important factor influencing the optimization of the OTC of OCs was time. In comparison to time, temperature had less of an impact on the OTC of 20CuPA-OC. The maximum OTC of 20CuPA-OC, which was 0.0546 mg of O₂/mg of OC, was reached using optimized process variables, including a temperature of 800 °C and a time of 3 min.

1. Introduction

Climate change is largely blamed on the emission of greenhouse gases (GHGs). GHGs act as heat traps in the atmosphere, contributing effectively to global temperature rise. Climate behaviors are changing all over the world because of global environment transformation, which is one of the negative consequences of the phenomenon. When fossil fuels are combusted, CO₂ is released into the atmosphere, and this is the most considerable factor contributing to global warming. Chemical looping (CL) is a favorable technology among the existing CO₂ capture techniques because it has the inherent ability to separate CO₂ from the surrounding environment [1,2]. Chemical looping technology is divided into various sub-technologies, including chemical looping reforming (CLR), chemical looping hydrogen generation (CLHG), chemical looping combustion (CLC), and chemical looping gasification (CLG). All of these processes rely entirely on the oxygen supply (air or H₂O) and output (H₂, syngas, and CO₂) [3]. Because of in situ CO₂ capture, CLC has become an emerging application for oxyfuel combustion [4]. In the CLC process, the fuel and air are kept separate by using two separate but interconnected reactors that do not mix. The reactor in which air is injected is referred to as an air reactor, while the reactor in which fuel is introduced is known as a fuel reactor. The oxygen required for oxidation is transported to the fuel by a metal oxide known as an oxygen carrier (OC). The OC serves as a transporter for oxygen that is circulated between the air and the fuel reactors. The ability of an OC to transfer maximum oxygen is known as oxygen transport capacity (OTC). The escape gas from the fuel reactor includes CO₂ and H₂O vapors only and inherent CO₂ can be separated after condensing H₂O [5]. Figure 1 depicts the basic operating concept of the CLC. Following the fuel oxidation process, the reduced oxygen carrier is reoxidized with air to generate thermal energy for power production. For instance, combustion of gaseous fuels such as CH₄ with metal oxide would require the two reactions Equations (1) and (2), each of which would accomplish a redox cycle [6].

Reduction: 4/(x − y) MO_x + CH₄ → 4/(x − y) MO_y + CO₂ + 2H₂O

(1)

Oxidation: 2/(x − y) MO_y + O₂ → 2/(x − y) MO_x + Heat

(2)

OC particle development is essential in all CLC operations. OCs that can contain and transfer large portions of gaseous O₂ while being averse to depletion and physical decay are suitable. Transition metals such as Ni, Co, Fe, Cu, and Mn play an important role as an active site in the OC that carries the O₂ from air to the fuel reactor [7,8,9]. The OTC of OCs over several redox cycles has a significant impact on the overall performance of the CLC process. Among all metals, Ni and Cu have the highest OTC. However, Ni-based OCs are the best performers in the chemical looping reforming of methane compared to their use in CLC application [10]. This research could benefit greatly from the employment of Cu-based OCs, which have a number of notable characteristics. CuO is inexpensive, widespread, and highly reactive, and it has a large OTC of 20 wt% [11]. In the presence of CuO, CH₄ can be fully transformed into CO₂ and H₂O [12]. CuO is often supported by support materials to enhance reaction efficiency, improve structural properties, and resist attrition. In the published studies, Al₂O₃ has been utilized extensively for this aim [13,14]. On the other hand, Diego et al. [15] investigated the influence of various variables on the agglomeration process of CuO/Al₂O₃. They discovered that the agglomeration of CuO coated onto γ-Al₂O₃ is influenced by the calcination temperature and the CuO contents. The calcination temperature was critical in the agglomeration of particles with a CuO concentration of 10–20 wt%. Calcined particles at temperatures below 850 °C did not aggregate. The efficiency of a CuO-OC implanted onto γ-Al₂O₃ with a CuO concentration of 14% synthesized at 850 °C was investigated by de Diego et al. [13]. No agglomeration issues were found with the OC that had been prepared. The XRD profiles of the fresh OC contained CuO, γ-Al₂O₃, and CuAl₂O₄. The high contact between CuO and γ-Al₂O₃ in the impregnated CuO/γ-Al₂O₃ particles, with CuO levels varying from 15 to 26 wt%, was attributable to the creation of CuAl₂O₄ [15]. The activity of all samples lowered with an increase in redox cycles. This lowering was attributed to the production of a copper aluminate during CuAl₂O₄ oxidation, which resulted in the depletion of certain free CuO as well as plenty of OC inactivation. At high temperatures, CuAl₂O_4, on the other hand, can be converted to Cu and CuAlO₂, supplying O₂ for the CLC operation. The decrease in the OC’s activity is due to the difficulty of re-oxidizing CuAlO₂ from its reduced state. As a result, not all of the Cu in subsequent redox cycles will be present for combustion. This is widely regarded as a significant concern when dealing with CuO/Al₂O₃ OC.

Cabello et al. [16] investigated the endurance of a commercialized CuO-based OC loaded onto γ-Al₂O₃ (Cu14-Al Commercial) in a nonstop CLC unit operating at temperatures ranging from 800 to 900 °C for 125 h of methane combustion. Additionally, they reported that the CuO contents were deactivated by 3.4 wt% due to creation of CuAl₂O₄. Gayán et al. [17] investigated the usage of several Cu-based OCs in the chemical looping with the oxygen uncoupling (CLOU) method in order to prevent the creation of CuAl₂O₄. This research discovered that using MgAl₂O₄ as a support prevents the creation of CuAl₂O₄.

Ryu et al. [18] studied the influence of operating temperature on the reactivity of the different types of OCs. They found that at higher temperatures (>900 °C), the reactivity of OC decreases due to agglomeration and sintering effects. However, the performance of Cu-based OC at the higher temperatures of 800–900 °C was investigated. The results showed that the use of Cu-based OC at the temperatures of 800–900 °C is feasible. However, the lifetime of the OC was decreased from 2700 to 1100 h. The temperature of the reaction stands out as the most crucial factor impacting the efficiency of fuel utilization in CLC. Molecular insights have revealed that raising the reaction temperature is particularly helpful in maximizing the use of LZ coal when it interacts with CuFe₂O₄, which improves the effective utilization of LZ coal [19]. Another interesting finding is that the maximal rate of oxygen production increases as the operating temperature rises. The prediction of CuO breakdown is made possible by the correlation between this occurrence and the length of time the oxygen carrier is exposed to N₂ [11].

Moreover, it has been identified that prolonging the residence time of the oxygen carrier in the fuel reactor enhances fuel conversion [20]. Apart from the effects of temperature and time, the effect of pressure on the rate of reaction of redox cycles was examined by García-Labiano et al. [21]. The study reported that an increase in total pressure adversely affects the reaction rates of all oxygen carriers. Considering these findings, it can be inferred that time and temperature emerge as the most critical factors influencing the responsiveness and performance of oxygen carriers during the CLC process. It is worth noting that prior research has not thoroughly investigated the impact of process variables like temperature and time on the oxygen transport capacity of oxygen carriers employing response surface methodology (RSM). This emphasizes the originality of the current study.

In the present study, Cu-based γ-Al₂O₃-supported praseodymium-modified OC was synthesized using the wet impregnation method [22]. The support γ-Al₂O₃ was modified with praseodymium oxide in order to decrease the possibility for the formation of CuAl₂O₄. The aim of these findings is to determine the optimal working parameters that will maximize the oxygen transport capacity of OC while minimizing Cu content loss. As a result, optimization was carried out using the design of experiments (DOE) in conjunction with the usual Central Composite Design (CCD).

2. Experimental Section

2.1. Materials

Cu(NO₃)₂.3H₂O (Merck, Boston, MA, USA, CAS No. 10031-43-3, purity ≥ 99.5%) and Pr(NO₃)₂.6H₂O (Sigma-Aldrich, Saint Louis, MO, USA, CAS No. 15878-77-0, purity 99.9%) nitrates were employed in the preparation of OCs. In addition to this, γ-Al₂O₃ (Merck, CAS No. 1344-28-1, purity 98%) was used as an OC support material.

2.2. Synthesis of Oxygen Carrier

According to Quddus et al. [23], the wet impregnation approach was used to prepare the Cu-Pr/γ-Al₂O₃ OC. The elemental composition of synthesized Cu-Pr/γ-Al₂O₃-based OC is shown in

Table 1. The compositions of metals in 20CuPA-based OCs.

Oxygen Carriers	Cu-Contents (wt%)		Pr-Contents (wt%)		γAl2O3 (wt%)
	Theoretical	Actual	Theoretical	Actual	Theoretical	Actual
20CuPA-fresh	20	19.9	10	9.8	70	70.2
20CuPA-used	20	21.6	10	8.24	70	70.1

. For the intent of developing an OC, the following pathways were performed:

(a)

Pre-impregnation with the addition of Pr

• Pr was dissolved in deionized water to obtain a precursor solution.
• A Pr precursor solution was poured drop-by-drop to the γ-Al₂O₃ particles under continuous mixing in order to accomplish a deposition of 10 wt% Pr.
• At 100 °C for 48 h, the solution was dehydrated before being ground and then calcined in the muffle furnace for 4 h at 450 °C.

(b)

Impregnation with Cu addition in Step 2

• Cu was dissolved in deionized water to acquire a precursor solution.
• A Cu precursor solution was poured drop-by-drop to the Pr/γ-Al₂O₃ particles under continuous mixing in order to accomplish a deposition of 20 wt% Cu.
• The solution was dried for 48 h at 100 °C before being pulverized and calcined for 4 h at 450 °C in the muffle furnace. This yields an OC containing 20 wt% Cu, 10 wt% Pr, and the remainder γ-Al₂O₃, which is referred to as 20CuPA.

2.3. Characterization

The surface structures of both the fresh (calcined) and the previously cycled (after 10 redox cycles) OCs underwent examination through field emission scanning electron microscopy (FESEM) using the Zeiss (Oberkochen, Germany) Supra 55 VP model. Additionally, the elemental composition of the OCs was investigated through energy-dispersive X-ray spectroscopy (EDX). Sample preparation involved applying OC particles onto a copper stub, with a 2 min gold layer coating for enhanced analysis. The crystalline phases were scrutinized through X-ray diffraction (XRD) analysis using CuKα radiation with a Bruker D8 Advance instrument, operating at 40 kV voltage and 40 mA current. The scan spanned from 30 to 80°, with a precise step size of 1° per min. Thermal conductivity detector (TCD)-equipped TPDRO100 equipment was used to perform temperature-programmed reduction (TPR) analysis. About 0.10 g of the material was added to a reactor that was housed inside of a furnace throughout this procedure. Nitrogen gas was used to degas the material for 60 min at 200 °C. The sample was then processed for one hour at 900 °C before the gas flow was changed to 5% H₂/N₂ at a rate of 30 mL/min with a heating rate of 10 °C/min.

2.4. CLC Experiments

Performance analysis of synthesized OCs was conducted using Thermogravimetric Analysis (TGA-TA model Q50). A total of 15 mg of the OC was weighed out and deposited in a platinum pan. Through the use of a hang-down wire, the platinum pan was suspended in the TGA furnace. The TGA furnace was sealed and heated at a heating rate of 50 °C/min to a desired temperature (768–981 °C). The sample was heated in the presence of nitrogen gas at a flow rate of 20 mL/min during the procedure. The temperature within the furnace was maintained at a range of 768–981 °C throughout the process. After that, a steady flow of methane gas (5% CH₄/N₂) with an 80 mL/min flowrate was maintained at the same temperature range (768–981 °C) for 1–3 min. Oxidation was performed with air at 768–981 °C for 10 min at a flow rate of 80 mL/min. Nitrogen gas was purged between the methane gas and the air for 3 min to prevent the two gases from mixing together. For the purpose of analyzing the CLC process parameters, a total of ten different redox cycles were carried out. Figure 2 illustrates a diagrammatic representation of the CLC process with the use of TGA.

The oxygen transport capacity can be determined by using the formula R_o = (m_o − m_r)/m_o, where “m_o” refers to the mass of OC when it has reached its maximum level of oxidation and “m_r” refers to the mass of OC when it has reached its maximum level of reduction in the redox cycle. R_o refers to the maximum quantity of oxygen that can be supplied from an air reactor to a fuel reactor for a certain mass flow of recirculating OC particles. Using TGA, the weight changes in metal-based OCs that depend on temperature can be used to figure out the R_o.

2.5. Design of Experiments and Statistical Analysis

In order to characterize methane gas using CLC, an experiment design was carried out using a statistical method and RSM via Central Composite Design (CCD) and the Design-Expert Version 12^® software. RSM is a well-known technique for performing multiple test analysis and then using ANOVA analysis to analyze the results. Determining whether the individual or combined effects of process factors have a bigger or smaller effect on one or more answers was made easier with the use of this analysis. Subsequently, a statistical correlation between the variables and responses was established using a polynomial model equation, as shown in Equation (3):

$$y={\mathsf{\beta }}_0+{\mathsf{\beta }}_1{x}_1+{\mathsf{\beta }}_2{x}_2+{\mathsf{\beta }}_{12}{x}_1{x}_2+{\mathsf{\beta }}_1{x}_1^2+{\mathsf{\beta }}_2{x}_2^2$$

(3)

The expected response is represented by y in this case, the intercept is β₀, the linear effects are β₁x₁ and β₂x₂, the interaction effect is β₁₂x₁x₂, and the quadratic effects are β₁x₁₂ and β₂x₂₂. Here, time and temperature are represented by the variables x₁ and x₂, respectively [24]. It is possible to determine the link between input and output variables by using this methodology. The resulting surface aids in extracting desired information with a reduced number of experiments [25]. In the current investigation, two operational variables, namely time (A) and temperature (B), were chosen to examine their impacts on the response variable OTC. The time varied within the range of 1–3 min, while the temperature was adjusted in the range of 768–981 °C. These ranges were determined based on previous research findings and experimental results [26,27,28,29,30,31,32,33]. The ranges, characteristics, factors, and levels for temperature and time are listed in

Table 2. Range of the operational parameters used in the experiment array design.

Code	Factor	−α	−1	0	+1	+α
A	Time, min	0.58	1	2	3	3.41
B	Temperature, °C	768.93	800	875	950	981.06

.

The process is found to have quadratic connections through the use of Central Composite Design (CCD). Thirteen experimental runs were produced using CCD, and

Table 3. Experimental design for actual and predicted results.

Run	Process Parameters		Response
	Time (A), min	Temperature (B), °C	Actual	Predicted
1	2	875	0.0540	0.0537
2	0.58	875	0.0360	0.0368
3	3.41	875	0.0523	0.0518
4	2	875	0.0539	0.0537
5	3	950	0.0518	0.0525
6	2	768.93	0.0543	0.0522
7	2	875	0.0535	0.0537
8	1	950	0.0390	0.0388
9	2	981.06	0.0490	0.0484
10	2	875	0.0530	0.0537
11	2	875	0.0543	0.0537
12	3	800	0.0546	0.0542
13	1	800	0.0480	0.0467

shows the results for the two process variables as well as the actual predicted OTC (reaction). ANOVA analysis was used to determine whether process variables had a greater or lesser impact on the answer. Three different tests were performed to evaluate the significance and validity of the designed model: (a) F and P values of process variables or the perturbation graph; (b) adjusted and anticipated R² values; and (c) lack-of-fit values.

3. Results and Discussion

3.1. FESEM Analysis

Figure 3 comprehensively illustrates FESEM images capturing both the fresh and used states of Cu-based oxygen carriers. Noteworthy are the small granules and grains apparent on the particle surface in both instances. Remarkably, the surface morphology of the particles exhibits enduring stability even after undergoing 10 cycles. There is an absence of agglomeration or sintering phenomenon on the surface, highlighting the robustness of the structure. Furthermore, a thorough examination of the surface topography of 20CuPA oxygen carriers reveals minimal disparities between the fresh and used OCs, underscoring the stability of the structure throughout the oxygen releasing process. The EDX analysis confirmed nearly uniform Cu contents, with 19.9 wt% in the fresh sample (Figure 3a) and 21.6 wt% after ten successive redox cycles (Figure 3b). In summary, these results suggest that the explored material demonstrates remarkable stability in terms of both surface morphology and chemical composition throughout repeated cycles. This stability is crucial for its potential application in oxygen release processes. The absence of undesirable phenomena, such as agglomeration or changes in composition, enhances the material’s suitability for sustained and reliable performance. Further investigations or applications of the material in relevant processes may benefit from these observed characteristics.

3.2. TPR Analysis

The TPR analysis illustrated in Figure 4 was employed to examine the reduction characteristics of 20CuPA-fresh and 20CuPA-used OCs. The TPR profiles exhibited two distinct peaks, delineated at α = 270–300 °C and β = 390–410 °C. However, the peaks at α and β are associated with the reduction processes of well-dispersed CuO and bulk CuO, respectively. Specifically, the reduction pathways involve CuO → Cu [26,34]. Minimal shifts in the reduction peaks were noted between the fresh and used states of the oxygen carrier, suggesting subtle changes in its redox behavior (Figure 4). The reduction peaks for the 20CuPA-used OC shifted to higher temperature compared to the 20CuPA-fresh OC. This phenomenon could be attributed to the migration of initially dispersed Cu species toward bulk species during the course of utilization [26]. Notably, the peaks for the used oxygen carrier shifted to higher temperatures, indicating a possible migration of initially dispersed Cu species toward bulk species during utilization. These findings underscore the nuanced nature of the redox processes and provide avenues for further mechanistic studies, optimization of redox kinetics, and potential applications in practical settings.

3.3. XRD Analysis

For crystal structure determination, X-ray diffraction (XRD) analysis was conducted. The XRD results for both the fresh and used 20CuPA oxygen carriers (OCs) are presented in Figure 5. Notably, diffraction peaks corresponding to CuO were identified at 2θ angles of 32, 35, 39, 46, 49, 53, 58, 61, 66, and 75°, as indicated in the data [26]. The peaks at a 2θ angle of 37° corresponds to CuAl₂O₄ phase [34]. However, a small peak associated with CuAl₂O₄ was detected in both the fresh and used 20CuPA OCs. The peaks in 20CuPA-fresh and 20CuPA-used OCs show negligible variation, underscoring the stability of the OC even after undergoing 10 reduction–oxidation cycles. The data obtained from the TPR analysis distinctly contributes to the understanding and insights derived from this study, adding a significant layer of information to our findings. The diminutive peak observed in the XRD results corresponding to CuAl₂O₄ suggests a limited formation of the CuAl₂O₄ compound within the OCs. This scant presence could potentially account for its non-detection in the TPR results. The correlation between the small XRD peak and the absence in the TPR findings implies that the formation of the CuAl₂O₄ compound within the OCs may be insufficient to manifest prominently in the reduction behavior as captured by the TPR analysis.

3.4. CLC Cyclic Test

Figure 6 presents the mass variations observed in the 20CuPA OC over ten successive oxidation/reduction cycles, utilizing a 5% (Vol) methane environment. As depicted in Figure 6, there is identical reactivity observed in each consecutive redox cycle. This phenomenon could be elucidated by the consistent distribution of Cu contents within the OC particles throughout consecutive cycles. The OTC of the fresh OC and after 10 consecutive redox cycles was 0.054 mg of O₂/mg of OC. With evident EDX results, the availability of oxygen for release to the fuel during the combustion process is nearly identical for both fresh and used OCs. The OTC and reactivity of 20CuPA OC was higher and stable even after 10 reduction–oxidation cycles, compared to previously reported Cu-based OCs [11,17,35,36,37].

3.5. Parametric and Optimization Analysis

Temperature, time, and the metal loading site all have a huge impact on an OC’s OTC. The highest Cu-metal loading was selected in compliance with the body of current research. Cu-based OC for the CLC process has been the subject of numerous studies, and the results have shown that agglomeration is a consistent occurrence for OCs with Cu levels higher than 20 wt% [15,30]. Based on previously published research, 20 weight percent was determined to be the ideal copper metal loading for the OC. As a result, an RSM-based 20CuPA-based OC was used to adjust the process variables, including temperature and time. Table 3 provides the experimental model together with the actual and projected values of oxygen transport capacity, which is the output of the chemical looping combustion process.

3.5.1. Regression Equation Development and Statistical Analysis

Regression analysis was used in the statistical analysis to look at how the process parameters—temperature and time—affected the outcome variable (OTC). Equation (4) represents the output of a coded quadratic equation that was created using the ANOVA results to describe the impact of independent parameters (process variables) on the dependent parameter (OTC).

$$OTC=0.0537+0.0053A-0.0024B-0.0016AB-0.0047A^2$$

(4)

where A = time and B = temperature.

Predictions regarding the OTC are made possible by the Equation (4) stated in terms of coded factors, given the levels provided for each constituent. In terms of design, factors with high levels are coded as +1 and those with low levels as −1. The coded equation can be used to determine the relative importance of the components by looking at the factor coefficients. ANOVA was used to assess the model’s and the variables’ significance with regard to over-the-counter medications, as

Table 4. ANOVA results for oxygen transport capacity of oxygen carrier.

Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	0.0004	5	0.0001	112.69	<0.0001	significant
A-Time	0.0002	1	0.0002	292.01	<0.0001
B-Temperature	0.0000	1	0.0000	60.33	0.0001
AB	9.61 × 10−6	1	9.6 × 10−6	12.46	0.0096
A2	0.0002	1	0.0002	197.72	<0.0001
B2	6.04 × 10−6	1	6.04 × 10−6	7.84	0.0265
Residual	5.4 × 10−6	7	7.71 × 10−7
Lack of Fit	4.38 × 10−6	3	1.46 × 10−6	5.78	0.0616	not significant
Pure Error	1.01 × 10−6	4	2.53 × 10−7
Cor Total	0.0004	12

R² = 0.9877; adjusted R² = 0.9790; predicted R² = 0.9255; adequate precision = 30.86.

illustrates.

The ANOVA findings showed that the experimental and predicted data for OTC matched exceptionally well. p-values, R², adjusted R², and F values were among the design criteria used to make sure the suggested model was valid and effective. The correctness of the anticipated model was confirmed by the p-values, which were less than 0.0001. When a model term’s p-value was less than 0.0500, it was deemed significant; if it was more than 0.0500, it was deemed non-significant. All model terms (A, B, AB, A², and B²) were determined to be meaningful across the entire procedure. The performance of the model was evaluated using the R² coefficient of determination, which shows the percentage of overall variation in the answer. For precision, a high R² value that is close to one is favored. With an R² of 0.9877 for this model, it can be said that only 1.33% of the experimental data are not explained by the model, and 98.77% of OTC changes are described by the process parameters. Although there may have been variances in the independent variables, the corrected R² values (0.9790) were remarkably close to R², indicating acceptable model fitting. The marginal difference also suggests practicality. Given that a signal-to-noise ratio of greater than four is ideal, the model’s sufficient precision value of 30.86 indicates that it can navigate the design space with effectiveness. The F-value of 5.78 for lack of fit and the p-value of 0.061 for lack of fit indicate that the lack of fit does not achieve the required significance level. The experimental and RSM-predicted OTC results due to the process parameters are illustrated in Figure 7.

Effect of Process Parameters on Response

The impact of process parameters on the linear term of oxygen transport capacity was examined through a perturbation graph, as depicted in Figure 8. Two curved lines were observed, corresponding to the two process parameters (time and temperature) influencing OTC. The curvature of these lines is directly proportional to their impact on OTC [38]. Consequently, it is evident that time exerts the most significant influence on OTC, as indicated by its higher curvature. The observation for the 20CuPA-based OC indicates that the majority of oxygen release and adsorption by the OC occurred within the initial minute, as illustrated in Figure 6.

Parametric Analysis of Oxygen Transport Capacity Using 3D Response Surface Plot

At different process settings, different OCs behave differently, which can result in an increase, decrease, or no change in OTC. As a result, temperature and time are the key process variables that have the biggest effects on the OTC of OCs in continuous redox cycles inside the CLC process. Regression equation frameworks are represented by response surface patterns, which help identify the ideal parameter values and comprehend how they interact to improve process effectiveness. Graphical illustrations of the regression equation are used to examine the relation between input and output variables. Two-dimensional (2D) counter plots and three-dimensional (3D) response surface plots are used. The 3D response surface plot (Figure 9) shows the combined effect of temperature and time on the OTC of OCs. Notably, the OTC of OCs gradually decreased from 0.048 to 0.039 mg of O₂/mg when the temperature was raised from 800 to 950 °C during a 1 min reduction reaction. On the other hand, a small increase in the reduction reaction time led to a significant rise in OTC. For example, the OTC increased significantly from 0.048 to 0.0546 mg of O₂/mg of OC at 800 °C with a time increase from 1 to 3 min. The observation suggests that the amount of OTC is mostly unaffected by a shift in reaction temperature. The 3D response surface analysis, like perturbation analysis, shows that time, as opposed to temperature, has the greatest impact on the OTC of Cu-based Pr-modified alumina OC among the two process parameters.

3.5.2. Optimization of Process Parameters

Numerical optimization, using a tool developed for experimental discoveries in the CLC process using TGA under particular operating circumstances, is crucial to maximizing the OTC. To validate the expected OTC at 800 °C with a 3 min reduction reaction, the experiment was carried out three times, as shown in

Table 5. Predicted and experimental results for the optimized process parameters.

Confirmation Runs	Time (min)	Temperature (°C)	OTC (mg of O2/mg of OC)		Percentage Error (%)
			Predicted	Experimental
Run 1	3	800	0.054	0.0541	0.18
Run 2	3	800	0.054	0.0546	1.11
Run 3	3	800	0.054	0.0551	2.03
Standard deviation	-	-	-	0.0004	-

. This validation made it possible to compare the real OTC directly to the predicted values from the first testing phase. Excellent agreement was shown between the predictions made by the model and the results of the confirmation tests, indicating the model’s dependability and efficiency. Three minutes and eight hundred degrees Celsius were found to be the ideal factors. This led to a predicted OTC of 0.054 mg of O₂/mg of OC. With an OTC standard deviation of 0.0004, the experimental and anticipated results showed a good degree of agreement.

3.6. Significance of Current Work

The significance of the 20CuPA-based OC is underscored by its robust stability, as evidenced in both crystal structure determination and temperature-programmed reduction analyses. These findings collectively highlight the stability and nuanced behavior of the 20CuPA-based OC, emphasizing its importance in advancing our understanding of oxygen carrier dynamics and its potential applicability in redox processes. A notable and crucial finding emerges from the data, revealing that a significant portion of both oxygen release and adsorption transpires within the initial minute of the process, as elucidated in Figure 6. This temporal emphasis on the first minute underscores the remarkable efficiency and rapidity of the oxygen exchange kinetics associated with the current OC. The prompt oxygen release and adsorption during this early stage suggests a highly responsive and effective oxygen transfer mechanism, which can be pivotal in applications where rapid and precise control of oxygen exchange is paramount. This characteristic not only speaks to the performance merits of the 20CuPA-based OC but also underscores its potential significance in scenarios demanding swift and efficient oxygen management, thereby accentuating its importance in current oxygen carrier research and applications.

4. Conclusions

The chemical looping combustion process was performed in a thermogravimetric analyzer using 5%CH₄/N₂ as a reducing gas and air as an oxidizing gas. The oxygen transport capacity of 20CuPA-OC was examined over 10 redox cycles in a CLC process. RSM was used to optimize and to investigate the parametric effects using CCD for the design of experiments. The OTC of 20CuPA-OC varied between 0.036 and 0.0546 mg of O₂/mg of OC as a result of varying operating conditions. Time was a more significant factor than temperature in determining OTC. A decrease in the OTC was examined when the temperature was increased from 800 °C to 950 °C. However, the OTC of 20CuPA-OC increased dramatically when the reduction process was prolonged from 1 min to 3 min. The highest OTC of 20CuPA-OC of 0.0546 mg of O₂/mg of OC was achieved at optimum process parameters such as a time of 3 min and a temperature of 800 °C. Applying the 20CuPA-OC in real-world settings resembling industrial processes could validate its performance under practical conditions. Testing the material’s efficiency in scenarios representing its intended applications will be crucial for assessing its real-world utility.