Graphene nanoplatelets promoted CoO-based catalyst for low temperature CO2 methanation reaction

Methanation of CO₂ is an important reaction for reducing CO₂ emissions in a power-to-gas system. Compared to cobalt supported on gamma-Al₂O₃, cobalt supported on graphene nanoplatelets (GNPs) showed significantly better performance for CO₂ methanation. Cobalt supported on GNPs was capable of 15% conversion of CO₂ to CH₄ at temperatures below 250°C, compared to 5% for cobalt supported on Al₂O₃. In situ thermogravimetric analysis (TGA) demonstrated that the Co/GNP catalyst was stable to 400°C. The maximum catalyst mass-specific CH₄ yield was obtained at a Co loading of 5_wt% on GNPs; however, high Co loading on GNPs deactivated the reactivity of the Co/GNP catalyst. Transmission electron microscopy (TEM) demonstrated that 5_wt% Co/GNPs had the smallest and most dispersed cobalt nanoparticles. Excessive loading of cobalt tended to form isolated large Co nanoparticles. X-ray photoelectron spectroscopy (XPS) and Raman spectrometry revealed that more CoO phases were maintained on the surface of 5_wt% Co/GNPs, indicating that the interaction between the Co and the GNPs had more of an impact on cobalt’s redox capacity than did particle size, which ultimately affected cobalt’s active phase during the CO₂ reduction process. Furthermore, Raman spectrometry demonstrated that Co loading led to an increase in graphene defects. Higher Co loading on GNPs resulted in fewer interfaces between Co and GNPs due to the agglomeration of Co nanoparticles.

1 Introduction

Researchers agree that global warming is mostly caused by CO₂ emissions from excessive use of fossil fuels (Johnsson et al., 2019). Over the decades, processes for CO₂ reduction have been extensively studied and tested but with little real progress. For example, CO₂ can be converted into other chemicals, such as CH₄, CH₃OH, and CH₃COOH, via various techniques such as thermal, electrochemical, photochemical, biochemical, and plasmatic techniques (Jimenez et al., 2011; Mateo et al., 2018; Ojelade and Zaman, 2021; Pham et al., 2022). Among these, the thermal catalytic methanation process, also known as the Sabatier reaction, has been considered the most competitive CO₂ reduction process for commercial application due to the high energy yield and conversion efficiency. In a power-to-gas system, CH₄ produced from CO₂ can be directly fed into the power plant for producing electricity, reducing the demand for natural gas (Bailera et al., 2017). Commercialization of the CO₂ methanation process benefits society not only through the reduction of CO₂ but also the replacement of fossil fuel by a renewable energy resource (Bacariza et al., 2020). However, the efficiency of the CO₂ methanation process is critically dependent on the activity of the catalyst.

The CO₂ conversion rate and CH₄ yield are limited by the thermodynamic equilibrium of CO₂ methanation at high temperatures; an ideal catalyst should be selective and function at relatively low temperatures (Kuśmierz, 2008; Wang et al., 2016). The transition metals Ru, Rh, Co, and Ni, supported on porous materials such as Al₂O₃, CeO₂, and TiO₂, have been reported to be active for CO₂ methanation (Frontera et al., 2017). The noble metal ruthenium- and rhenium-based catalysts have shown excellent activity and selectivity over a wide temperature range, but their high market price has stimulated the development of cobalt and nickel catalysts as replacements. Ni/CeO₂ has been shown to be comparable to the noble metal catalysts, but only at elevated temperatures, where it tends to be deactivated because of the agglomeration of Ni particles and coking on the catalyst’s surface (Vogt et al., 2018). In contrast, cobalt-based catalysts have demonstrated better reactivity at low temperatures (Ci et al., 2010; Liu et al., 2018; Parastaev et al., 2020; Tu et al., 2021). The active structure of cobalt-based catalysts has been determined to be the CoO phase (ten Have et al., 2022), (Zhao et al., 2020). However, this transition phase tends to be reduced to metallic Co by the reductive mixture of CO₂ and H₂, leading to studies on stabilizing the active phase for long-term reactivity (Zhong et al., 2019; Zhong et al., 2021a; Zhong et al., 2021b).

In order to maintain the stability of the catalytic CoO phase during the CO₂ methanation reaction, it is essential to tune the redox ability of Co. Conventionally, the redox ability of Co can be adjusted by changing particle size, interaction with the support, or with a second promoter (Wigzell and Jackson, 2017; Qi et al., 2020; Rahmati et al., 2020). As reported previously, the insertion of a graphene layer into a Co/ZnO system results in a more reductive surface in an oxidative environment. Graphene is also able to tune Co particles (He et al., 2013; Karimi et al., 2015; Cañón and Teplyakov, 2021). Inspired by those results, we used graphene nanoplatelets as supports for cobalt-based CO₂ methanation catalysts. Bulk and surface characterization methods were used to investigate the promotion mechanism of the GNP support. To the best of our knowledge, this is the first time that a carbonaceous material like GNP, has been used as a catalyst support for the thermal CO₂ reduction process.

2 Experimental methods

2.1 Materials and catalyst preparation

The Co-based catalysts were prepared by the incipient impregnation wetness method. For the Co/Al₂O₃ sample, Co(NO)₃·6H₂O (Alfa Aesar, CAS#10026-22-9) was dissolved in deionized water (DIW). Al₂O₃ (2 g) was impregnated into the cobalt nitrate solution, and the mixture was dried at 80°C in air. For the Co/GNP samples, the cobalt nitrate was dissolved in a mixture of DIW and ethanol (1:1, vol%) because of the hydrophobic nature of the GNP (Sigma-Aldrich, CAS#7782-42-5) surface. The solution was then applied to the GNPs based on the saturated water absorption of the support, and this was repeated three times. For the gamma Al₂O₃ support (Jiangxi, Pingxiang, Alibaba.com), the cobalt nitrate was dissolved in DIW and the solution was impregnated three times. After the impregnation step, the samples were dried in air at 80°C for around 12 h. After drying, the as-prepared sample was directly loaded into a fixed-bed reactor. Before starting the CO₂ methanation, in-situ reduction of the sample with 5% H₂ (by vol) at 400°C for 2 h was performed to anneal the Co precursor to the metallic Co. For characterizations, the samples were reduced in 5% H₂ (by vol) balanced with N₂ at 400°C for 2 h, and then collected for different measurements.

2.2 Material characterization

The Brunauer–Emmett–Teller (BET) surface area of the supports was obtained by the N₂ adsorption–desorption method using a BELSORP MAX II analyzer from Microtract MRB. The loading content of Co in each sample was determined with an Agilent 5110 inductively coupled plasma optical emission spectrometer (ICP-OES). X-ray diffraction patterns were obtained on a Bruker D8 Advance instrument (40 kV, 40 mA, Cu Kα radiation, and λ = 0.154 nm). X-ray photoelectron spectroscopy (XPS) and Raman spectroscopy were used for surface characterization. The XPS spectra of Co 2p were collected under ultra-high-vacuum (UHV) on a Kratos Axis Supra XPS system using the monochromatic Kα line of an aluminum X-ray source (1486.6 eV) with the analyzer set at a pass energy of 20 eV. The deconvolution of the Al 2p peak was completed with CasaXPS software. Raman spectroscopy was obtained under ambient conditions using a 632-nm laser. Scanning electron microscopy (SEM) images were acquired on a Thermo-Fisher Teneo FE-SEM. Transmission electron microscopy images were acquired with Thermo-Fisher Tecnai Osiris (200 kV) and Thermo-Fisher Tecnai Spirit (120 kV) EMs. Thermo-gravimetric analysis (TGA) was performed using a TG 209 F1 Libra instrument by Netzsch.

2.3 Catalytic activity evaluation

The reactivity of catalysts for CO₂ methanation was evaluated in a microscale fixed-bed flow reactor. The reactor consists of a 5-cm-long stainless steel tube with an inner diameter of 8 mm for the catalyst bed zone and a temperature control system. The catalyst sample was loaded as pellets with a size of 40–60 mesh. The catalyst bed zone was heated in a furnace with the reaction temperature measured by a K-type thermocouple running through the catalyst bed. For each test, 200 mg of sample pellets were loaded into the reactor and reduced with 10% (by vol) H₂ (2 ml/min H₂ + 8 ml/min N₂) at 400°C for 3 h. After the temperature had cooled to 50°C, the gas mixture was switched to 3 ml/min of CO₂, 4.5 ml/min of N₂, and 12 ml/min of H₂. For each reaction at a specific temperature, a dwell of 2 h was set, after which the outlet gas was analyzed on a gas chromatograph (SRI 83670) with a thermal conductivity detector (TCD). The CO₂ conversion (X_CO2), CO selectivity (S_CO), and CH₄ selectivity (S_CH4) rate were determined separately by Eqs 1–3:

${\mathit{X}}_{\mathit{C}\mathit{O}\mathbf{2}}=\frac{{\mathit{C}\mathit{O}}_{\mathbf{2},\mathit{i}\mathit{n}}-{\mathit{C}\mathit{O}}_{\mathbf{2},\mathit{o}\mathit{u}\mathit{t}}}{{\mathit{C}\mathit{O}}_{\mathbf{2},\mathit{i}\mathit{n}}},(1)$

${\mathit{S}}_{\mathit{C}\mathit{O}}=\frac{{\mathit{C}\mathit{O}}_{\mathit{o}\mathit{u}\mathit{t}}}{{\mathit{C}\mathit{O}}_{\mathbf{2},\mathit{i}\mathit{n}}-{\mathit{C}\mathit{O}}_{\mathbf{2},\mathit{o}\mathit{u}\mathit{t}}},(2)$

${\mathit{S}}_{\mathit{C}\mathit{H}\mathbf{4}}=\frac{{\mathit{C}\mathit{H}}_{\mathbf{4},\mathit{o}\mathit{u}\mathit{t}}}{{\mathit{C}\mathit{O}}_{\mathbf{2},\mathit{i}\mathit{n}}-{\mathit{C}\mathit{O}}_{\mathbf{2},\mathit{o}\mathit{u}\mathit{t}}},(3)$

where CO₂, _out/in, CH_{4 out}, and CO_out are the molar concentrations of the reactor inlet/outlet gas stream. For each gas, the molar concentration was determined by external calibration curves with standard gases. For correction of the total volume change from inlet to outlet due to the reaction, N₂ was used as an internal standard calibration gas. In order to compare the intrinsic activity of Co in each sample, we have calculated the Co mass-specific CH₄ formation rate by Eq. (4):

${\mathit{R}}_{\mathit{C}\mathit{H}\mathbf{4}}=\frac{{\mathit{X}}_{\mathit{C}\mathit{O}\mathbf{2}}\times S_{CH4}\times {\mathit{F}}_{\mathit{C}\mathit{O}\mathbf{2},\mathit{i}\mathit{n}}}{{\mathit{V}}_{\mathit{m}}\times {\mathit{C}\mathit{o}}_{\mathit{w}\mathit{t}}\%\times {\mathit{m}}_{\mathit{c}\mathit{a}\mathit{t}\mathit{a}\mathit{l}\mathit{y}\mathit{s}\mathit{t}}},(4)$

where V_m is the molar volume of ideal gas at standard conditions, which is 22.4 L/mol, while m_catalyst is the mass of the catalyst loaded for each test. Co% is the cobalt content in weight percentage, as defined by ICP-OES analysis.

3 Results and discussion

3.1 Catalytic reactivity

The reactivity of supported Co catalysts for the hydrogenation of CO₂ to methane is shown in Figure 1. For the same Co loading (5_wt%), Co supported on GNPs exhibited a much higher CO₂ conversion rate than on Al₂O₃. For example, only 5% CO₂ conversion is obtained with 5_wt% Co/Al₂O₃ at 235°C, while the conversion rate is 15% for 5_wt% Co/GNPs. Unexpectedly, the increased Co loading on GNPs did not equate to a comparable rise in CO₂ conversion. Much less CO₂ was converted by 10_wt% Co/GNPs than by 5_wt% Co/GNPs. Figure 1B also compares the Co mass-specific CH₄ production of four catalysts at kinetic-dominated temperatures to directly assess the intrinsic reactivity of Co in each sample. The Co mass-specific yield of CH₄ of 10_wt% Co/GNPs was lower than that of 5_wt% Co/Al₂O₃. The results clearly indicate that a catalyst with 5_wt% Co supported on GNPs was the most reactive, while the 10_wt% Co loaded on GNPs had the lowest reactivity. The difference in mass-specific reactivity can likely be attributed to the different active phases of Co in each sample. The characteristics of this Co phase are revealed in the following results and analysis.

FIGURE 1

FIGURE 1. CO₂ conversion of catalysts at different temperatures (A) and the mass-specific CH₄ formation rate of cobalt in each catalyst at 230°C (B). Reaction conditions: 1 bar, 19.5 ml/min total flow rate with reaction mixtures of 15_vol% of CO₂, 60_vol% of H₂, and 25_vol% of N₂.

3.2 Bulk and morphology properties

To investigate the intrinsic effects of GNPs on Co catalysis for CO₂ conversion, we tested commercial GNPs and compared them to porous Al₂O₃ supports with the same surface area (300 m²/g) as a reference. The BET surface area was determined, and results can be found in supporting information (Supplementary Table S1; Supplementary Figure S1). The porous Al₂O₃ material is commonly used as a support in commercial and industrial-scale operations for fabricating supported-metal catalysts because of its relatively low price and compatibility with different application conditions. Even though other reducible oxides, like CeO₂, ZrO₂, and ZnO, have been reported as promising supports for cobalt-based CO₂ methanation, the intrinsic reactivity of those oxides for CO₂ conversion complicates the determination of the specific influences of the cobalt–support interaction. In this study, the selected pure Al₂O₃ and GNPs are both inert in the CO₂ methanation reaction at the tested temperatures. The Co content in the tested catalysts was confirmed by IPC-OES, and all the catalysts had the designated Co content (Table 1). The small discrepancies between nominal content and content in synthesized samples were probably due to deviations occurring during synthesis.

TABLE 1

TABLE 1. ICP-OES quantification results of cobalt content in reduced catalyst samples.

SEM-EDX mapping results (Figure 2) demonstrate that the 5_wt% of Co applied is distributed uniformly onto both Al₂O₃ and GNP supports. Only a few regions in the map show a heavier Co deposit, indicating that most Co clusters were resistant to agglomeration during reduction at 400°C. TEM images (Figure 3) of Co/GNP samples show that increasing Co loading to 15_wt% leads to formation of large Co aggregates. Cobalt particles of about 1 nm are formed and are well dispersed in the 5_wt% Co/GNP sample, but their average size rose to 3.8 nm in the 10wt% Co/GNP sample. Large cobalt particles up to 30 nm were formed when Co content was increased to 15_wt%. Large particles typically have a relatively low surface area, which results in fewer sites for reaction. This may help explain why larger loading results in a lower metal-mass-specific yield of CH₄. Although the sample with 10_wt% loading had smaller cobalt particles than that with 15_wt% loading, which is believed to have a higher active surface area of Co, it exhibited lower CH₄ yield than the 15_wt% catalyst. The discrepancy between the Co surface area and reactivity may be explained by the finding, which is supported by numerous studies, that the catalytic reactivity of Co is dependent on its particle size. In those investigations, it was discovered that the size of Co affects its redox capacity and defines the active phase during reaction (Ci et al., 2010; Sadasivan et al., 2013; Torshizi et al., 2021).

FIGURE 2

FIGURE 2. Representative SEM-EDX mapping images of cobalt supported on GNPs (left) and Al₂O₃ (right) after reduction by H₂.

FIGURE 3

FIGURE 3. TEM images and cobalt particle size distribution of Co/GNP samples after reduction at 400°C by H₂.

Figure 4 shows the crystalline structure of Co and GNPs. A wide peak around 2θ = 36° is attributed to the CoO (220) crystalline phase (PDF#00-048-1719) in all Co/GNP samples. The Co₃O₄ phase (PDF#04-001-8014) was only detected in the 15_wt% Co/GNPs, while the metallic Co crystalline phase was found in both the 10_wt% Co/GNPs and 15_wt% Co/GNPs. Although all samples were reduced under the same conditions, they were oxidized during the ex situ measurement and transition due to exposure to air. The differences in the crystalline phase of Co in the three samples indicate that its redox ability might be different, suggesting some mechanistic aspects of the different Co active sites. This redox ability is dependent on Co particle size and interactions between Co and the GNP support (Sadasivan et al., 2013). It has been reported that smaller Co metal particles were oxidized more readily than bigger particles. According to TEM size analysis, the 5_wt% Co catalyst had the smallest particle size. Although it was oxidized under the same conditions, the XRD pattern showed no Co₃O₄ phase in this sample. In addition to particle size, the interaction between the Co and the support plays a key role in determining its redox activity. We hypothesized that the metal–support interaction plays an essential role in Co’s redox ability, eventually affecting the Co active phase for CO₂ methanation.

FIGURE 4

FIGURE 4. Full XRD patterns of GNP-based samples. Samples were first reduced with H₂ at 400°C and measured ex situ in air.

3.3 Surface properties

Structural analysis of Co catalysts has revealed that the size of Co particles was dominated by the Co loading content. The size of the Co particles has always been considered a key aspect in the reactivity of Co, but the variation in reactivity with particle size did not agree with the findings in our study. Co’s crystalline phase also varies with the loading content, demonstrating that Co’s active phase in Co/GNPs catalysts might be different. To further define the active phase of Co, XPS and Raman spectrometry, which are powerful surface-sensitive techniques, have been used for verifying the surface phase of catalysts. In Figure 5, two satellite peaks at 785.8eV and 789.8eV indicate the coexistence of CoO (referred to as Co²⁺) and Co₃O₄ (referred to as Co³⁺) phases, respectively; meanwhile, the peak of metallic Co (about 778 eV) was not observed (Khassin, 2001; Lahijani et al., 2015; Cañón and Teplyakov, 2021). The deconvolution of the Co 2p peak based on previous literature studies allowed calculation of the ratio of Co²⁺/Co³⁺ on the surface. As summarized in Table 2, the ratio of Co²⁺/Co³⁺ of the tested catalysts followed the trend of 5_wt%Co/GNPs > 5_wt%Co/Al₂O₃ > 15_wt%Co/GNPs >10_wt%Co/GNPs, which is consistent with the trend of their intrinsic Co activity (Figure 1B). This trend indicates that CoO is the preferred phase for CO₂ conversion, as reported. The different amounts of CoO formed on the catalyst’s surface were related to the redox ability of Co which is normally related to Co particle size and metal–support interactions (Torshizi et al., 2021; Díez-Ramírez et al., 2017; Parastaev et al., 2020). The GNP support was more conducive to the formation of the CoO phase for the reaction compared to the influence of particle size.

FIGURE 5

FIGURE 5. High-resolution XPS spectra of Co 2p for cobalt-based catalysts. All samples were reduced at 400°C with 5% H₂ in N₂ before measurement.

TABLE 2

TABLE 2. Ratio of different cobalt species and the graphene phase on the surface of the catalyst and support analyzed by XPS and Raman spectrometry, respectively.

Figure 6A shows the typical Raman spectra of GNPs in catalysts and as a support only. A strong G-band peak appears at about 1583 cm⁻¹ attributed to the E_2g mode, which is caused by stretching of the C-C bond in all carbon materials. A 2D band peak located around 2700 cm⁻¹ confirms the graphitic structure of GNPs. (Ci et al., 2010), (Luo et al., 2017) The relative low intensity of the 2D band together with a red shift location indicates that GNPs contain multiple graphene layers. Another peak at about 1350 cm⁻¹ is the signature of the D band caused by disorder in the graphene structure. It is known that doping with transition metals, Ni, Co or Pt, leads to extrinsic disorder in graphene structure with formation of covalent bonds between C-atoms (Krasheninnikov et al., 2009; Xin et al., 2016). The quantification of the relative ratio between the intensities of the D band and the G band (I_D/I_G) provides information on the degree of disorder in the graphene layers after Co loading (Cançado et al., 2011) (Table 2). The 5_wt% Co/GNPs catalyst has the highest I_D/I_G ratio at 0.17, while the support alone has the lowest I_D/I_G ratio at 0.10. However, loading more Co does not increase the disorder but results in less disorder. According to theoretical calculations (Krasheninnikov et al., 2009), the addition of a dopant to graphene shifts the Fermi-level of carbon, leading to the enhancement of conductivity and catalytic activity. This helps explain why the 5_wt% Co/GNP sample had the highest reactivity for CO₂ conversion. In this sample, it is also possible that more Co interacted with graphene, leading to a more stable electronic structure resisting the redox transformation of the CoO phase under reaction conditions. The agglomeration of Co clusters results in lower formation of interfaces or boundaries between graphene and Co.

FIGURE 6

FIGURE 6. Raman spectra of catalysts and pure GNPs; the range of carbon features is shown in (A), while the cobalt features are depicted in (B). The Co/GNP samples were reduced before measurement, while the pure GNPs were measured directly without any pretreatment.

The Raman spectra of the Co phase are shown in Figure 6B. Five intense peaks located at 191, 470, 515, 608, and 675 cm⁻¹ were found in all the Co/GNP samples. Based on previous results, a CoO octahedron-shaped sample registers three Raman peaks around 515 cm⁻¹, 555 cm⁻¹, and 680 cm⁻¹ (Ravindra et al., 2014), while Co₃O₄ with a spinel structure has five Raman-active modes: A1g, Eg, and three T2g modes located around 194 cm⁻¹, 479 cm⁻¹, 515 cm⁻¹, 617 cm⁻¹, and 686 cm⁻¹, respectively. Among the five modes, the A1g mode at 194cm-1 is the most intense (Hadjiev et al., 1988). For the stretching of Co-O, the nanoscale size of the sample and distortions of the lattice due to defects leads to the shift of position and change in intensity (Li et al., 2016). These characteristic peaks were observed in all samples with slight shifts, indicating the co-existence of CoO and Co₃O₄ oxide on the sample surface. This agrees with the XPS results, which always depict a face with a mixture of Co³⁺ and Co²⁺. It should be noted that the applied laser could also cause CoO oxidation, resulting in more Co₃O₄ phase, which complicates the discussion [44]. However, the relative ratio of Co₃O₄ in the sample can be derived indirectly from the intensity of the peak at 191cm-1 that corresponds to the A1g mode of the Co₃O₄ phase. The spectra demonstrate that 5_wt% Co/GNP has the weakest peak at 191cm-1 after normalization, indicating that this catalyst has the highest CoO ratio, but the smallest amount of the Co₃O₄ phase. This finding is consistent with the XPS results, highlighting the CoO phase’s established reactivity for CO₂ methanation.

3.4 Stability

The stability of carbon materials is always a concern for application in thermal CO₂ conversion reactions due to the reverse Boudouard reaction of CO₂ + C – 2CO (Lahijani et al., 2015). This reaction, also known as the CO₂ gasification reaction, is thermodynamically supported at temperatures above 350°C, and at ambient pressure. In the case of a GNP-supported catalytic system for CO₂ methanation, if the GNPs interact with the CO₂ reactants, the support lifetime will be limited. Herein, we have used CO₂-TGA to determine the stability of a synthesized GNP-supported Co catalyst. The test was performed at higher temperatures than the ideal CO₂ methanation temperature of 200–300°C. Figure 7A demonstrates that the sample mass remains steady in CO₂ at 400°C up to 2 h. The time-on-stream CO₂ conversion of this catalyst running at 350°C shows a lifetime up to 24 h with only a slight decrease. This decrease is perhaps caused by the agglomeration of cobalt particles, as indicated in TEM images (Figure 3); stabilization of the Co particles should obviate this problem.

FIGURE 7

FIGURE 7. (A) TGA curve of the 5wt% Co/GNP sample after reduction in a continuous CO₂ stream; (B) time-on-stream of CO₂ conversion by a 5_wt% Co/GNPs catalyst tested at 350°C under constant reaction conditions: 1 bar, 19.5 ml/min total flow rate with a reaction mixture containing 15_vol% of CO₂, 60_vol% of H₂, and 25_vol% of N₂.

4 Conclusions

Commercial GNP material was used as a support of a cobalt catalyst for CO₂ methanation. The as-synthesized Co/GNP catalysts exhibited higher intrinsic reactivity than the Al₂O₃-supported Co catalyst. The best Co/GNPs, according to the reactivity tests, were obtained with a loading of 5_wt% Co. TEM size analysis showed that larger Co particles were formed with increased Co loading, while Raman spectra showed that the growth of cobalt nanoparticles reduced the formation of interfaces between Co and the graphene surface, ultimately influencing the total number of Co active sites. As a result, fewer surface defects of graphene were produced in high-loading (10_wt% and 15_wt%) Co/GNP samples, which corresponded to lower catalytic reactivity and CH₄ yield. Cobalt surface analysis using XPS and Raman spectra showed that a higher oxidative phase of Co (Co³⁺) was observed on the surface of materials with high Co loading. With the same loading, the sample supported by GNPs had more of the Co²⁺ phase than the cobalt supported by Al₂O₃. Accordingly, we conclude that the GNP support promotes the formation and maintenance of more of the reactive Co²⁺ phase on the catalyst surface for CO₂ methanation. Modest Co loading (5_wt%) promoted the formation of graphene defects while simultaneously forming more CoO active phases for increased reactivity. In conclusion, this research has been the first to demonstrate the potential reactivity of a carbon-supported Co catalyst and the synergistic role of graphene support for CO₂ thermal methanation. Further efforts need to be devoted to improving the lifetime of this catalyst system.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Author contributions

LZ performed the synthesis, tests, characterization, data analysis, and paper drafting. TM performed the TEM and SEM microscopy measurements. YK measured the TGA and ICP-OES catalysts. LZ wrote the paper, with inputs from other authors. AZ reviewed the paper. All authors contributed to the article and approved the submitted version.

Funding

This research was supported by GAZNAT and the Swiss Federal Office of Energy (SFOE) under contract SI/502228-0.

Acknowledgments

The authors acknowledge the financial support of EPFL and Empa in Switzerland.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fceng.2023.1160254/full#supplementary-material

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