Plasma-catalytic reforming of CH4–CO2 over porous Ni/N-doped carbon: efficient syngas production and mechanistic insights

Tian Chang *abcd, Zhao Yang ab, Zuotong Zhao ab, Xuanchen Chang ab and Chuanyi Wang abe
aSchool of Environmental Science and Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China. E-mail: changtian@sust.edu.cn
bShaanxi University Key Laboratory of Industrial Pollution Control and Environmental Health, Shaanxi University of Science and Technology, Xi'an 710021, China
cState Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710049, China
dState Key Laboratory of High-efficiency Utilization of Coal and Green Chemical Engineering, Ningxia University, Yinchuan 750021, China
eDepartment of Environmental and Sustainable Engineering, Faculty of Engineering, Chulalongkorn University, 254 Phayathai Road, Pathumwan, Bangkok, 10330, Thailand

Received 31st July 2025 , Accepted 12th November 2025

First published on 13th November 2025


Abstract

The integration of non-thermal plasma and catalysis offers a promising route for low-temperature reforming of methane (CH4) and carbon dioxide (CO2) into high-value syngas (H2 and CO), enabling efficient activation of stable molecules and tunable product selectivity. However, limitations in energy efficiency, selectivity control, and catalyst durability remain. In this study, a water-cooled dielectric barrier discharge (DBD) reactor coupled with a porous nitrogen-doped carbon-supported nickel catalyst (Ni/N–C) was developed to enhance CH4–CO2 reforming performance. The results showed that increasing the CH4/CO2 molar ratio significantly enhanced both reactant conversion and syngas selectivity, while a higher gas flow rate adversely affected conversion efficiency. Under optimal conditions (60 mL min−1 gas flow rate, 1[thin space (1/6-em)]:[thin space (1/6-em)]5 molar ratio of CH4/CO2), CH4 and CO2 conversions reached 44.1% and 20.0%, with CO and H2 selectivities of 67.6% and 48.1%, respectively. The corresponding energy efficiency was 0.39 mmol kJ−1. Mechanistic insights derived from catalyst characterization and performance analysis revealed that moderate acid sites promoted CH4 activation and facilitated the selective formation of C2 hydrocarbons, while abundant basic sites enhanced CO2 adsorption and activation, thereby improving CO and H2 selectivity. The synergistic effect of acid–base site modulation and plasma-driven activation played a key role in steering the reaction pathway and optimizing product distribution. This work highlighted the potential of tailored Ni-based catalysts for efficient and selective plasma-catalytic reforming of CH4 and CO2 into syngas.


1. Introduction

Currently, the world is facing dual challenges of global warming and escalating energy demands. The 2015 Paris Agreement established a goal to limit the global temperature rise to within 1.5 °C above pre-industrial levels, while according to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report, the global average temperature has already risen by 1.1 °C.1–3 The excessive emission of greenhouse gases has led to a range of environmental challenges, including climate change, air pollution, rising sea levels, and increased frequency of extreme weather events.4 CH4 and CO2 are recognized as two major greenhouse gases, with their mitigation strategies and emission reduction technologies drawing significant scientific and societal attention.5 Dry reforming of methane (DRM) offers a promising route for simultaneous conversion of CH4 and CO2 into CO and H2 (eqn(1)), valuable intermediates for downstream processes such as Fischer–Tropsch synthesis to yield alcohols, acids, and aldehydes.6 This approach not only addresses carbon emission reduction and recycling but also contributes to chemical feedstock generation and partial fulfillment of energy needs.7 However, the DRM reaction is highly endothermic (ΔH298K = +247.3 kJ mol−1), and the activation of CH4 (C–H, 439 kJ mol−1) and CO2 (C[double bond, length as m-dash]O, 750 kJ mol−1) requires high energy input. As a result, conventional catalytic DRM typically operates above 700 °C, imposing significant energy and operational costs.8 Therefore, developing efficient catalytic systems capable of activating CH4 and CO2 under milder conditions is critical to improving the energy efficiency and sustainability of DRM.
 
CH4 + CO2 → 2CO + 2H2 ΔH298K = +247.3 kJ mol−1(1)

Plasma technology has brought new development prospects for DRM. According to the degree of thermodynamic equilibrium among electrons, ions, and neutral species, plasma can be generally classified into two categories: thermal plasma and non-thermal plasma (NTP).9 Thermal plasma processes can achieve extremely high temperatures (typically above 4000 K), enabling near-complete conversion of reactants and effective treatment of solid waste, while simultaneously producing syngas with high CO and H2 selectivities (>80%).10,11 In contrast, NTP offers a promising strategy for enabling DRM under ambient or near-ambient conditions. With electron temperatures typically ranging from 1 to 10 eV, NTP provides sufficient energy to activate thermodynamically stable CH4 (4.5 eV) and CO2 (5.5 eV) molecules.12 Through processes like excitation, collision, ionization, and dissociation, NTP creates high-energy electrons and reactive radicals from CH4 and CO2 under ambient conditions. This enables the technology to drive thermodynamically constrained reactions to proceed rapidly under low-temperature conditions, thereby significantly reducing the requirements for high temperatures and associated energy consumption.13 However, NTP systems still face challenges such as relatively low selectivity toward target products and the need for further improvement in energy efficiency.14 Consequently, researchers have introduced catalysts to lower activation energy and regulate reaction pathways, achieving efficient conversion of CH4 and CO2 with substantially improved product selectivity and energy efficiency.15 As the core component of DRM technology, catalysts have become the primary research focus, with most studies concentrating on catalyst development.16

Currently, noble metal catalysts loaded with rhodium (Rh), platinum (Pt), and palladium (Pd) exhibit excellent catalytic activity in DRM reactions. However, their extremely limited global reserves result in high costs, making industrial-scale applications challenging.17 In contrast, transition metal catalysts (e.g., Ni, Co, and Fe) combine high intrinsic activity with cost-effectiveness.18 Among them, Ni-based catalysts, typically supported on materials such as metal oxides,19 zeolite,20 and composite oxides,21 have been widely employed in plasma-assisted DRM systems due to their cost-effectiveness and strong activity in C–C/C–H bond activation.18 For example, Abbas et al.22 fabricated a Ni–Co3O4/TiO2 NR (nanorod) catalyst that, when integrated with NTP, achieved CO and H2 selectivities of 49.0% and 50.1%, respectively, which were significantly higher than the 31.6% and 33% obtained in plasma-only operation. In addition, the hybrid system attained a maximum energy efficiency of 0.131 mmol kJ−1, representing a 26% improvement compared to the plasma-only system. Besides catalytic activity, recent studies have highlighted the crucial role of support properties in determining active site dispersion, charge transfer, and plasma–catalyst synergy. For instance, Diao et al.23 showed that Ni/NS-Al2O3 with finely dispersed Ni nanoparticles enhanced electron density and reduced CO2 activation energy, while Xu et al.24 found that embedding Ni into the mesopores of MCM-41 improved dispersion and accessibility of active sites. Despite these advances, conventional metal oxides and zeolites still face challenges related to limited activity or structural stability under plasma conditions. Hence, the development of novel support materials with tailored textural and electronic properties is essential for further enhancing DRM performance in plasma-catalytic systems.

Metal–organic framework (MOF)-derived carbon materials have emerged as highly promising supports due to their large specific surface area, well-developed porosity, and tunable pore structures. These properties facilitate the uniform dispersion of metal nanoparticles and enhance their stability under reaction conditions.25 Among them, ZIF-8-derived carbon materials are particularly attractive due to their exceptional thermochemical stability and activation capacity after metal incorporation.26 For example, Guo et al.27 synthesized nitrogen-doped, hierarchically porous carbon polyhedra from a ZIF-8 framework. They found that the well-defined micro- and mesoporous structure significantly enhanced mass transport and exposed internal active sites, resulting in excellent CO2 photoconversion performance under mild conditions. Similarly, Li et al.28 developed M/ZIF-8-C catalysts (M = Ni, Fe, Co, and Cu) for CO2 hydrogenation. Their study demonstrated that highly dispersed metal nanoparticles, along with pyridinic nitrogen and carbide species, effectively promoted CO2 activation and provided abundant active sites. These findings collectively highlight the potential of ZIF-8-derived carbon materials as multifunctional supports for CO2 conversion reactions. Moreover, nitrogen co-doping introduces abundant defect sites, which enhance charge transfer, improve metal anchoring, and contribute to higher mass activity and catalytic stability.29 Despite these advantages, the application of MOF-derived carbon materials in DRM catalysis remains relatively underexplored. In particular, the underlying reaction mechanisms, those occurring under NTP conditions, are not yet fully understood. This knowledge gap presents both a challenge and an opportunity for future research.

In this study, a porous nitrogen-doped carbon material (N–C) was synthesized as a support for nickel and integrated into a water-cooled dielectric barrier discharge (DBD) reactor for low-temperature reforming of CH4 and CO2. The effects of key process parameters, including the gas flow rate and CH4/CO2 molar ratio, on conversion rates, product selectivity, and energy efficiency were thoroughly investigated. Based on the analysis of reaction products, identification of plasma-generated reactive species, and detailed catalyst characterization, a synergistic mechanism governing CH4/CO2 reforming over the Ni/N–C catalyst under NTP conditions was proposed.

2. Experimental

2.1. Chemicals and instruments

CH4 (99.99%) and CO2 (99.99%) were purchased from Xi'an Yuefeng Tianyi Gas Co., Ltd. (China). Zinc nitrate hexahydrate (Zn(NO3)2·6H2O, analytical reagent (AR), 98%), 2-methylimidazole (C4H6N2, AR, 98%), and methanol (CH3OH, AR, ≥99.5%) were procured from Shanghai Macklin Biochemical Technology Co., Ltd. (China). Nickel nitrate hexahydrate (Ni(NO3)2·6H2O, AR, 98%) and hydrochloric acid (HCl, AR, 36–38%) were obtained from Sinopharm Chemical Reagent Co., Ltd. (China). Deionized water was used throughout the experiments.

2.2. Catalyst preparation

2.2.1. Preparation of the N–C support. ZIF-8 was synthesized with reference to the conventional method reported in the literature.29 Specifically, 5.578 g of Zn(NO3)2·6H2O was dissolved in 150 mL of methanol, followed by ultrasonication at 40 °C for 10 minutes. Similarly, 6.160 g of 2-methylimidazole was dissolved in 150 mL of methanol to prepare the corresponding solution. First, a total of 4 mL of the metal salt solution was injected into the 2-methylimidazole solution and ultrasonicated for 10 minutes, followed by the addition of the remaining solution and another 10 minutes of ultrasonication. The mixture was then subjected to static growth at 35 °C for 12 hours. After centrifugation at 8000 rpm for 3 minutes, thorough washing with methanol, and drying at 80 °C for 12 hours, a white ZIF-8 powder was obtained. The dried ZIF-8 was carbonized in N2 at 850 °C (heating rate 3 °C min−1) for 3 hours. The resulting black sample was washed three times with 1 M HCl solution to remove residual inorganic components, ultimately yielding the N–C support.
2.2.2. Preparation of the Ni/N–C catalyst. The procedure involved adding 5 g of N–C support to an aqueous solution containing 2.750 g of Ni(NO3)2·6H2O, which was stirred for 5 hours and then centrifuged at 6000 rpm for 5 minutes, followed by drying at 80 °C for 12 hours. Finally, the dried sample was calcined in N2 at 550 °C (heating rate: 2 °C min−1) for 4 hours. After cooling to room temperature, the 10 wt% Ni/N–C catalyst was obtained.

2.3. Experimental setup

Fig. 1 shows a schematic diagram of the experimental setup. High-purity CH4 and CO2 gases were regulated using mass flow controllers (D07, Sevenstar) and premixed before being introduced into a cylindrical DBD reactor. The reactor comprised a quartz tube (outer diameter: 12 mm; inner diameter: 8 mm) with a central stainless-steel high-voltage electrode (diameter: 4 mm) and a water-cooled outer electrode. The discharge gap was 2 mm, and the discharge length was 50 mm. The catalyst bed was prepared by uniformly mixing 200 mg of tablet-pressed and sieved catalyst with 400 mg of quartz sand. The mixture was loaded into the quartz tube, fixed in place using quartz wool plugs, and maintained at 10 °C using a water cooler equipped with a temperature detector sensor (PT100, Dongyang Sanxing Temperature Instrument Co., Ltd., China). An adjustable high-voltage alternating current (AC) power supply (CTP-2000 K, Nanjing Suman Plasma Technology Co., Ltd., China) delivering energy to the plasma system was employed for plasma generation. Electrical signals were recorded using a digital oscilloscope (DSOX2014A, Keysight Technologies, USA), with discharge power calculated based on Lissajous figure analysis. Liquid products (CH3OH, C2H5OH, CH3COOH, and CH3COCH3) were condensed in a cooling trap and collected in a liquid-phase bottle. The volumetric flow rate of the outlet gas was measured using a soap-film flowmeter. Gaseous reactants and products such as CO, H2, and CxHy (C2H6, C2H4, C2H2, C3H8, and C3H6) were analyzed online via a gas chromatograph (9790 II, Fuli, China). Additionally, active species generated during plasma-driven CH4–CO2 reforming were detected using optical emission spectroscopy (OES) with a spectrometer (Maya-2000 Pro, Ocean Insight, USA).
image file: d5cy00936g-f1.tif
Fig. 1 Schematic diagram of the experimental setup.

The conversion of reactants, selectivity to gaseous products and oxygenates, and energy efficiency were calculated using the following equations (eqn (2)–(13)):

 
image file: d5cy00936g-t1.tif(2)
 
image file: d5cy00936g-t2.tif(3)
 
image file: d5cy00936g-t3.tif(4)
 
image file: d5cy00936g-t4.tif(5)
 
image file: d5cy00936g-t5.tif(6)
 
Soxygenates (%) = 100% − (SCO + SCxHy) − ca. 5% carbon deposition(7)
 
image file: d5cy00936g-t6.tif(8)
 
image file: d5cy00936g-t7.tif(9)
 
image file: d5cy00936g-t8.tif(10)
 
image file: d5cy00936g-t9.tif(11)
 
image file: d5cy00936g-t10.tif(12)
 
image file: d5cy00936g-t11.tif(13)
where XCH4 and XCO2 represent the conversions of CH4 and CO2, respectively; SH2, SCO and SCxHy represent the selectivities to H2, CO and CxHy, respectively; Soxygenates, SCH3COOH, SCH3COCH3, SCH3OH and SCH3CH2OH represent the selectivities to oxygenates, CH3COOH, CH3COCH3, CH3OH and CH3CH2OH, respectively; E (mmol kJ−1) represents the energy efficiency of individual components (CH4, CO2, CO, and H2), Etotal (mmol kJ−1) represents the total energy efficiency, P (kW) represents the plasma discharge power, q (mol s−1) represents the flow rate of each component, and subscripts ‘in’ and ‘out’ represent the inlet and outlet of the reactor, respectively.

3. Results and discussion

3.1. Discharge characteristics

Catalysts exert a pronounced influence on the discharge behavior of DBD plasma, while discharge power and energy density play vital roles in determining the type and quantity of active species generated. Fig. 2(a and b) present the discharge signal profiles for plasma-only and Ni/N–C catalyst-packed conditions at a discharge power of 25 W. In both cases, the voltage and charge waveforms exhibit quasi-sinusoidal characteristics.30 In the plasma-only system, the charge peak is approximately 0.47 μC, accompanied by numerous sharp current spikes, indicating that the discharge mode is predominantly filamentary. After introducing the catalyst, both the number and amplitude of charge spikes decrease significantly, whereas the peak charge increases to ∼0.65 μC. This behavior suggests a transition toward a mixed discharge regime combining weak filamentary and surface discharges due to the presence of the catalyst in the discharge gap.31 The corresponding discharge images (Fig. S1) visually confirm this shift in the discharge pattern.
image file: d5cy00936g-f2.tif
Fig. 2 Discharge signals: (a) plasma only; (b) packed with the Ni/N–C catalyst.

3.2. Characterization of materials

To investigate the structural evolution of the carbon support and the crystallinity of the active metal phase, X-ray diffraction (XRD) analysis was performed on the N–C support and Ni/N–C catalyst. As shown in Fig. 3a, the N–C support exhibits broad diffraction peaks at 2θ = 24.1° and 44.4°, corresponding to the (002) and (101) planes of graphitic carbon, respectively, which reflect its predominantly amorphous structure and low degree of graphitization.32 For the Ni/N–C catalyst, well-defined peaks are observed at 2θ = 44.5°, 51.8°, and 76.4°, indexed to the (111), (200), and (220) planes of metallic Ni (PDF#04-0850), confirming the successful incorporation of highly crystalline Ni nanoparticles.33 It is noteworthy that no characteristic diffraction peaks of NiO were detected in the XRD patterns, which may be attributed to its small crystallite size, highly dispersed state, and low crystallinity.34 The graphite-related peaks remained largely unchanged after Ni loading, indicating that the structural integrity of the N–C framework was preserved.
image file: d5cy00936g-f3.tif
Fig. 3 (a) XRD patterns of the N–C support and Ni/N–C catalyst; (b) Raman spectrum of the Ni/N–C catalyst; (c) FTIR spectrum of the Ni/N–C catalyst; (d) N2 adsorption–desorption isotherms of the N–C support and Ni/N–C catalyst; (e) pore size distribution profiles of the N–C support and Ni/N–C catalyst.

Raman spectroscopy (Fig. 3b) was employed to further probe structural defects in the carbon support. The spectrum of the Ni/N–C catalyst displays three characteristic bands: the D band (∼1368 cm−1) arising from disordered carbon and structural defects, the D band at 1368 cm−1 associated with sp3 defects, and the G band at 1585 cm−1 corresponding to the stretching vibrations of all sp2-bonded pairs, with a 2D band at ∼2651 cm−1, which may be related to the presence of layered or partially ordered carbon domains.35 The intensity ratio of the D to G bands (ID/IG = 1.14) suggests a high density of surface defects and edge sites, likely introduced by nitrogen doping and carbon disorder. These features are expected to enhance metal dispersion, active site accessibility, and ultimately catalytic performance.36

Fourier transform infrared spectroscopy (FTIR) spectra (Fig. 3c) were recorded to identify surface functional groups. The broad absorption band at 3410 cm−1 is attributed to O–H stretching vibrations, including surface hydroxyl groups and adsorbed water.37 The peak at 2922 cm−1 corresponds to C–H stretching vibrations. A strong band at 1584 cm−1 can be ascribed to overlapping C[double bond, length as m-dash]N and C[double bond, length as m-dash]C stretching vibrations in aromatic or nitrogen-doped structures. Additional peaks at 1500 cm−1 and 1292 cm−1 are assigned to C[double bond, length as m-dash]N/C[double bond, length as m-dash]C aromatic ring vibrations and C–N stretching modes, respectively.38 These results confirm the successful formation of nitrogen-doped carbon structures in the Ni/N–C catalyst.

Fig. 3d displays the N2 adsorption–desorption isotherms and pore size distribution profiles of the N–C support and Ni/N–C catalyst. Both samples exhibit type IV isotherms with H4-type hysteresis loops, characteristic of mesoporous materials.39 Compared with the N–C support, the Ni/N–C catalyst shows higher nitrogen uptake, consistent with its increased specific surface area and pore volume, as summarized in Table S1. This enhancement may be attributed to structural modification of the carbon matrix during high-temperature calcination, as well as the formation of additional porosity induced by Ni nanoparticle dispersion.40 Pore size distribution analysis (Fig. 3e) reveals that both materials contain dominant mesopores in the 2–5 nm range. Notably, the average pore diameter of the Ni/N–C catalyst is slightly smaller than that of the N–C support, suggesting that metal incorporation may lead to the generation of more finely distributed mesopores and micropores, likely due to restructuring or fragmentation of pore walls during Ni loading and thermal treatment.41 In addition, inductively coupled plasma-mass spectrometry (ICP-MS) analysis confirmed a nickel loading of 9.73 wt% for the Ni/N–C catalyst, which closely matches the theoretical value of 10.00 wt%. This result indicates that the metal incorporation process was highly efficient, with negligible Ni loss during impregnation and calcination.

Transmission electron microscopy (TEM) characterization was conducted to observe the morphological changes and Ni particle size of the Ni/N–C catalyst before and after the reaction. As shown in Fig. 4a and d, the N–C support derived from ZIF-8 templates exhibits a well-defined rhombic dodecahedral morphology with an average particle size of approximately 500 nm, consistent with previous reports.42 The surface appears smooth prior to the reaction, and well-dispersed Ni nanoparticles with an average diameter of 6.4 nm are clearly observed. This small particle size indicates high metal dispersion and increased density of accessible active sites, which are beneficial for initial catalytic performance.23 The TEM images (Fig. 4e and h) of the fresh Ni/N–C catalyst show that the N–C framework retains its morphological integrity, with Ni nanoparticles remaining uniformly distributed across the surface. The Ni nanoparticles remain uniformly dispersed on the support with an average particle size of 7.9 nm, exhibiting a marginal increase compared to the fresh state, likely due to slight agglomeration. Notably, no significant carbon deposition was observed on the spent catalyst. High-resolution transmission electron microscopy (HRTEM) images revealed 0.203 nm lattice spacings corresponding to Ni (111) planes in both fresh and spent catalysts (Fig. 4c and g), consistent with the XRD data. More importantly, an interplanar spacing of 0.241 nm corresponding to the (111) plane of NiO (PDF#47-1049) can be clearly observed (Fig. 4b and f), indicating the coexistence of Ni and NiO particles on the Ni/N–C catalyst. These observations collectively indicate that the Ni/N–C catalyst maintains excellent structural stability and metal dispersion under reaction conditions.


image file: d5cy00936g-f4.tif
Fig. 4 TEM, HRTEM, and particle size distribution histograms of the Ni/N–C catalyst: (a–d) fresh; (e–h) spent.

X-ray photoelectron spectroscopy (XPS) was employed to investigate the surface chemical states and elemental composition of the Ni/N–C catalyst (Fig. 5). In the Ni 2p spectrum (Fig. 5a), the peaks located at 852.4 and 854.8 eV correspond to Ni0 and Ni2+ species in the Ni 2p3/2 region, respectively, and a prominent satellite peak at 860.4 eV further supports the assignment of Ni2+.43 Additionally, peaks at 871.7 and 878.2 eV are attributed to Ni0 in the Ni 2p1/2 region and its associated satellite feature, confirming the coexistence of both oxidized and metallic nickel species.44 This observation is consistent with the HRTEM results shown in Fig. 4. Furthermore, the proportions of Ni0 and Ni2+ are 55.81% and 44.19% (Table 1), respectively, corresponding to a Ni0/Ni2+ ratio of 1.26. The relatively high content of metallic Ni0 suggests that the catalyst possesses good reducibility and abundant exposed metallic sites, while the remaining NiO species may provide additional basic sites that could influence the adsorption and activation of reactant molecules in subsequent reactions.45,46 The O 1s spectrum (Fig. 5b) was deconvoluted into three distinct components: lattice oxygen (OI, 528.8 eV), chemisorbed oxygen (OII, 530.6 eV), and physisorbed oxygen (OIII, 531.7 eV).47 The high proportion of chemisorbed oxygen indicates the presence of abundant surface-active oxygen species (Table 1), which are believed to play a key role in enhancing CH4 and CO2 adsorption and sustaining redox cycles during the reforming process.46 In the N 1s spectrum (Fig. 5c), three types of nitrogen species were identified: pyridinic N (398.7 eV), pyrrolic N (400.2 eV), and graphitic N (401.6 eV).48 Nitrogen functionalities can modulate the electronic environment and promote metal anchoring and dispersion, contributing to improved catalytic performance.28 The C 1s spectrum (Fig. 5d) shows characteristic peaks at 285.1 eV (C–C), 286.1 eV (C–N), and 288.8 eV (C[double bond, length as m-dash]O), confirming the presence of various oxygen- and nitrogen-containing surface functionalities.48


image file: d5cy00936g-f5.tif
Fig. 5 XPS spectra of the Ni/N–C catalyst: (a) Ni 2p, (b) O 1s, (c) N 1s, and (d) C 1s.
Table 1 Ni 2p and O 1s spectral results of the Ni/N–C catalyst
Catalyst Ni0 (%) Ni2+ (%) Ni0/Ni2+ OI (%) OII (%) OIII (%)
Ni/N–C 55.81 44.19 1.26 7.52 49.46 43.02


To investigate the reducibility of the catalyst and the interaction between the metal and support, hydrogen-temperature programmed reduction (H2-TPR) characterization was performed as shown in Fig. 6a. The N–C support shows a broad hydrogen consumption signal from 200 to 550 °C, with a main peak at 376 °C attributed to the reduction of nitrogen-containing surface groups.49 In comparison, the Ni/N–C catalyst exhibits multiple distinct reduction peaks. The first peak at 303 °C is mainly assigned to the reduction of small NiO particles with weak interactions with the N-doped carbon support.50 However, this peak overlaps with the reduction region of N–C, suggesting possible contributions from residual or Ni-perturbed nitrogen groups. The second peak at 458 °C likely originates from nitrogen functionalities that are partially covered or electronically influenced by nearby Ni/NiO species, leading to delayed reduction.51 The peak at 523 °C is attributed to NiO particles embedded within the mesoporous structure, where strong metal–support interactions with nitrogen dopants increase the reduction temperature by facilitating electron transfer from the support to NiO.33 Finally, the broad high-temperature peak at 675 °C corresponds to highly dispersed NiO species strongly interacting with the support, possibly through Ni–N coordination. These strong interactions stabilize the Ni2+ state and hinder reduction.52 Overall, the reduction behavior of Ni/N–C reflects a complex interplay between Ni/NiO dispersion, metal–support interaction strength, and the influence of nitrogen-doped sites in the carbon matrix.53


image file: d5cy00936g-f6.tif
Fig. 6 (a) H2-TPR, (b) NH3-TPD, (c) CO2-TPD, and (d) TGA profiles of the fresh and spent Ni/N–C catalyst.

Ammonia-temperature programmed desorption (NH3-TPD) was used to probe the surface acidic characteristics of the N–C support and Ni/N–C catalyst (Fig. 6b), with semi-quantitative results based on peak areas summarized in Table S2. The desorption below 150 °C is attributed to physical adsorption.54 A weak desorption peak between 150 and 200 °C indicates the presence of weak acid sites.55 The N–C support exhibited a strong acid desorption peak at 485 °C, which may be attributed to Lewis acid sites associated with electronic vacancies in the mesoporous carbon. In contrast, the Ni/N–C catalyst showed a prominent medium-strength acid peak at 297 °C, likely originating from unsaturated Ni centers formed through interaction with nitrogen dopants.56 Semi-quantitative analysis of the peak areas indicates that after Ni loading, strong acid sites were significantly reduced or eliminated, while the number of medium-strength acid sites increased notably. This redistribution of acid sites is considered beneficial, as excessively strong acidity may hinder CO2 adsorption and promote carbon deposition.57 The increase in medium-strength acid sites contributes to enhanced catalytic activity and improved resistance to carbon formation.

Characterization of the basic sites on the material surface was performed using carbon dioxide-temperature programmed desorption (CO2-TPD) analysis (Fig. 6c), as shown in Table S3. The desorption peaks observed at 128 °C for the N–C support and 111 °C for the Ni/N–C catalyst are attributed to the physical adsorption of CO2. In both samples, CO2 desorption above 600 °C is primarily associated with the thermal degradation of the carbon framework.58 Notably, the Ni/N–C catalyst exhibits a prominent desorption peak at 554 °C, which indicates the presence of abundant strong basic sites. This enhancement in basicity is attributed to the introduction of Ni, particularly the formation of NiO nanoparticles that contribute significantly to the generation of strong basic sites on the catalyst surface.40 The increased density of basic sites improves the adsorption and activation of CO2, thereby facilitating its conversion.59

Thermogravimetric analysis (TGA) analysis of fresh and spent catalysts revealed that the fresh catalyst exhibited a 12.1% mass loss at 0–130 °C (Fig. 6d), attributed to desorption of guest methanol molecules from N–C crystal cavities and evaporation of moisture. Notably, the spent catalyst showed significantly reduced mass loss in this range, indicating effective removal of surface water and solvent during the reaction.60 A substantial 51.7% mass loss occurred between 300 and 600 °C for the fresh catalyst, corresponding to oxygen-containing functional group decomposition in Ni/N–C.61 Remarkably, the total mass loss of the spent catalyst increased by 4.6% compared to the fresh catalyst, primarily due to carbon deposition during the catalytic process.62

3.3. Catalytic performances

3.3.1. Synergistic interactions. The reforming reaction performance was investigated in distinct modes: plasma-alone and plasma–catalyst systems. As shown in Fig. 7a, the plasma-alone mode yielded CH4 and CO2 conversions of 11.1% and 8.7%, respectively, due to activation by high-energy electrons generated in the discharge.14 When plasma was coupled with the N–C support, the conversion rate of CH4 increased, while the conversion rate of CO2 remained almost unchanged. Notably, a significant enhancement was observed in the plasma–Ni/N–C system, where CH4 and CO2 conversions reached 16.2% and 13.3%, respectively—approximately 1.5 times higher than in the plasma-alone mode. The energy efficiency also improved from 0.15 to 0.25 mmol kJ−1. Fig. 7b compares the product selectivities among the three systems. The plasma–N–C system increased the CO selectivity, but the H2 selectivity remained almost unchanged. Meanwhile, the plasma–Ni/N–C system achieved markedly higher selectivities for both CO (59.2%) and H2 (45.2%) compared to the plasma-alone system (44.5% and 41.1%, respectively). Moreover, the total selectivity for C2–C3 hydrocarbons also improved in the plasma–Ni/N–C system. The catalyst integration not only enhances conversion but also steers product distribution toward syngas and light hydrocarbons.63
image file: d5cy00936g-f7.tif
Fig. 7 (a) Conversion rates of CH4 and CO2; (b) selectivity to gaseous products; (c) component-specific selectivity to C2–C3 hydrocarbons (discharge power: 25 W; gas flow rate: 60 mL min−1; CH4/CO2 molar ratio: 1[thin space (1/6-em)]:[thin space (1/6-em)]1).

As shown in Fig. 7c, C2H6 was the dominant C2–C3 hydrocarbon product across all modes, accounting for approximately 70% of total hydrocarbon selectivity. Other products followed the order C3H8 > C2H2 > C2H4 > C3H6; among them, C3H6 was present only in trace amounts. In the plasma–N–C system, although the total selectivity for C2–C3 hydrocarbons remained nearly unchanged upon incorporating the N–C support, the addition enhanced the selectivity for C2H6 while reducing that for C3H8. In the plasma–Ni/N–C system, the selectivity toward C2H6 (up to 17.2%) and C2H4 increased, while C3H8 selectivity slightly decreased. This shift suggests that the catalyst not only facilitates C–C coupling reactions but also helps regulate hydrogenation pathways. The presence of well-dispersed Ni nanoparticles and nitrogen-doped carbon may weaken the over-hydrogenation of intermediates, thereby promoting the formation of light olefins and alkynes. These results confirm the role of the Ni/N–C catalyst in tuning product distribution under plasma conditions. According to the NH3-TPD and CO2-TPD characterization results, the N–C support has almost no basic sites for chemisorption but a large number of acidic sites, indicating that the acidic sites may enhance both the CH4 conversion rate and C2H6 selectivity. Meanwhile, the Ni/N–C catalyst possesses more basic sites and medium acid sites, suggesting that the synergetic effect between basic and medium acid sites can significantly improve CO2 conversion as well as the selectivities towards CO and H2.

3.3.2. Influence of the gas flow rate. The effect of the gas flow rate on the performance of the plasma-coupled N–C support and plasma–Ni/N–C catalyst systems was systematically evaluated. As shown in Fig. 8a and b, increasing the gas flow rate led to a general decline in CH4 and CO2 conversion rates for both systems. For the Ni/N–C catalyst, the highest conversions of CH4 (23.1%) and CO2 (15.1%) were obtained at 40 mL min−1. However, when the flow rate was increased to 80 mL min−1, the conversions decreased to 13.0% and 10.3%, respectively. This trend is attributed to shortened residence time and reduced molecular collision frequency at higher flow rates, which limit reactant activation and conversion efficiency.64 Interestingly, although the conversions decreased, the energy efficiency of CH4 and CO2 reforming over the Ni/N–C catalyst increased with rising flow rate, owing to the greater absolute quantity of reactants processed within the same discharge period. This indicates that higher throughput compensates for lower per-molecule conversion, resulting in a net gain in energy efficiency.65 In contrast, the N–C support system exhibited minimal changes in energy efficiency, highlighting the superior activation capacity of the Ni-loaded catalyst.
image file: d5cy00936g-f8.tif
Fig. 8 Effects of the gas flow rate on CH4–CO2 reforming performance: (a and b) CH4 and CO2 conversion rates and energy efficiency; (c and d) CO and H2 selectivity and energy efficiency; (e) selectivity to gaseous hydrocarbon products (discharge power: 25 W; CH4/CO2 molar ratio: 1[thin space (1/6-em)]:[thin space (1/6-em)]1).

As shown in Fig. 8c and d, the selectivity for CO and H2 decreased with increasing flow rate, dropping from 67.9% to 58.5% and from 44.6% to 40.5%, respectively. Meanwhile, the total C2–C3 hydrocarbon selectivity increased from 19.9% to 26.3%. Notably, C2H6 selectivity showed a marked rise from 14.6% to 20.0% (Fig. 8e), which can be ascribed to enhanced recombination of image file: d5cy00936g-t12.tif radicals under shorter residence times, suppressing their decomposition into CO and H2.64 This shift reflects the kinetic competition between hydrogenation and reforming pathways. Furthermore, regardless of the gas flow rate variations, the Ni/N–C catalyst consistently outperformed the N–C support in terms of conversion, product selectivity, and energy efficiency. These improvements are primarily due to the high density of active Ni sites and the synergistic effect between the metal and nitrogen-doped carbon matrix, which together promote efficient plasma–catalyst interactions under dynamic flow conditions.66,67

3.3.3. Influence of the CH4/CO2 molar ratio. The effect of the CH4/CO2 molar ratio on the reforming performance of the plasma–Ni/N–C system was investigated, as shown in Fig. 9. When the CH4/CO2 ratio decreased from 5[thin space (1/6-em)]:[thin space (1/6-em)]1 to 1[thin space (1/6-em)]:[thin space (1/6-em)]5, both CH4 and CO2 conversion rates increased significantly, with CH4 conversion rising from 7.7% to 44.1% and CO2 conversion from 9.7% to 20.0% (Fig. 9a and b). This improvement is attributed to the higher CO2 content, which generates more reactive oxygen species via electron impact dissociation, enhancing C–H bond cleavage in CH4 (eqn (14)).65 Meanwhile, the increased CH4 conversion produces more H* radicals; H* undergoes self-recombination to form H2, which promotes the reverse water–gas shift (RWGS) reaction (eqn (15)) and further accelerates CO2 consumption.
image file: d5cy00936g-f9.tif
Fig. 9 Effects of the CH4/CO2 molar ratio on reforming performance: (a and b) CH4 and CO2 conversion rates and energy efficiency; (c and d) CO and H2 selectivity and energy efficiency; (e) selectivity to gaseous hydrocarbon products (discharge power: 25 W; CH4/CO2 molar ratio: 1[thin space (1/6-em)]:[thin space (1/6-em)]1).

As shown in Fig. 9c and d, CO selectivity increased markedly with decreasing CH4/CO2 ratio, reaching 67.6% at 1[thin space (1/6-em)]:[thin space (1/6-em)]5, due to the excess CO2 available for CO formation.65 H2 selectivity also increased, peaking at 48.0% under CO2-rich conditions, benefiting from enhanced hydrogen radical generation. Notably, once the CH4/CO2 ratio dropped below 2.5[thin space (1/6-em)]:[thin space (1/6-em)]1, the energy efficiencies for CH4, CO2, CO, and H2 over the Ni/N-C catalyst consistently surpassed those of the N–C support, reflecting the superior reforming capability of the metal-loaded system under oxidizing conditions. In contrast, the selectivity to C2–C3 hydrocarbons decreased with decreasing CH4/CO2 ratio (Fig. 9e). At a ratio of 5[thin space (1/6-em)]:[thin space (1/6-em)]1, the highest selectivities were observed for C2H6 (25.5%), C3H8 (13.8%), C2H2 (15.8%), and C2H4 (10.0%), with trace amounts of C3H6 (2.4%). These findings indicate that hydrocarbon chain growth and image file: d5cy00936g-t13.tif radical recombination are favored under CH4-rich conditions, whereas high CO2 concentrations suppress hydrocarbon formation and steer product selectivity toward syngas components (CO and H2).68,69

 
image file: d5cy00936g-t14.tif(14)
 
CO2 + 4H2 → CH4 + 2H2O(15)

3.3.4. Distribution of liquid products. As shown in Fig. 10a, the concentrations of liquid products were analyzed after 6 hours of reaction under three conditions: plasma-only, plasma–N–C and plasma–Ni/N–C systems. Evidently, under all three systems, the concentration of CH3OH was the highest, followed by CH3CH2OH, while only trace amounts of other liquid products were detected. In the plasma-alone system, the concentration of CH3OH was 7.8 mg mL−1, and that of CH3CH2OH was 2.0 mg mL−1. After coupling with the N–C support, the concentration of alcohols further increased. In the system combining plasma with the Ni/N–C catalyst, the concentration of alcohols, particularly CH3OH, significantly increased, with the CH3OH concentration reaching 15.4 mg mL−1—nearly twice that in the plasma-alone system. This highlights the critical role of Ni/N–C catalysis in promoting CH3OH production. This enhancement is attributed to the activation of CH4 by Ni0 species after Ni loading on the N–C support, which facilitates CH4 dissociation to produce image file: d5cy00936g-t15.tif radicals. These radicals can then react with OH* species derived from O* and H* to form CH3OH (image file: d5cy00936g-t16.tif), where image file: d5cy00936g-t17.tif acts as a key intermediate.11,70 Moreover, previous studies reported that Ni2+ (NiO) exhibited a weak adsorption capacity for CO*, which suppressed the CO* + OH* → COOH* and image file: d5cy00936g-t18.tif pathways, thereby favoring the direct formation of CH3OH through the coupling of image file: d5cy00936g-t19.tif and OH*.71 As shown in Fig. 10b, the selectivity for CH3OH remains the highest among the three systems, followed by CH3CH2OH. However, after coupling the plasma with either the N–C support or the Ni/N–C catalyst, the overall selectivity toward liquid products decreased. This may be attributed to the enhanced conversion of CH4 and CO2 toward gaseous products, such as CO and C2–C3 hydrocarbons. Nevertheless, the total concentration still shows a significant increase.
image file: d5cy00936g-f10.tif
Fig. 10 (a) Liquid product concentration distribution and (b) selectivity for plasma-only, the N–C support, and the Ni/N–C catalyst (discharge power: 25 W; gas flow rate: 60 mL min−1; CH4/CO2 molar ratio: 1[thin space (1/6-em)]:[thin space (1/6-em)]1).

3.4. Stability test of the Ni/N–C catalyst

Fig. 11 shows the 48 hour stability test of the CH4–CO2 reforming reaction using the plasma–Ni/N–C catalyst under optimal reaction conditions. As observed in Fig. 11a, the conversion rates of CH4 and CO2 remained largely constant throughout the test period, with only a slight decline toward the end. Specifically, the CH4 conversion decreased from 42.3% to 37.4% (a reduction of 4.9%), while the CO2 conversion dropped from 19.8% to 17.1% (a reduction of 2.7%). This minor decline may be attributed to the partial coverage of active sites by trace carbon deposits formed during the reaction. Fig. 11b reveals a modest increase in the selectivity to CO and H2 during the test. The CO selectivity increased from 66.3% to 71.5% (an increase of 5.2%), and the H2 selectivity increased from 47.2% to 49.5% (an increase of 2.3%). Fig. 11c and d further present the stable distribution of gaseous hydrocarbons and liquid products. The selectivity to gaseous hydrocarbons remained relatively stable at below 5%, while that to liquid products was maintained within 25%, with minor fluctuations in the selectivity to individual products. Methanol was consistently the dominant liquid product, exhibiting a selectivity of approximately 16% (Fig. 11d). Overall, the results demonstrate that the Ni/N–C catalyst maintains excellent catalytic stability during extended plasma-assisted CH4–CO2 reforming.
image file: d5cy00936g-f11.tif
Fig. 11 Stability performance of the plasma–Ni/N–C system: (a) CH4 and CO2 conversion rates; (b) CO and H2 selectivity; (c) gaseous hydrocarbon selectivity; (d) liquid product selectivity (discharge power: 25 W; gas flow rate: 60 mL min−1; CH4/CO2 molar ratio: 1[thin space (1/6-em)]:[thin space (1/6-em)]5).

As shown in Table 2, which compares the catalytic performance of various plasma-coupled Ni-based catalysts, the Ni/N–C catalyst developed in this study achieved CO and H2 selectivities of 67% and 48%, respectively, in CH4–CO2 reforming under relatively mild conditions (10 °C). Its energy efficiency reached 0.39 mmol kJ−1, ranking among the highest levels in the compared systems.71–75 Although some catalysts achieved higher absolute conversion rates, they required higher discharge powers (50–100 W) or lower gas flow rates, limiting their energy efficiency and scalability. The Ni/N–C catalyst, while maintaining competitive syngas selectivity, exhibited superior energy efficiency, underscoring the synergistic role of N-doped carbon in promoting active site dispersion, enhancing plasma–catalyst coupling, and improving overall energy utilization efficiency.

Table 2 Comparison of syngas selectivity and energy efficiency in CH4–CO2 reforming using plasma-coupled Ni-based catalysts
Catalysts Discharge power (W) Gas flow rate (mL min−1) CH4/CO2 molar ratio Conversion (%) Selectivity (%) Energy efficiency (mmol kJ−1) Ref.
CH4 CO2 CO H2
Ni/N–C 25 60 1[thin space (1/6-em)]:[thin space (1/6-em)]5 44 20 67 48 0.39 This work
NiGa/NF 25 30 1[thin space (1/6-em)]:[thin space (1/6-em)]1 16 9 41 37 0.12 71
Ni/SiO2 50 20 1[thin space (1/6-em)]:[thin space (1/6-em)]1 55 44 61 48 0.27 72
Ni/La2O3–MgAl2O4 100 20 1[thin space (1/6-em)]:[thin space (1/6-em)]1 86 84 49 50 0.13 73
Ni/γ-Al2O3 50 50 1[thin space (1/6-em)]:[thin space (1/6-em)]1 56 30 52 31 0.32 74
Co/Ni-MOF 22.5 30 1[thin space (1/6-em)]:[thin space (1/6-em)]1 52 34 53 47 0.13 75


3.5. Reaction mechanism

3.5.1. Analysis of plasma active species. The active species generated during the plasma reforming of CH4 and CO2 were characterized using OES across the 200–800 nm spectral range. As shown in Fig. 12a, various excited radicals were observed, including CO2+, CO, CH, OH, CO2, C2, Hα and O. The CO2+ (A2Π–X2Π) bands were detected at 287.6, 337.7, 351.3, and 369.6 nm, while the CO emission bands corresponding to the b3Σ–a3Π and B1Σ–A1Π transitions were observed at 287.9 nm and within the 450–570 nm range, confirming CO formation as a major pathway.12 The C2 (d3Π–a3Π) Swan bands appeared between 460 and 520 nm, likely arising from CO decomposition and subsequent carbon–carbon bond formation.76 CH radicals were identified via C2Σ+–X2Π, B2Σ–X2Π, and A2Δ–X2Π transitions at 315.4, 391.2, and 431.2 nm, indicating hydrocarbon fragmentation and recombination.12,19 OH radicals, attributed to the A2Σ+–X2Π and 3Π–3Σ transitions, were observed at 311.3 and 356.1 nm, and likely originated from trace moisture or CO2 dissociation within the DBD reactor.12,19 The CO2 (1B2–X1Σ+) bands were also present at 375.2, 426.6, and 433.7 nm, confirming incomplete CO2 decomposition under discharge conditions.77,78 Additionally, relatively weak intensity peaks corresponding to the Hα (3d2D–2p2P0) transition at 656.3 nm and the O (3s5S0–3p5P) transition at 777.5 nm were detected.12 Although image file: d5cy00936g-t20.tif and image file: d5cy00936g-t21.tif cannot be directly detected by OES, the concurrent presence of CH and Hα radicals suggests the stepwise dehydrogenation of CH4 to image file: d5cy00936g-t22.tif (x = 1, 2, 3) intermediates, as outlined in (eqn (16)–(19)).
 
image file: d5cy00936g-t23.tif(16)
 
image file: d5cy00936g-t24.tif(17)
 
image file: d5cy00936g-t25.tif(18)
 
CH* + e → C* + H* + e(19)

image file: d5cy00936g-f12.tif
Fig. 12 (a) OES spectrum (discharge power: 25 W; gas flow rate: 60 mL min−1; CH4/CO2 molar ratio: 1[thin space (1/6-em)]:[thin space (1/6-em)]1) and (b) non-thermal plasma-coupled Ni/N–C catalytic CH4–CO2 reforming reaction mechanism diagram.
3.5.2. Mechanism of the CH4–CO2 reforming reaction. Based on the physicochemical properties of the catalysts, the nature of active species, and the observed product distribution, a reaction mechanism for CH4–CO2 reforming conditions is proposed (Fig. 12b).

In the plasma-alone system, energetic electrons collide with CH4 and CO2 molecules, generating reactive radicals such as image file: d5cy00936g-t26.tif (x = 1–3), H*, O*, and CO*. image file: d5cy00936g-t27.tif radicals may recombine to form C2H6, H* forms H2, and O* contributes to carbon oxidation into CO.79 However, due to the absence of catalytic control, radical utilization is inefficient, resulting in low selectivity for syngas and hydrocarbons, and significant carbon accumulation on surfaces.

The introduction of the N–C support significantly alters the plasma–catalyst interface. The abundant strong acid sites facilitate CH4 activation and dehydrogenation, increasing CH4 conversion and promoting C–C coupling reactions. Additionally, the mesoporous architecture of N–C enriches image file: d5cy00936g-t28.tif radicals within confined channels, enhancing their self-coupling into C2H6 while suppressing undesired routes such as image file: d5cy00936g-t29.tifimage file: d5cy00936g-t30.tif coupling that leads to C3H8. However, despite containing both strong acid and some basic sites, the CO2 conversion with N–C is only marginally higher than that of the plasma-alone system. This suggests that the basic sites in N–C are either insufficiently exposed or lack adequate strength to effectively adsorb and activate CO2 under plasma conditions. Some O* radicals generated from CO2 dissociation may still react with surface carbon to form CO, partially enhancing CO selectivity and mitigating coking.

The incorporation of Ni into N–C substantially enhances both CH4 and CO2 activation pathways. The surface of Ni/N–C is dominated by metallic Ni species, which efficiently dissociate CH4 into image file: d5cy00936g-t31.tif and H*, accelerating conversion. At the same time, unsaturated Ni centers generate moderate acid sites that stabilize image file: d5cy00936g-t32.tif intermediates, reducing over-dehydrogenation and suppressing carbon formation. These image file: d5cy00936g-t33.tif species are more likely to recombine into C2–C3 hydrocarbons, with image file: d5cy00936g-t34.tif self-coupling accounting for the high selectivity to C2H6 over C3H8. Some surface C2H6 may further dehydrogenate to yield C2H4. Importantly, the addition of Ni also introduces stronger and more abundant basic sites through the formation of finely dispersed oxidized Ni species. These basic sites significantly improve CO2 adsorption and activation, promoting the generation of reactive oxygen species (O*). These O* radicals contribute to multiple reaction steps: oxidizing carbon deposits to form CO, reacting with CH4 to produce OH*, and facilitating the formation of oxygenates such as CH3OH. Furthermore, lattice oxygen (O2−) associated with these oxygen-containing species can participate in redox cycles near metallic Ni centers, continuously converting image file: d5cy00936g-t35.tif and CO2 into CO and H2 while regenerating O2−. This dynamic oxygen cycle supports sustained syngas production and improves catalyst durability.

In summary, the cooperative interaction between metallic Ni and oxygen-containing species, together with a well-balanced distribution of acid–base functionalities, plays a pivotal role in enhancing CH4 and CO2 conversion, improving selectivity toward syngas and light hydrocarbons, and effectively inhibiting catalyst deactivation due to carbon deposition.

4. Conclusion

This study demonstrated the efficient reforming of CH4 and CO2 into syngas using a NTP-catalytic system with a Ni/N–C catalyst. Under the optimal reaction conditions, including a discharge power of 25 W, a total gas flow rate of 60 mL min−1, and a CH4/CO2 molar ratio of 1[thin space (1/6-em)]:[thin space (1/6-em)]5, the CH4 and CO2 conversions reached 44.1% and 20.0%, respectively. The corresponding selectivities for CO and H2 were 67.6% and 48.1%, and the energy efficiency reached 0.39 mmol kJ−1. Furthermore, the Ni/N–C catalyst maintained excellent stability during the prolonged 48 hour catalytic performance test. Catalyst characterization and performance results confirm that the mesoporous N–C support possesses a high specific surface area and a well-connected pore network, providing abundant sites for CH4/CO2 adsorption and activation while facilitating efficient mass transfer of reactive species to active Ni centers. Pyridinic nitrogen groups serve as robust anchoring sites that strengthen Ni–support interactions, effectively preventing nanoparticle agglomeration and maintaining uniform Ni dispersion. Metallic Ni species act as the key active centers for CH4 dissociation, while oxygen-containing Ni species introduce basic sites that promote CO2 adsorption and activation. Moreover, moderate acidity at Ni–N/C interfacial regions helps stabilize image file: d5cy00936g-t36.tif intermediates, suppressing over-dehydrogenation and favoring selective C–C coupling. The synergy between hierarchical porosity, N-doping, acid–base functionality, and plasma-generated reactive species enables efficient and selective CH4–CO2 conversion, providing valuable guidance for the rational design of next-generation plasma-catalytic systems.

Author contributions

Tian Chang: methodology, conceptualization, supervision, funding acquisition, project administration, writing – original draft, writing – review & editing. Zhao Yang: investigation, data curation, manuscript writing. Zuotong Zhao: investigation. Xuanchen Chang: writing – review & editing. Chuanyi Wang: writing – review & editing.

Conflicts of interest

There are no conflicts to declare.

Data availability

All data generated in this study are included in the article and its supplementary information (SI).

Supplementary information: characterization methods, discharge images, N2 adsorption–desorption and ICP-MS results, NH3-TPD and CO2-TPD analysis data. See DOI: https://doi.org/10.1039/d5cy00936g.

Acknowledgements

This work was financially supported by the National Natural Science Foundation of China (22208204), the China Postdoctoral Science Foundation (2022M722015), the State Key Laboratory of Electrical Insulation and Power Equipment (EIPE23213), the Foundation of State Key Laboratory of High-efficiency Utilization of Coal and Green Chemical Engineering (2022-K45), the Innovation Capability Support Program of Shaanxi (2024WZ-YBXM-18), the Postdoctoral Research Project of Shaanxi Province, and the Graduate Scientific Research Foundation of School of Environmental Science & Engineering, SUST.

References

  1. D. Welsby, J. Price, S. Pye and P. Ekins, Nature, 2021, 597, 230–234 CrossRef CAS PubMed .
  2. H. Adun, J. D. Ampah, O. Bamisile and Y. Hu, Sustain. Prod. Consum., 2024, 45, 386–407 CrossRef .
  3. R. P. Madruga, Science, 2021, 374, 511 CrossRef CAS .
  4. K. Arshad, N. Hussain, M. H. Ashraf and M. Z. Saleem, Sci. Total Environ., 2024, 928, 172370 CrossRef .
  5. H. Wang, G. Cui, H. Lu, Z. Li, L. Wang, H. Meng, J. Li, H. Yan, Y. Yang and M. Wei, Nat. Commun., 2024, 15, 3765 CrossRef CAS .
  6. S. Zhang, M. Ying, J. Yu, W. Zhan, L. Wang, Y. Guo and Y. Guo, Appl. Catal., B, 2021, 291, 120074 CrossRef CAS .
  7. E. Akbari, S. M. Alavi and M. Rezaei, J. CO2 Util., 2018, 24, 128–138 CrossRef CAS .
  8. B. Abdullah, N. A. Abd Ghani and D.-V. N. Vo, J. Cleaner Prod., 2017, 162, 170–185 CrossRef CAS .
  9. T. Gupta and H. Ayan, Appl. Sci., 2019, 9, 3548 CrossRef CAS .
  10. Y. Zhou, R. Chu, L. Fan, J. Zhao, W. Li, X. Jiang, X. Meng, Y. Li, S. Yu and Y. Wan, Sci. Total Environ., 2023, 866, 161453 CrossRef CAS PubMed .
  11. Y. Zhou, L. Zhu, B. Yang, L. Fan, X. Meng, R. Chu, X. Jiang, P. Li, W. Li and H. Chen, J. Hazard. Mater., 2024, 461, 132698 CrossRef CAS .
  12. Y. Wang, Y. Chen, J. Harding, H. He, A. Bogaerts and X. Tu, Chem. Eng. J., 2022, 450, 137860 CrossRef CAS .
  13. L. Wang, Y. Yi, C. Wu, H. Guo and X. Tu, Angew. Chem., Int. Ed., 2017, 56, 13679–13683 CrossRef CAS PubMed .
  14. S. Baig and B. Sajjadi, J. Energy Chem., 2024, 97, 265–301 CrossRef CAS .
  15. I. Yentekakis, P. Panagiotopoulou and G. Artemakis, Appl. Catal., B, 2021, 296, 120210 CrossRef CAS .
  16. D. He, S. Wu, X. Cao, D. Chen, L. Zhang, Y. Zhang and Y. Luo, Appl. Catal., B, 2024, 346, 123728 CrossRef CAS .
  17. O. V. Golubev, P. S. Il'chuk and A. L. Maximov, Pet. Chem., 2024, 64, 435–449 CrossRef CAS .
  18. Z. Wang, Z. Mei, L. Wang, Q. Wu, C. Xia, S. Li, T. Wang and C. Liu, J. Mater. Chem. A, 2024, 12, 24802–24838 RSC .
  19. D. Ray, P. Reddy and C. Subrahmanyam, Catal. Today, 2018, 309, 212–218 CrossRef CAS .
  20. J. Liu, J. Meng, C. Zou, X. Wang, C. Bu, J. Zhang, C. Liu, X. Cao, L. Liu and H. Xie, J. Energy Inst., 2025, 120, 102050 CrossRef CAS .
  21. A. Khoja, M. Tahir and N. Amin, Fuel Process. Technol., 2018, 178, 166–179 CrossRef CAS .
  22. T. Abbas, H. S. M. Yahya and N. A. S. Amin, Fuel Process. Technol., 2023, 248, 107836 CrossRef CAS .
  23. Y. Diao, H. Wang, B. Chen, X. Zhang and C. Shi, Appl. Catal., B, 2023, 330, 122573 CrossRef CAS .
  24. J. Xu, B. Yang, K. Chen, Q. Zhang, P. Xia, L. Jiang and F. Guo, Microporous Mesoporous Mater., 2024, 364, 112847 CrossRef CAS .
  25. W. Xu, M. Dong, L. Di and X. Zhang, Nanomaterials, 2019, 9, 1432 CrossRef CAS PubMed .
  26. B. An, Y. Ma, X. Han, M. Schröder and S. Yang, Acc. Mater. Res., 2024, 6, 77–88 CrossRef .
  27. Y. Guo, L. Feng, C. Wu, X. Wang and X. Zhang, J. Catal., 2020, 390, 213–223 CrossRef CAS .
  28. Y. Li, X. Cai, S. Chen, H. Zhang, K. H. L. Zhang, J. Hong, B. Chen, D. H. Kuo and W. Wang, ChemSusChem, 2018, 11, 1040–1047 CrossRef CAS PubMed .
  29. Q. Liang, W. Li, L. Xie, Y. He, B. Qiu, H. Zeng, S. Zhou, J. Zeng, T. Liu, M. Yan, K. Liang, O. Terasaki, L. Jiang and B. Kong, Nano Lett., 2022, 22, 2889–2897 CrossRef CAS PubMed .
  30. D. Mei, M. Sun, S. Liu, P. Zhang, Z. Fang and X. Tu, J. CO2 Util., 2023, 67, 102307 CrossRef CAS .
  31. D. Mei, G. Duan, J. Fu, S. Liu, R. Zhou, R. Zhou, Z. Fang, P. Cullen and K. Ostrikov, J. CO2 Util., 2021, 53, 101703 CrossRef CAS .
  32. Z. Tai, M. Shi, S. Chong, Y. Chen, C. Shu, X. Dai, Q. Tan and Y. Liu, J. Alloys Compd., 2019, 800, 1–7 CrossRef CAS .
  33. Y. Diao, H. Wang, B. Chen, L. Wang, X. Zhang and C. Shi, Fuel Process. Technol., 2023, 243, 107676 CrossRef CAS .
  34. R. Zhou, M. Mohamedali, Y. Ren, Q. Lu and N. Mahinpey, Appl. Catal., B, 2022, 316, 121696 CrossRef CAS .
  35. B. Singh, S. Samal, S. Nayak, S. Majhi, L. Besra and S. Bhattacharjee, Surf. Coat. Technol., 2011, 206, 1319–1326 CrossRef CAS .
  36. S. Dai, Z. Liu, B. Zhao, J. Zeng, H. Hu, Q. Zhang, D. Chen, C. Qu, D. Dang and M. Liu, J. Power Sources, 2018, 387, 43–48 CrossRef CAS .
  37. G. Varadwaj, O. Oyetade, S. Rana, B. Martincigh, S. Jonnalagadda and V. Nyamori, ACS Appl. Mater. Interfaces, 2017, 9, 17291–17306 CrossRef PubMed .
  38. S. Jafari, F. Ghorbani-Shahna, A. Bahrami and H. Kazemian, Appl. Sci., 2018, 8, 310 CrossRef .
  39. Z. ALOthman, Materials, 2012, 5, 2874–2902 CrossRef CAS .
  40. X. Cao, J. Xia, X. Meng, J. Xu, Q. Liu and Z. Wang, Adv. Funct. Mater., 2019, 29, 1902237 CrossRef .
  41. M. Hossain, M. Ahasan and R. Wang, Chem. Eng. J., 2024, 496, 154193 CrossRef .
  42. B. Hatamluyi, S. Sadeghzadeh, M. Rezayi and S. Sany, Sens. Actuators, B, 2023, 381, 133424 CrossRef CAS .
  43. J. Diao, T. Zhang, Z. Xu and G. Guo, Chem. Eng. J., 2023, 467, 143271 CrossRef CAS .
  44. O. Daoura, N. El Hassan, M. Boutros, S. Casale, P. Massiani and F. Launay, ACS Appl. Nano Mater., 2022, 5, 18048–18059 CrossRef CAS .
  45. Y. Diao, X. Zhang, Y. Liu, B. Chen, G. Wu and C. Shi, Appl. Catal., B, 2022, 301, 120779 CrossRef CAS .
  46. Y. Wang, L. Li, G. Li, Q. Zhao, X. s. Wu, Y. Wang, Y. Sun and C. Hu, ACS Catal., 2023, 13, 6486–6496 CrossRef CAS .
  47. N. Abdullah, N. Ainirazali, C. Chong, H. Razak, H. Setiabudi, A. Jalil and D. Vo, Int. J. Hydrogen Energy, 2020, 45, 18426–18439 CrossRef CAS .
  48. M. Yi, C. Zhang, C. Cao, C. Xu, B. Sa, D. Cai and H. Zhan, Inorg. Chem., 2019, 58, 3916–3924 CrossRef CAS .
  49. S. Liu, H. Yang, X. Huang, L. Liu, W. Cai, J. Gao, X. Li, T. Zhang, Y. Huang and B. Liu, Adv. Funct. Mater., 2018, 28, 1800499 CrossRef .
  50. T. Chang, T. Zhang, Y. Wang, A. Labidi, K. Leus, N. De Geyter, R. Morent and C. Wang, Chem. Eng. J., 2025, 520, 166113 CrossRef CAS .
  51. Y. Sun, G. Zhang, Y. Xu and R. Zhang, Int. J. Hydrogen Energy, 2019, 44, 16424–16435 CrossRef CAS .
  52. M. W. Dlamini, T. N. Phaahlamohlaka, D. O. Kumi, R. Forbes, L. L. Jewell and N. J. Coville, Catal. Today, 2020, 342, 99–110 CrossRef CAS .
  53. F. Ju, M. Wang, H. Luan, P. Du, Z. Tang and H. Ling, RSC Adv., 2018, 8, 33354–33360 RSC .
  54. Y. Chen, J. Li, W. Teng, W. Liu, S. Ren, J. Yang and Q. Liu, J. Environ. Chem. Eng., 2023, 11, 110787 CrossRef CAS .
  55. S. Zhang, Q. Cao, Y. Meng and D. Xia, Appl. Surf. Sci., 2025, 686, 162216 CrossRef CAS .
  56. L. Wang, L. Fan, Y. Wang, Q. Chen, Y. Zhu and Y. Yi, Appl. Catal., B, 2024, 350, 123938 CrossRef CAS .
  57. F. Al-Mubaddel, R. Kumar, M. Sofiu, F. Frusteri, A. Ibrahim, V. Srivastava, S. Kasim, A. Fakeeha, A. Abasaeed, A. Osman and A. Al-Fatesh, Int. J. Hydrogen Energy, 2021, 46, 14225–14235 CrossRef CAS .
  58. S. Zhang, X. Zhang, K. Wang, C. Li, Q. Ma, T. Zhao, X. Gao and J. Zhang, J. Environ. Chem. Eng., 2025, 13, 116334 CrossRef CAS .
  59. M. Zhang, Y. Gao, Y. Mao, W. Wang, J. Sun, Z. Song, J. Sun and X. Zhao, Chem. Eng. J., 2023, 451, 138616 CrossRef CAS .
  60. J. T. Li and S. Xia, Catal. Surv. Asia, 2024, 28, 269–282 CrossRef CAS .
  61. M. Jiang, X. Cao, D. Zhu, Y. Duan and J. Zhang, Electrochim. Acta, 2016, 196, 699–707 CrossRef CAS .
  62. J. Lu, J. Wu, Y. Jiang, P. Tan, L. Zhang, Y. Lei, X. Liu and L. Sun, Angew. Chem., Int. Ed., 2020, 59, 6428–6434 CrossRef CAS .
  63. D. Mei, X. Shen, S. Liu, R. Zhou, X. Yuan, Z. Rao, Y. Sun, Z. Fang, X. Du, Y. Zhou and X. Tu, Chem. Eng. J., 2023, 462, 142044 CrossRef CAS .
  64. B. Wanten, S. Maerivoet, C. Vantomme, J. Slaets, G. Trenchev and A. Bogaerts, J. CO2 Util., 2022, 56, 101869 CrossRef CAS .
  65. D. Mei, P. Zhang, G. Duan, S. Liu, Y. Zhou, Z. Fang and X. Tu, J. CO2 Util., 2022, 62, 102073 CrossRef CAS .
  66. J. Wang, Y. Fu, W. Kong, F. Jin, J. Bai, J. Zhang and Y. Sun, Appl. Catal., B, 2021, 282, 119546 CrossRef CAS .
  67. M. Hu, W. Deng, M. Zhu, Y. Su, L. Wang and G. Chen, Chem. Eng. J., 2024, 499, 156437 CrossRef CAS .
  68. S. Li, J. Sun, Y. Gorbanev, K. Van't Veer, B. Loenders, Y. Yi, T. Kenis, Q. Chen and A. Bogaerts, ACS Sustainable Chem. Eng., 2023, 11, 15373–15384 CrossRef CAS .
  69. C. Qi, Y. Bi, H. Yu, H. Zhang, Q. Zhang, X. Wang, M. Fan, T. Xing, M. Wang, M. Wu and W. Wu, Ind. Eng. Chem. Res., 2024, 63, 9576–9583 CrossRef CAS .
  70. P. Chawdhury, Y. Wang, D. Ray, S. Mathieu, N. Wang, J. Harding, F. Bin, X. Tu and C. Subrahmanyam, Appl. Catal., B, 2021, 284, 119735 CrossRef CAS .
  71. J. Li, L. Dou, Y. Gao, X. Hei, F. Yu and T. Shao, J. CO2 Util., 2021, 52, 101675 CrossRef CAS .
  72. J. Wang, K. Zhang, M. Mertens, A. Bogaerts and V. Meynen, Appl. Catal., B, 2023, 337, 122977 CrossRef CAS .
  73. A. Khoja, M. Tahir and N. Amin, Energy Fuels, 2019, 33, 11630–11647 CrossRef CAS .
  74. Y. Zeng, X. Zhu, D. Mei, B. Ashford and X. Tu, Catal. Today, 2015, 256, 80–87 CrossRef CAS .
  75. K. Zheng, X. Gao, Y. Xie, Z. He, Y. Ma, S. Hou, D. Su and X. Ma, J. Colloid Interface Sci., 2025, 683, 564–573 CrossRef CAS PubMed .
  76. Q. Lu, W. Lei, W. Yue, W. Huang, Y. Dong, W. Yan, Y. Liu, Y. Chen and Y. Zhao, Fuel, 2023, 344, 128041 CrossRef CAS .
  77. X. Wang, S. Xu, W. Yang, X. Fan, Q. Pan and H. Chen, Carbon Capture Sci. Technol., 2022, 5, 100067 CAS .
  78. P. Reyes, A. Gómez, J. Vergara, H. Martínez and C. Torres, Rev. Mex. Fis., 2017, 63, 363–371 CAS .
  79. T. Chang, X. Chang, Z. Zhao, C. Ma, X. Zhao, Y. Du, A. Patrocinio, A. Nikiforov and C. Wang, J. Environ. Chem. Eng., 2025, 13, 117074 CrossRef CAS .

This journal is © The Royal Society of Chemistry 2026
Click here to see how this site uses Cookies. View our privacy policy here.