Abstract
The electrochemical conversion of methane offers a sustainable alternative to traditional thermochemical syngas pathways; however, the rational design of catalysts that ensure high productivity remains a significant challenge. In this study, a high‐entropy oxide (HEO) catalyst composed of Co, Cr, Fe, Mn, and Ni is explored, with a targeted element enriched, and identify that a Co‐rich HEO demonstrates high efficiency in room‐temperature electrochemical methane conversion. This analysis of the projected density of states (PDOS) reveals that Co sites in the HEO catalyst possess an optimally positioned p‐band center for methane activation. The Co‐rich HEO catalyst achieves an ethanol production rate of 12315 µmol/gcat/hr at 1.6 VRHE, with a Faradaic efficiency of 63.5%; a flow cell electrolyzer equipped with this catalyst achieves continuous methane‐to‐ethanol conversion at a rate of 26533 µmol/gcat/hr over 100 h. Process modeling evaluates the economic and environmental implications, demonstrating that a commercially viable process can be realized through economies of scale while significantly reducing CO₂ emissions.
Keywords: Co enrichment, electrochemical methane conversion, ethanol production, high entropy oxide, process sustainability
A Co‐rich high‐entropy oxide (HEO) catalyst enables efficient electrochemical methane‐to‐ethanol conversion at room temperature. By leveraging elemental enrichment, the catalyst achieves high selectivity and stability, outperforming conventional systems. Process modeling further highlights its economic viability and significant potential for reducing carbon emissions.

1. Introduction
The valorization of methane into alcohols is becoming increasingly imperative for energy storage, fuel upgrading, and environmental mitigation.[ 1 ] Conventionally, the synthesis of alcohol from methane has been primarily achieved using an indirect route via syngas.[ 2 ] However, this traditional approach is both energy‐intensive and causes significant carbon emissions, as well as low efficiency in carbon utilization.[ 3 ] Consequently, efforts are increasingly focused on environmentally friendly and direct conversion methods.
Among these methods, liquid‐phase conversion emerges as a particularly promising approach, offering high‐selectivity partial oxidation under mild conditions.[ 4 ] This advantage arises from the stabilization of intermediates and the rapid extraction of oxygenates through solvation.[ 4 ] Electrochemical conversion, in particular, offers distinct benefits by enabling precise control over reaction kinetics and selectivity through the adjustment of applied potential.[ 5 ] Furthermore, the integration of electrochemical conversion with renewable energy sources amplifies its environmental benefits and overall sustainability.[ 4 , 6 ] Recently, Peng and colleagues utilized Fe‐Ni‐OH electrocatalysts to achieve the conversion of methane to ethanol, highlighting a high Faradaic efficiency of 87%.[ 7 ] Moon and colleagues demonstrated electrochemical methane conversion in tandem with silicon solar cells.[ 6b ] Despite the achievements of prior studies, the performance of electrocatalysts (e.g., TiO2/RuO2/V2O5, Rh/ZnO, NiO/Ni) in previous studies remains limited, with production rates ≈5000 µmol/gcat/hr or lower (Table S1, Supporting Information). Therefore, novel electrocatalysts with superior production rates are urgently needed to pursue commercial viability.
For high‐efficiency electrochemical methane conversion, we explore high‐entropy (HE) materials. HE materials are single‐phase solid solutions stabilized by high configurational entropy, consisting of at least five different transition metal cations.[ 8 ] These materials enable additional control over the electronic properties of catalytic active sites through synergistic interactions among different elements.[ 9 ] Furthermore, lattice distortion can create abundant defects and active sites on the surface, enhancing catalytic activity.[ 10 ] These characteristics make HE materials a promising approach for developing high‐performance catalysts, overcoming the limitations of conventional electrochemical catalysts, which typically contain only one or two metal cations. HE materials have already shown exceptional performance in water electrolysis and CO2 reduction.[ 11 ] For example, the FeCoPdIrPt alloy has achieved a hydrogen evolution reaction rate 26 times higher than that of commercial Pt.[ 12 ] However, their potential as catalysts for electrochemical methane activation remains unexplored.
In this study, we introduce HE oxides (HEOs) containing Co, Cr, Fe, Mn, and Ni. Transition metals like Ni, Co, and Fe have already been recognized for their activity in methane activation (Figure 1a).[ 13 ] Rather than using near‐equiatomic ratios of constituent elements as in conventional synthesis,[ 8 ] we prepare HEOs with compositions that feature targeted enrichment of a single cation. This strategy aims to achieve a high proportion of methane‐active elements while still benefiting from the synergistic effects of multiple components. Our findings show that Co‐rich HEOs are the most efficient for electrochemical methane conversion, as supported by projected density of states (PDOS) analysis of active oxygen adsorbed on the catalyst surface. By applying Co‐rich HEO catalysts in a flow cell electrolyzer, we achieve continuous methane‐to‐ethanol conversion with a remarkably high production rate of 26533 µmol/gcat/hr. To assess the economic and environmental implications of this continuous electrochemical conversion, we conducted a process analysis, demonstrating that our electrochemical process can achieve economic viability through economies of scale and features a very low Global Warming Potential (GWP) index.
Figure 1.

Characterization of HEO. a) Schematic of electrochemical methane‐to‐ethanol conversion on a HEO catalyst. b) SEM images of the HEO. c) TEM images of HEO and corresponding EDS mapping for each element. d) XRD pattern of HEO, with the XRD pattern of CoFe2O4 provided as a reference. e) FT, k2‐weighted EXAFS spectra from the Ni, Co, Fe, Mn, and Cr K‐edges pertaining to HEO.
2. Results and Discussion
2.1. Synthesis and Characterization of the (CoCrFeMnNi)3O4 Catalyst
We synthesize an HEO with the general formula (CoCrFeMnNi)3O4, which corresponds to using equimolar amounts of the selected precursors. Most of these transition metal elements —chosen for their similar atomic radii—have been utilized as catalysts for methane activation radii.[ 13 ] Specifically, the HEO is synthesized using a precursor mixture composed of Co(NO3)2, CrCl3, FeSO4, Mn(NO3)2, and Ni(NO3)2 through the sol‐gel method with calcination at 900 °C.[ 14 ] The HEO, demonstrating a spherical morphology, has a size of ≈50 ± 5 nm (Figure 1b). EDS elemental mapping images from TEM exhibit a homogeneous distribution of Cr, Mn, Fe, Co, and Ni elements within the particles (Figure 1c). The BET surface area of these particles is measured to be 54.5 m2 g−1 (Figure S1, Supporting Information).
Theoretically, HE materials stably form when the configurational entropy (Sconf , ) is at least 1.5R (Supplementary note #1).[ 15 ] The elemental composition of the HEO is analyzed via inductively coupled plasma atomic emission spectroscopy (ICP‐AES) (Table S2, Supporting Information); the Sconf for the HEO is quantified as 1.601R, satisfies the condition. The XRD pattern of the HEO exhibits a single‐phase cubic spinel structure, confirming that the HEO consists of only one Wyckoff site for the cations[ 16 ] (Figure 1d); this structure comprises two interpenetrating face‐centered cubic (FCC) lattices, with each cation occupying either tetrahedral or octahedral sites. The diffraction peaks correspond well to the planes of CoFe2O4.[ 10a ] The inset of the HR‐TEM image confirms the (220) planes of the cubic spinel with an interplanar spacing of 0.285 nm. Apart from these peaks, other peaks are not pronounced, indicating the absence of phase‐separated oxides in the HEO (Figure S2, Supporting Information).
Furthermore, we utilize the extended X‐ray absorption fine structure (EXAFS) technique to study the local structure of each element in the HEO (Figure 1e). The Fourier‐transformed (FT) k2‐weighted EXAFS spectra reveal two primary peaks that correspond to different coordination environments within the HEO structure. The peak observed in the range of ≈1.5–1.6 Å is attributed to metal–oxygen (M–O) bonds, whereas the peaks appearing at 2.5–3.3 Å correspond to metal–oxygen–metal (M–O–M) linkages, consistent with previously reported values.[ 17 ] These peaks are consistently observed at similar positions across all five metal elements, suggesting a uniform local environment for each cation. Notably, the M–O–M bond distance near 2.5 Å indicates that Ni, Co, Fe, Mn, and Cr primarily occupy octahedral sites, in agreement with the structural characteristics of spinel oxides.[ 18 ] This result confirms the formation of a single‐phase spinel‐structured HEO. A wavelet transform (WT)‐EXAFS analysis for each element exhibits similar peaks in both K and R spaces, which reaffirms the uniformity of the radius factor values across all elements (Figure S3, Supporting Information).[ 19 ] This analysis indicates that these elements occupy tetrahedral or octahedral sites without preference.
The surface chemical state of the HEO is analyzed using XPS (Figure S4, Supporting Information).[ 11a ] The Co 2p spectrum features main peaks at 780.1 and 796.2 eV, corresponding to Co 2p3/2 and Co 2p1/2, respectively, alongside satellite peaks at 785.4 and 802.9 eV. The Co 2p3/2 peak further deconvolves into peaks for Co2+ and Co3+, with the peak area ratio (Co2+/Co3+) calculated as 46.9/53.1.[ 20 ] Similarly, the Cr 2p spectrum shows deconvoluted peaks for Cr3+ and Cr6+; the Fe 2p spectrum shows deconvoluted peaks for Fe2+ and Fe3+; and the Mn 2p spectrum shows deconvoluted peaks for Mn3+ and Mn4+ in similar ratios.[ 21 ] These analyses indicate that the elements constituting the HEO exist in various oxidation states compared to those in single‐composition oxides.[ 20 , 21 ] These diverse oxidation states imply favorability toward Faradaic reactions.[ 22 ]
2.2. Identification of Active Sites and Synthesis of Co‐rich HEO Catalysts
We prepare HEOs with a targeted enrichment of one element (Supplementary note #2) and designate the samples as MX HEO (M = Co, Fe, Ni, Cr or Mn, X = the element with excess ratio). The configurational entropy (Sconf) for M60 HEO (M = Co, Fe, Ni, Cr, or Mn) is theoretically calculated to be 1.573R, which satisfies the 1.5R criterion based on experimental composition (Table S3, Supporting Information). By comparing these samples, we identify the element site with the highest activity for electrochemical methane conversion and determine the optimal HEO composition for this process.
The SEM image of Co60 HEO reveals particles similar in size to the HEO (Figure 2a). TEM/EDS images confirm that all transition metal elements are uniformly mixed in Co60 HEO (Figure 2b). TEM images of other HEO samples are provided in Figure S5 (Supporting Information). The XRD pattern for Co60 HEO matches that of the HEO, exhibiting a cubic spinel structure of CoFe2O4 (Figure 2c). EXAFS analysis shows consistent metal‐metal and metal‐oxygen bond lengths across all elements, indicating uniform occupancy of cation sites in the Co60 HEO lattice (Figure S6, Supporting Information).
Figure 2.

Characterization of composition‐controlled HEO and DFT calculations. a) SEM image, b) TEM images, and EDS mapping images of Co60 HEO. c) XRD pattern of Co60 HEO, with CoFe2O4 as the reference. d) LSV profiles (scan rate: 0.2 mV s−1) and e) Ethanol production rates for HEO catalysts with enriched Co, Fe, Ni, Cr, and Mn compositions. f) FE of ethanol and other oxygenates at the corresponding production rates for the same HEO catalysts. g) PDOS of the oxygen 2p‐band in HEO and Co3O4. h) Electron accumulation around adsorbed oxygen species on Co sites in Co60 HEO and Co3O4, with yellow indicating electron accumulation and blue representing depletion.
To evaluate the methane oxidation activity of M60 HEO (M = Co, Fe, Ni, Cr, or Mn) catalysts, we conduct anodic sweeps using M60 HEO‐coated electrodes, Pt counter electrodes, and an Ag/AgCl reference electrode in an electrolyte filled with methane. We include CO3 2− as an oxidizing agent in the electrolyte; CO3 2− provides active oxygen (O*) upon adsorption on the oxide catalyst (Figure S7, Supporting Information).[ 23 ] The current‐voltage profiles of M60 HEOs show an inflection point ≈1.7 VRHE (Figure 2d). A steep increase in current density above 1.7 VRHE is attributed to the oxygen evolution reaction (OER) occurring on the surface of the HEO catalysts. This increase indicates the onset of water oxidation, as confirmed by control experiments conducted in an electrolyte without methane, where M60 HEOs exhibit water splitting with an onset potential of ≈1.7 VRHE (Figures S8 and S9, Supporting Information). Below this potential, the measured current is attributed to methane oxidation, demonstrating that methane activation occurs at lower overpotentials, distinct from the OER. To validate this assignment, isotope‐labeling experiments with methane (13CH₄) and CO₃2⁻ were conducted, which confirmed the formation of liquid‐phase oxygenates such as ethanol and methanol in the electrolyte (Figure S10, Supporting Information).
We compare the current density of M60 HEO at 1.6 VRHE, where OER is not fully activated. Co60 HEO exhibits the highest current values, ≈2.7 times higher than that of Mn60 HEO (Figure S11, Supporting Information). This trend indicates that methane oxidation activity decreases in the order of Co60 HEO, Fe60 HEO, Ni60 HEO, Cr60 HEO, and Mn60 HEO. Ethanol production rates at 1.6 VRHE show a similar trend, with Co60 HEO achieving rates ≈2.1 times higher than Mn60 HEO (Figure 2e; Figure S11, Supporting Information). This correlation between current density and ethanol production confirms the exceptional activity of Co sites for electrochemical methane conversion. Figure 2f shows the Faradaic efficiency (FE) of ethanol (EtOH) and other oxygenates across M60 HEO catalysts, with Co60 HEO achieving the highest FE for ethanol at ≈63%. These results further validate the superior selectivity of Co60 HEO for ethanol production compared to Fe60, Ni60, Cr60, and Mn60 HEOs.
To rationalize the high activity of Co sites for methane oxidation, we analyze the projected density of states (PDOS) of oxygen adsorbed on each metal site. Considering that the activation of the methane C─H bond occurs directly at active oxygen sites, it is reasonable to consider the p‐band center (εp ) of active oxygen adsorbed on the catalyst surface.[ 24 ] Zhao and coworkers demonstrated that methane activation follows the Sabatier principle, with optimal p‐band centers near ‐0.9 eV for efficient C‐H bond activation.[ 24 ] The p‐band center of each element is determined using the following equation:[ 25 ]
| (1) |
where εp is p‐band center, Dp(E) is the density of states from p orbitals of the surface O atoms at a given energy E, the integral is taken for all occupied states.
The PDOS analysis (Figure 2g) reveals that the p‐band center values for active oxygen on Cr, Co, Ni, and Fe are ‐0.38, ‐0.85, ‐1.32, and ‐1.53 eV, respectively; The calculation for Mn was not included due to difficulties in obtaining a stabilized structure. These results confirm that Co sites in Co60 HEO, with a p‐band center of ‐0.85 eV, provide the most favorable conditions for methane activation.
Additionally, Co60 HEO demonstrates oxidation current values 3.2 times higher than those of Co₃O₄ and ethanol production rates 3 times higher (Figure S12, Supporting Information). The p‐band center for Co₃O₄ (‐1.4 eV) is less favorable than for Co60 HEO, highlighting the synergy provided by the high‐entropy configuration, which stabilizes multiple oxidation states. To further understand the superior catalytic performance of Co60 HEO compared to Co₃O₄, a charge density difference (CDD) analysis was conducted (Figure 2h). The isosurface plots from CDD analysis reveal significant electron accumulation around adsorbed oxygen species on Co sites in Co60 HEO, indicating strong covalent interactions between Co and oxygen. This strong interaction enhances methane activation. In contrast, Co₃O₄ shows weaker electron accumulation, consistent with its less favorable p‐band center (‐1.4 eV), which limits its catalytic efficiency. Bader charge analysis supports these findings, showing greater electron loss per Co atom in Co60 HEO (‐0.85 e⁻) compared to Co₃O₄ (‐0.62 e⁻). This enhanced charge donation in Co60 HEO can be attributed to its high‐entropy configuration, facilitating efficient electron transfer. Together, the CDD plots and Bader charge analysis provide a detailed mechanistic explanation for the superior catalytic activity of Co60 HEO in methane oxidation.
2.3. Productivity, Selectivity and Reaction Pathways in Co‐rich HEO catalysts
We compare the production rate of total liquid oxygenates/ethanol on Co60 HEO catalysts by varying the applied potential (Figure 3a). The production rate increases with the increase in potential, reaching a maximum at 1.6 VRHE; however, the rate decreases when the potential exceeds 1.6 VRHE. This decrease is attributed to the activation of OER; as OER oxidizes the O* on the catalyst to O2, the fast OER suppresses the methane oxidation reaction. We obtain the maximum production rates for oxygenates and ethanol at 1.6 VRHE, which are 18643 and 12153 µmol/gcat/hr, respectively. The Faradaic efficiency at this potential is 87.8% (Supplementary note #3).
Figure 3.

Electrochemical methane conversion and reaction pathways. a) Production rates of ethanol and total oxygenates at various anodic potentials. b) Selectivity of liquid oxygenates at different anodic potentials. c) Comparative plot of production rate versus primary product selectivity, comparing our results with previous studies on liquid‐phase methane conversion. d) Schematic representation of the proposed reaction mechanism from methane to alcohols on Co‐rich high entropy oxide catalysts.
The selectivity for liquid oxygenates is presented in Figure 3b. Ethanol is the primary product at all potential ranges. Notably, as the potential increases, the selectivity for methanol decreases, while the selectivity for C3 products, such as acetone and isopropyl alcohol, increases. At 1.6 VRHE, the selectivity for ethanol is 68%. We compare the selectivity versus the production rate of the primary product for the Co60 HEO catalyst with previous results (Figure 3c). Considering that selectivity and production rate are typically governed by a trade‐off,[ 26 ] our results exhibit a remarkably high ethanol production rate at relatively high selectivity.
The increase in selectivity for methanol, ethanol, and C3 products with increasing potential suggests a reaction pathway involving the sequential conversion from methanol to ethanol and then to C3 products. Based on this, we propose the following reaction mechanism (Figure 3d). The oxygen at the Co site of the HEO acts as the active site for methane oxidation. The active oxygen at the Co site, originating from carbonate‐derived adsorbed oxygen, facilitates methane oxidation, while the lattice oxygen mechanism is negligible due to the low reaction temperature (Figure S13, Supporting Information). Isotope‐labeling experiments using an H₂¹⁸O‐containing electrolyte further confirm that radicals generated from water splitting do not participate in the reaction (Figure S14, Supporting Information). (1) Methane is activated at this site through C─H bond activation to produce methanol (CH3OH) (Figure S10, Supporting Information). Subsequently, methanol can either desorb thermochemically or undergo electrochemical deprotonation. Since the selectivity of ethanol (CH3CH2OH) increases with increasing potential in the range of 1.4‐1.6 VRHE, the deprotonation of methanol may be thermodynamically more favorable than its desorption, leading to the formation of CH2OH. (2) Further deprotonation of CH2OH forms formaldehyde (CH2O), which can then couple with methane to form ethanol (CH3CH2OH). The increasing selectivity for C3 products with rising potential indicates that the electrochemical dehydrogenation of ethanol is occurring (Figure 3b). This dehydrogenation forms acetaldehyde (CH3CHO),[ 27 ] and its further dehydrogenation forms either CH3CO* or CH2CHO*. (3) The coupling of CH3CO* with methane forms acetone (CH3COCH3),[ 28 ] (4) while the coupling of CH2CHO* with methane results in isopropyl alcohol (CH3CHOHCH3).[ 29 ]
2.4. Continuous Conversion and Techno‐Economic Analysis through Process Modeling
For the practical application of electrochemical conversion, continuous operation is essential; this approach also significantly improves the mass transfer efficiency of methane compared to batch reactions.[ 4a ] We construct a continuous flow electrolyzer as shown in Figure 4a (see also Figure S15, Supporting Information), consisting of a methane flow plate, a gas diffusion layer (GDL) (Figure S16), a catalyst layer, an anion‐permeable separator, an electrolyte flow plate. During operation, as methane and the electrolyte flow on either side of the carbon fiber gas diffusion layer coated with the Co60 HEO catalyst, allowing methane to diffuse through the GDL into the electrolyte and immediately participate in the conversion reaction at the nearby catalyst (Figure 4b).
Figure 4.

Continuous electrochemical methane conversion. a) Schematic representation of a continuous flow cell with a Co60 HEO‐coated GDL serving as the electrode and b) the conversion reactions at the Co60 HEO catalyst surface. c) Ethanol production rate at different methane flow rates. d) Selectivity of various oxygenates at different methane flow rates. e) Methane conversion current during long‐term operation.
We controlled the methane flow rate, fixing the applied voltage at 1.5 VPt (this voltage corresponds ≈to 1.6 VRHE). Increasing the methane flow rate from 50 to 125 sccm results in a gradual increase in the production rate of ethanol (Figure 4c). The increase in methane flow rate raises the internal pressure of methane in the gas diffusion layer, which not only increases its solubility in the electrolyte but also appears to facilitate its transport to the electrolyte/catalyst interface.[ 30 ] The production rate of ethanol reaches a maximum of 26533 µmol/gcat/hr at 125 sccm. Notably, the production rate in the flow cell is approximately double that in the batch‐type reaction; this improvement is purely attributed to enhanced mass transport. The selectivity for ethanol at various flow rates is consistently analyzed at ≈60 ± 5% (Figure 4d), which is similar to the results observed earlier.
The long‐term operational stability of the continuous reaction is confirmed by monitoring the current density; the current density starts at ≈7 mA cm− 2 and decreases by only 5%, reaching 6.7 mA cm− 2 after 100 h (Figure 4e); The product profile over this reaction period is presented in Figure S17 (Supporting Information). This stability may be attributed to the durability of the catalyst and the catalyst‐coated electrode; after the reaction, the HEO retains its single‐phase crystallinity, and the surface chemical species analysis shows similar valence ratios for each transition metal compared to the pristine HEO (Figures S18 and S19, Supporting Information). Additionally, impedance analysis of the catalyst‐coated GDL shows only negligible changes in resistance (Figure S20, Supporting Information).
To present the process implications of our electrochemical methane conversion performance, we establish a rigorous process model and conduct a techno‐economic analysis (Supplementary Note #4). The process model includes the feed of methane and carbonate electrolytes to the electrolyzer, the separation and purification of liquid oxygenates, including ethanol, and the recycling and purging of residual methane gas. Specifically, indirect thermal integration, which recovers waste heat from combustors, is applied to minimize external energy requirements (Supplementary note #4, Figure A).
Here, we determine the minimum required selling price (MRSP) through a comprehensive techno‐economic evaluation (Figure 5a; Supplementary note #4, Table A‐E). The MRSP for ethanol in this process model is 7.514 USD kg−1, with a cost breakdown indicating significant contributions from electrolyzer costs and electricity expenses, making it capital‐intensive; this is similar to analyses of low‐temperature CO2 electrolysis.[ 31 ] This MRSP is higher than the market price of 0.697 USD kg−1.[ 32 ] Sensitivity analysis shows that a 20% and 40% reduction in electrolyzer costs could lower the MRSP to 4.812 and 2.11 USD kg−1, respectively. This scenario is reliably achievable through the attainment of economies of scale for the electrolyzer. Another factor we consider is the production cost of green electricity, which can vary based on the country and technological advancements.[ 33 ] Sensitivity analysis indicates that adjusting green electricity costs by ‐20% and ‐40% reduces the MRSP by 62.7% and 89.5%, achieving MRSPs of 2.802 and 0.792 USD kg−1, respectively. Considering these capital costs, economic parity for the MRSP of ethanol can be achieved with a 25% reduction in electrolyzer costs combined with a 46.5% reduction in green electricity costs. Alternatively, improving the electrolyzer can be considered. Enhancing current density can be achieved through various design improvements in the electrolyzer cell (e.g., flow path optimization, zero‐gap implementation).[ 34 ] Based on a 25% cost reduction in both electrolyzer and green electricity costs, an ≈5% improvement in the current density of the electrolyzer can align the MRSP with the market price. (Supplementary note #4, Figure B).
Figure 5.

Techno‐economic and environmental evaluation of ethanol production. a) MRSP breakdown for ethanol production under various scenarios. Sensitivity analysis shows significant reductions in MRSP through decreases in electrolyzer and electricity costs or improved current density, achieving parity with the market price (0.697 USD kg−1). b) Comparison of the GWP for the electrochemical process (0.213 kg CO2eq/kg ethanol) with bioethanol (1.15 kg CO2eq/kg) and petrochemical ethanol (1.93 kg CO2eq/kg), highlighting the environmental benefits of the electrochemical approach.
To assess potential environmental impacts, a gate‐to‐gate life cycle impact assessment (LCIA) was conducted (Supplementary Note #4, Table F). The environmental sustainability of the electrochemical process was measured using the global warming potential (GWP) in CO2 equivalents (CO2eq).[ 35 ] Our process was compared to commercial ethanol production methods, specifically bioethanol produced through biomass fermentation and petrochemical‐based ethanol from the hydration of ethylene.[ 36 ] While the GWP of our electrochemical conversion process is 0.213, the commercial processes have GWPs of 1.15 for bio‐based ethanol and 1.93 for petrochemical‐based ethanol, respectively (Figure 5b). Thus, the GWP of our electrochemical process is only 10–20% of the GWP of commercial ethanol synthesis processes. This result highlights that the electrochemical conversion process offers a substantial reduction in carbon footprint compared to traditional methods.
3. Conclusion
The electrochemical conversion of methane into oxygenates is a promising strategy for addressing global energy demands and environmental challenges. In this study, we introduce a novel class of high‐entropy oxides (HEOs) with targeted elemental enrichment, which distinguishes our approach from conventional HEOs synthesized with near‐equiatomic compositions. By enriching cobalt within the HEO matrix, we leverage the dual benefits of high configurational entropy and element‐specific activity. This approach not only enhances the catalytic performance of cobalt but also preserves the synergistic interactions among multiple transition metals. Our Co‐rich HEO (Co60 HEO) exhibits exceptional catalytic performance, achieving an ethanol production rate of 12315 µmol/gcat/hr with a selectivity of 68% at 1.6 VRHE. These results significantly surpass those of conventional catalysts and equiatomic HEOs. DFT calculations reveal that cobalt, in the high‐entropy environment, forms highly active oxygen species due to the unique stabilization of multiple oxidation states and enhanced electron transfer capabilities. This highlights the distinctive advantage of enriching methane‐active elements within a high‐entropy matrix, offering a new paradigm for catalyst design.
The practical potential of Co60 HEO is demonstrated through its integration into a continuous flow electrolyzer with a catalyst‐coated gas diffusion layer. This design achieves a record ethanol production rate of 26533 µmol/gcat/hr, supported by enhanced mass transport and sustained operational stability over long‐term testing. The structural and chemical integrity of Co60 HEO is maintained throughout, underscoring its robustness and scalability for industrial applications. A comprehensive techno‐economic analysis reveals that targeted cost reductions in electrolyzer components and electricity prices can make this process economically competitive. Furthermore, environmental impact assessments show that the electrochemical methane‐to‐ethanol process reduces global warming potential (GWP) by 80–90% compared to traditional ethanol production methods, aligning with sustainability goals. Our approach not only advances the field of catalysis but also offers a viable process for utilizing methane, an abundant yet underexploited resource, to produce value‐added chemicals and fuels.
4. Experimental Section
Preparation of the ((CoCrFeMnNi)3O4)HEO Catalyst
Spherical mesoporous HEOs were synthesized via a sol‐gel method. The synthesis with standard quantities is as follows: 2.78×10−4 m of F‐127 was dissolved in a mixture of water (46 mL) and ethanol (8 mL). Then, ammonia solution (0.5 mL) was added. After 30 min, 0.38 mL of formaldehyde solution (37‐40 wt.%) was added. After stirring for 24 hr, 2.96×10−4 m of a metal precursor solution containing Co(NO3)26H2O, CrCl36H2O, FeSO47H2O, Mn(NO3)26H2O, and Ni(NO3)26H2O (0.02 g) was added. After further stirring for 12 hr, the products underwent hydrothermal treatment at 100 °C for 12 hr. The samples, denoted as Ni‐Co‐Cr‐Fe‐Mn‐TF (TF refers to tannin‐formaldehyde resin), were washed and dried repeatedly. Spherical mesoporous HEOs were prepared by calcination of Ni‐Co‐Cr‐Fe‐Mn‐TF in air 900 °C.[ 14 ]
Analysis of Electrochemical Methane Conversion
Linear sweep voltammetry (LSV) measurements were conducted using a potentiostat (Versastat Ametek) at a scan rate of 0.02 V s−1. The LSV was performed using a three‐electrode setup, with the working electrode being a carbon substrate coated with the HEO catalyst (typically with an area of 1 × 1 cm2). The electrolyte used was 0.5 m Na2CO3. Methane saturation in the electrolyte was achieved by bubbling methane through a microsparger at 25 °C for 30 min. The electrochemical methane conversion was carried out by immersing the HEO catalyst electrode, a Pt counter electrode, and an RHE reference electrode in a gas‐tight reactor containing the methane‐saturated electrolyte, maintained at 25 °C.
Analysis of the Product
Gas chromatography‐mass spectrometry (GC‐MS) analyses were performed using a GC‐MS system (7890B‐5977A, Agilent Technologies, USA) equipped with a mass selective detector MSD 5975 (electron impact ionization, EI, 70 eV, Agilent Technologies). A fused‐silica capillary column (DB‐WAX, 0.25 µm thick poly(ethyleneglycol) coating, Agilent Technologies, USA) was used. Samples were introduced by headspace sampling (1000 µl of a sample heated at 70 °C for 30 min); the injection temperature was set to 250 °C. Helium (99.999%) was used as the carrier gas at a flow rate of 1 mL min−1, with a split ratio of 8:1. The oven temperature program was as follows: hold at 40 °C for 5 min, ramp at 4 °C min−1 to 100 °C, then ramp at 20 °C min−1 to 240 °C, and hold for 3 min.
Analysis Using Isotopes
The reaction was conducted using 13CH4 (Sigma‐Aldrich, 99%, 99 atom% 13C) in a D2O‐based electrolyte. To synthesize the ¹⁸O‐labeled carbonate, 200 µL of [¹⁸O] water (9.1 mmol, 98% ¹⁸O) was first reacted with 5 mL of tetraethyl orthocarbonate (23.8 mmol) and 1.5 mg of dehydrated toluenesulfonic acid. After allowing the reaction to proceed for a few min, a solution of 500 mm sodium methoxide in dry methanol (30 mL, 15 mmol) along with 350 µL of [¹⁸O] water (15.9 mmol) was added. Following the reaction at 80–85 °C for 30 h, the solvent was evaporated using a rotary evaporator, leading to the precipitation of ¹⁸O‐labeled sodium carbonate. The liquid product containing isotopes was analyzed using nuclear magnetic resonance (NMR) spectroscopy (Avance III HD 400 FT‐NMR instrument, Bruker Biospin). The proton high power decoupling field strength was 11.7 (5.0 µs length 90° 1H pulse); the contact time was 4 ms at the Hartmann‐Hahn matching condition of 50 kHz, and the scan delay time was 3 s. The 13C chemical shifts were determined with an accuracy of ±0.5 ppm. Tetramethylsilane (TMS) was used as a standard, and calibration was performed with the residual signal of 3‐(trimethylsilyl)‐1‐propane sulfonic acid sodium salt (DSS) at δ = 0.0 ppm.
Characterization
Scanning electron microscopy (SEM) images were obtained using a JSM‐7800F microscope (JEOL). Transmission electron microscopy (TEM) was performed with a JEM‐ARM200F microscope (JEOL), which is equipped with a spherical aberration corrector in the condenser lens (probe corrector). High‐angle annular dark field‐scanning TEM (HAADF‐STEM) was also conducted using the JEM‐ARM200F microscope at an acceleration voltage of 200 kV. Energy‐dispersive X‐ray spectroscopy (EDS) mapping was carried out with an Oxford Instruments X‐Max SDD. X‐ray diffraction (XRD) patterns were recorded using a Rigaku Miniflex‐2005G303 diffractometer with Cu Kα radiation at 20 kV and 10 mA, covering a 2θ range of 25–65°. X‐ray photoelectron spectroscopy (XPS) analysis was conducted using a Leybold spectrometer with an Al Kα monochromatic source. X‐ray absorption fine structure (XAFS) measurements were performed at the 7D XAFS beamline of the Pohang Light Source (PLS‐II) in the 3.0 GeV storage ring, aiming to probe the valence state and coordination of iron species. Spectra were collected in fluorescence mode and processed with Demeter software. Extended X‐ray absorption fine structure (EXAFS) spectra fitting was conducted using Artemis software in the k‐space range of 3–14 Å. Gas chromatography‐mass spectrometry (GC‐MS) analyses were performed using an Agilent Technologies 7890B‐5977A GC‐MS system, equipped with a mass selective detector (MSD 5975, electron impact ionization, EI, 70 eV, Agilent Technologies). A fused‐silica capillary column (DB‐WAX, 0.5 µm thick poly(ethyleneglycol) coating, Agilent Technologies) was used. Samples were injected at 250 °C. Helium was used as the carrier gas at a flow rate of 1 mL min−1 with a split ratio of 10:1. The oven temperature program was set as follows: hold at 40 °C for 5 min, ramp at 4 °C min−1 to 100 °C, then ramp at 20 °C min−1 to 240 °C, and hold for 3 min. The crystal structure is visualized using VESTA.[ 37 ]
DFT Calculation
All calculations were conducted using the Quantum ESPRESSO package, which is based on density functional theory. The projector augmented wave (PAW) method and the Generalized Gradient Approximation (GGA) with the Perdew–Burke–Ernzerhof (PBE) exchange‐correlation function were utilized. A plane‐wave basis set with a cutoff energy of 95 Ry was employed. A periodic supercell containing 4 Mn, 5 Cr, 5 Fe, 5 Co, 5 Ni, and 32 O atoms was used to construct the slab models for HEOs (Supplementary Note #5). The vacuum spacing was set to 15 Å along the z‐axis to prevent interactions between neighboring slabs. The k‐point mesh of (4 × 3 × 1) was selected according to the Monkhorst‐Pack scheme to perform Brillouin zone integration. For structure optimization, all ions were relaxed until the maximum force on each ion was less than 0.005 eV Å−1. The charge density difference (CDD) was calculated to visualize electron redistribution upon oxygen adsorption, with isosurfaces generated at a cutoff value of 0.007 e/bohr3. Bader charge analysis was performed to quantify the electron transfer at Co sites, using zero‐flux partitioning of the charge density.[ 38 ]
Conflict of Interest
The authors declare no conflict of interest.
Supporting information
Supporting Information
Acknowledgements
H.M., C.K. and S.‐Y.L. contributed equally to this work. J.H.M. acknowledges support from the National Research Foundation of Korea (2024‐00466477, 2025 ‐ 00559443) and the Pohang Accelerator Laboratory. B.‐Y.Y. acknowledges support from the National Science and Technology Council of R.O.C. (NSTC 113‐2218‐E‐002‐027).
Min H., Kim C., Lin S.‐Y., Choi J., Sim Y., Yu B.‐Y., Moon J. H., Co‐Enriched High Entropy Oxides for Efficient Continuous Electrochemical Methane Conversion: Catalytic Performance and Sustainability Insights. Adv. Mater. 2025, 37, 2418767. 10.1002/adma.202418767
Contributor Information
Bor‐Yih Yu, Email: bor-yihyu@ntu.edu.tw.
Jun Hyuk Moon, Email: junhyukmoon@korea.ac.kr.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
References
- 1.a) Xie J., Jin R., Li A., Bi Y., Ruan Q., Deng Y., Zhang Y., Yao S., Sankar G., Ma D., Tang J., Nat. Catal. 2018, 1, 889; [Google Scholar]; b) Sushkevich V. L., Palagin D., Ranocchiari M., van Bokhoven J. A., Science 2017, 356, 523. [DOI] [PubMed] [Google Scholar]
- 2. Ismagilov Z. R., Matus E. V., Tsikoza L. T., Energy Environ. Sci. 2008, 1, 526. [Google Scholar]
- 3.a) Mao J., Liu H., Cui X., Zhang Y., Meng X., Zheng Y., Chen M., Pan Y., Zhao Z., Hou G., Hu J., Li Y., Xu G., Huang R., Yu L., Deng D., Nat. Catal. 2023, 6, 1052; [Google Scholar]; b) Upham D. C., Agarwal V., Khechfe A., Snodgrass Z. R., Gordon M. J., Metiu H., McFarland E. W., Science 2017, 358, 917; [DOI] [PubMed] [Google Scholar]; c) Song Y., Ozdemir E., Ramesh S., Adishev A., Subramanian S., Harale A., Albuali M., Fadhel B. A., Jamal A., Moon D., Choi S. H., Yavuz C. T., Science 2020, 367, 777. [DOI] [PubMed] [Google Scholar]
- 4.a) Kim C., Min H., Kim J., Moon J. H., Energy Environ. Sci. 2023, 16, 3158; [Google Scholar]; b) Latimer A. A., Kakekhani A., Kulkarni A. R., Nørskov J. K., ACS Catal. 2018, 8, 6894. [Google Scholar]
- 5.a) Jang J., Shen K., Morales‐Guio C. G., Joule 2019, 3, 2589; [Google Scholar]; b) Wang H., Chen J., Lin Y., Wang X., Li J., Li Y., Gao L., Zhang L., Chao D., Xiao X., Lee J.‐M., Adv. Mater. 2021, 33, 2008422. [DOI] [PubMed] [Google Scholar]
- 6.a) Albo J., Alvarez‐Guerra M., Castaño P., Irabien A., Green Chem. 2015, 17, 2304; [Google Scholar]; b) Lee J., Yang J., Moon J. H., ACS Energy Lett. 2021, 6, 893. [Google Scholar]
- 7. Li J., Yao L., Wu D., King J., Chuang S. S. C., Liu B., Peng Z., Appl. Catal. B: Environ. 2022, 316, 121657. [Google Scholar]
- 8.a) Yao Y., Dong Q., Brozena A., Luo J., Miao J., Chi M., Wang C., Kevrekidis I. G., Ren Z. J., Greeley J., Wang G., Anapolsky A., Hu L., Science 2022, 376, eabn3103; [DOI] [PubMed] [Google Scholar]; b) Glasscott M. W., Pendergast A. D., Goines S., Bishop A. R., Hoang A. T., Renault C., Dick J. E., Nat. Commun. 2019, 10, 2650; [DOI] [PMC free article] [PubMed] [Google Scholar]; c) Zhu H., Sun S., Hao J., Zhuang Z., Zhang S., Wang T., Kang Q., Lu S., Wang X., Lai F., Liu T., Gao G., Du M., Wang D., Energy Environ. Sci. 2023, 16, 619. [Google Scholar]
- 9.a) George E. P., Raabe D., Ritchie R. O., Nat. Rev. Mater. 2019, 4, 515; [Google Scholar]; b) Song B., Yang Y., Rabbani M., Yang T. T., He K., Hu X., Yuan Y., Ghildiyal P., Dravid V. P., Zachariah M. R., Saidi W. A., Liu Y., Shahbazian‐Yassar R., ACS Nano 2020, 14, 15131. [DOI] [PubMed] [Google Scholar]
- 10.a) Nguyen T. X., Patra J., Chang J.‐K., Ting J.‐M., J. Mater. Chem. A 2020, 8, 18963; [Google Scholar]; b) Wang D., Jiang S., Duan C., Mao J., Dong Y., Dong K., Wang Z., Luo S., Liu Y., Qi X., J. Alloys Compd. 2020, 844, 156158; [Google Scholar]; c) Wang Y., Mi J., Wu Z.‐S., Chem Catalysis 2022, 2, 1624. [Google Scholar]
- 11.a) Nguyen T. X., Liao Y.‐C., Lin C.‐C., Su Y.‐H., Ting J.‐M., Adv. Funct. Mater. 2021, 31, 2101632; [Google Scholar]; b) Mori K., Hashimoto N., Kamiuchi N., Yoshida H., Kobayashi H., Yamashita H., Nat. Commun. 2021, 12, 3884. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Gao S., Hao S., Huang Z., Yuan Y., Han S., Lei L., Zhang X., Shahbazian‐Yassar R., Lu J., Nat. Commun. 2020, 11, 2016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.a) Dummer N. F., Willock D. J., He Q., Howard M. J., Lewis R. J., Qi G., Taylor S. H., Xu J., Bethell D., Kiely C. J., Hutchings G. J., Chem. Rev. 2023, 123, 6359; [DOI] [PMC free article] [PubMed] [Google Scholar]; b) Fan W. K., Tahir M., J. Environ. Chem. Eng. 2021, 9, 105460; [Google Scholar]; c) Xie S., Liu Y., Deng J., Zhao X., Yang J., Zhang K., Han Z., Arandiyan H., Dai H., Appl. Catal. B: Environ. 2017, 206, 221; [Google Scholar]; d) Xu X., Faglioni F., Goddard W. A., J. Phys. Chem. A. 2002, 106, 7171. [Google Scholar]
- 14. Wang G., Qin J., Feng Y., Feng B., Yang S., Wang Z., Zhao Y., Wei J., ACS Appl. Mater. Interfaces 2020, 12, 45155. [DOI] [PubMed] [Google Scholar]
- 15. Sarkar A., Wang Q., Schiele A., Chellali M. R., Bhattacharya S. S., Wang D., Brezesinski T., Hahn H., Velasco L., Breitung B., Adv. Mater. 2019, 31, 1806236. [DOI] [PubMed] [Google Scholar]
- 16. Tomboc G. M., Zhang X., Choi S., Kim D., Lee L. Y. S., Lee K., Adv. Funct. Mater. 2022, 32, 2205142. [Google Scholar]
- 17. Iwase K., Honma I., ACS Appl. Energ. Mater. 2022, 5, 9292. [Google Scholar]
- 18. Wang J., Sun S., Xi S., Sun Y., Ong S. J. H., Seh Z. W., Xu Z. J., J. Phys. Chem. C 2024, 128, 4978. [Google Scholar]
- 19. Liu Y., Wu D., Yu F., Yang R., Zhang H., Sun F., Zhong L., Jiang Z., Phys. Chem. Chem. Phys. 2019, 21, 10791. [DOI] [PubMed] [Google Scholar]
- 20. Menezes P. W., Indra A., Gutkin V., Driess M., Chem. Commun. 2017, 53, 8018. [DOI] [PubMed] [Google Scholar]
- 21.a) Allen G. C., Harris S. J., Jutson J. A., Dyke J. M., Appl. Surf. Sci. 1989, 37, 111; [Google Scholar]; b) Zheng X., Zhang Y., Liu H., Fu D., Chen J., Wang J., Zhong C., Deng Y., Han X., Hu W., Small 2018, 14, 1803666; [DOI] [PubMed] [Google Scholar]; c) Langell M. A., Hutchings C. W., Carson G. A., Nassir M. H., J. Vac. Sci. Technol. A 1996, 14, 1656. [Google Scholar]
- 22. Raveendran A., Chandran M., Dhanusuraman R., RCS Adv. 2023, 13, 3843. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Kim C., Min H., Kim J., Sul J., Yang J., Moon J. H., Appl. Catal. B: Environ. 2023, 323, 122129. [Google Scholar]
- 24. Kang Y., Li Z., Lv X., Song W., Wei Y., Zhang X., Liu J., Zhao Z., J. Catal. 2021, 393, 20. [Google Scholar]
- 25. Nørskov J. K., Bligaard T., Rossmeisl J., Christensen C. H., Nat. Chem. 2009, 1, 37. [DOI] [PubMed] [Google Scholar]
- 26. Kumar N., Mukherjee S., Harvey‐Reid N. C., Bezrukov A. A., Tan K., Martins V., Vandichel M., Pham T., van Wyk L. M., Oyekan K., Kumar A., Forrest K. A., Patil K. M., Barbour L. J., Space B., Huang Y., Kruger P. E., Zaworotko M. J., Chem 2021, 7, 3085. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Ob‐eye J., Praserthdam P., Jongsomjit B., Catalysts 2019, 9, 66. [Google Scholar]
- 28. Lee J., Lee S., Kim C., Yoo J. S., Moon J. H., Appl. Catal. B‐Environ. Energy 2024, 344, 123633. [Google Scholar]
- 29. Xu N., Coco C. A., Wang Y., Su T., Wang Y., Peng L., Zhang Y., Liu Y., Qiao J., Zhou X.‐D., Appl. Catal. B: Environ. 2021, 282, 119572. [Google Scholar]
- 30. Xing Z., Hu L., Ripatti D. S., Hu X., Feng X., Nat. Commun. 2021, 12, 136. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Shin H., Hansen K. U., Jiao F., Nat. Sustain. 2021, 4, 911. [Google Scholar]
- 32.a) ChemAnalyst, Ethanol Price Trend and Forecast, https://www.chemanalyst.com/Pricing‐data/ethanol‐13 (accessed: April 2024);; b) Akbari M., Oyedun A. O., Jain S., Kumar A., Sustain. Energy Technol. Assess. 2018, 26, 83. [Google Scholar]
- 33. International Renewable Energy Agency, Renewable capacity statistics 2022, https://www.irena.org/publications/2022/Apr/Renewable‐Capacity‐Statistics‐2022 (accessed: April 2022).
- 34.a) Lee W. H., Kim K., Lim C., Ko Y.‐J., Hwang Y. J., Min B. K., Lee U., Oh H.‐S., J. Mater. Chem. A 2021, 9, 16169; [Google Scholar]; b) Dinh C.‐T., Burdyny T., Kibria M. G., Seifitokaldani A., Gabardo C. M., García de Arquer F. P., Kiani A., Edwards J. P., De Luna P., Bushuyev O. S., Zou C., Quintero‐Bermudez R., Pang Y., Sinton D., Sargent E. H., Science 2018, 360, 783; [DOI] [PubMed] [Google Scholar]; c) Kumaravel V., Bartlett J., Pillai S. C., ACS Energy Lett. 2020, 5, 486. [Google Scholar]
- 35. Sreekumar A., Shastri Y., Wadekar P., Patil M., Lali A., Clean Technol. Environ. Policy 2020, 22, 409. [Google Scholar]
- 36.a) DemİRbaŞ A., Energy Sources 2005, 27, 327; [Google Scholar]; b) Duque A., Álvarez C., Doménech P., Manzanares P., Moreno A. D., Processes 2021, 9, 206; [Google Scholar]; c) Restrepo‐Flórez J. M., Maravelias C. T., Energy Environ. Sci. 2021, 14, 493. [Google Scholar]
- 37. Momma K., Izumi F., J. Appl. Crystallogr. 2011, 44, 1272. [Google Scholar]
- 38. Tang W., Sanville E., Henkelman G., J. Phys. Condens. Matter 2009, 21, 084204. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting Information
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
