Organometallic complexes with electron rich metal centers promise efficient and selective conversion of methane to methanol: proof of principle computational study

The efficient and simultaneously selective conversion of methane to methanol has been one of the most research-intensive topics in catalysis over the past decades. The weaker C-H bond of methanol promotes the production of over-oxidized species. The present computational study examines the catalytic performance of organometallic complexes with electron rich Earth abundant metals (cobalt, nickel, copper, formally negatively charged). A deliberately designed ligand is proposed to secure the negative charge on the metal and enable the formation of stable terminal metal-oxygen bonds. The ligand coordinates the metal with metal-carbon bonds, and the skeleton of the ligand is chosen to constrain the motion of the coordinated carbon atoms, avoiding the insertion of oxygen to the metal-carbon bond. We found that the energy barriers for methane activation are less than 15 kcal/mol across all three metals, and that the turnover frequency is determined by the methanol-release step, which is highly temperature-sensitive. Therefore, solvent effects and temperature can be tuned to improve the overall catalytic efficiency. The most impressive result of our study is that the activation barriers for methane and methanol are competitive (within 1–2 kcal/mol). This observation makes catalysts with electron rich metal centers unique and promising for efficient and selective conversion of methane to methanol.

Industrial methanol production primarily depends on the indirect syngas process, where methane is reformed into synthesis gas (CO/H 2) (Grabow and Mavrikakis, 2011; Szanyi and Goodman, 1991) and then hydrogenated over Cu/ZnO/Al 2 O 3 catalysts (Szanyi and Goodman, 1991; Dummer et al., 2023; Klier, 1982). Although this method is industrially optimized, it requires temperatures above 800 °C for methane reforming, consumes a lot of energy, and involves significant infrastructure costs (Alvarez-Galvan et al., 2011; Lunsford, 2000). Increasing environmental concerns and the demand for easily transportable methanol have sparked interest in direct methane-to-methanol (MTM) conversion.

A direct, one-step oxidation of methane under mild conditions would represent a transformative technological advance. Such a process could eliminate the energy penalties associated with syngas production, enable modular on-site conversion of natural gas, and drastically reduce methane flaring and emissions (Agarwal et al., 2017; Claveau et al., 2023a). Despite its conceptual simplicity, direct MTM conversion remains one of the most challenging reactions in catalysis (Alvarez-Galvan et al., 2011; Agarwal et al., 2017; Latimer et al., 2018). Methane is among the least reactive hydrocarbons due to its strong C–H bond dissociation enthalpy (∼105 kcal/mol) (Ruscic, 2015; Bi et al., 2022). The molecule exhibits minimal polarizability and lacks functional groups capable of interacting strongly with catalytic surfaces or molecular complexes. Consequently, activating the first C–H bond requires a catalyst which is capable of donating electron density into the antibonding C-H orbitals, or accepting electron density from the bonding orbitals of methane (Claveau et al., 2023a). Overcoming this barrier without simultaneously compromising selectivity remains a central challenge.

In striking contrast, the C–H bond in methanol is 9 kcal/mol weaker (∼96 kcal/mol) (Latimer et al., 2018; Ruscic, 2015), which makes methanol more reactive under oxidative conditions. Numerous kinetic studies demonstrate that the activation barrier for methanol is consistently lower than that for methane, regardless of whether molecular, heterogeneous, or photochemical catalysts are employed (Dummer et al., 2023; Claveau et al., 2023b). As a result, methanol, once formed, is prone to further oxidation to formaldehyde, formic acid, CO, or CO 2. This intrinsic selectivity challenge: the difficulty in activating methane and ease of oxidizing methanol, is the principal bottleneck limiting the advancement of MTM catalysis.

Another layer of complexity involves product inhibition, where methanol binds strongly to active catalytic centers or forms metal-bound methoxy species (Li et al., 2023), blocking subsequent methane activation. In heterogeneous systems, this often leads to coke formation or irreversible surface oxidation (Dummer et al., 2023; Parfenov et al., 2014; Chen et al., 2014). For molecular systems, strong methanol coordination can hinder catalyst turnover, necessitating strategies that promote rapid product desorption (Latimer et al., 2018; Harkou et al., 2025; Periana et al., 1998).

Traditional methane oxidation catalysts electron-poor metal ions (e.g., high-valent Cu, Fe, or Pd), which interact with methane through electrophilic pathways (Latimer et al., 2018; Ravi et al., 2017). However, this often results in tight binding of oxygenated products and subsequent overoxidation. The limitations of conventional electrophilic catalysts have instigated the exploration of alternative electronic systems, such as catalysts with electron-rich metals (Androutsopoulos et al., 2024). To our knowledge, only bare electron-rich metals (Pd −, Pt −, Cu −, Co −) generated via gas-phase techniques, such as laser ablation, (Chiba et al., 2025; Liu et al., 2019a; Liu et al., 2019b), have been used for methane activation. While invaluable for mechanistic studies, such species are unsuitable for scalable catalytic applications, and the incorporation of stabilizing ligands is deemed necessary (Chiba et al., 2025; Liu et al., 2019b).

Catalysts with electron-rich metal centers (CERMAs) (Androutsopoulos et al., 2024), offer a fundamentally different reactivity advantage. They can donate electron density into antibonding orbitals of strong bonds, facilitating activation and creating weak product–metal interactions (Sader and Miliordos, 2022) enhancing product desorption, and thereby mitigating undesired oxidative pathways. A plethora of coordination complexes with anionic metal centers has been reported recently in a review article (Landaeta et al., 2024) and our recent computational study reveals the kinds of ligands necessary to stabilize CERMAs (Androutsopoulos et al., 2024). It was shown that organometallic complexes (with ligands binding to the metal with a metal-carbon bond) have the highest potential.

A critical consideration is the stability of the metal oxide species of such CERMAs (-CMO −) since the oxygen atom can insert into the ligand framework to form -COM −, thereby deactivating the catalyst. The (CH 3) 4 MO −, M = Ni, Pd, Pt, anionic models were identified computationally as a prototypical system serving as proof of principle system (Sader and Miliordos, 2022). To prevent this deactivation, we used quantum chemical calculations to design an alternative ligand architecture (denoted A(C 3 MO) −; see Figure 1) and probe its performance towards selective MTM conversion. This ligand anchors carbon atoms in fixed positions near the metal center, which makes them less flexible and resembles the adamantine (Fort and Schleyer, 1964) and porphyrin-type ligands (anchoring nitrogen atoms replaced by carbon) used commonly for positively charged metal centers (Yasue and Yoshida, 2021). The review article of ref (Landaeta et al., 2024). has a collection of synthesized organometallic complexes with electron rich metal centers and structural features similar to those of Figure 1 (see, for example, their Scheme 44). By studying the reaction of these species with methane and methanol, we assess the catalytic efficiency of three first-row metals (M = Co, Ni, Cu).

Below, we first describe our computational approach (Section 2), and then we discuss stability and reactivity aspects of the proposed catalyst (Section 3). Finally, we summarize our results and provide insights for future studies (Section 4).

To study the catalytic performance, we found all intermediate and transition state structures. All stationary points were fully optimized using Gaussian 16 (Frisch et al., 2016), and their Cartesian coordinates are listed in Supplementary Tables S3-S5 of the supporting information (SI) file. Harmonic frequency calculations were performed to confirm the nature of each structure, ensuring that minima exhibited no imaginary frequency and transition states showed exactly one. All intermediate structures are confirmed to be minima in their potential energy surface. It should be mentioned that crossing points on the potential energy surfaces have not been optimized. Gibbs free energies at 25 °C and 1 atm were calculated for all species using the harmonic approximation as implemented in Gaussian 16. These free energies were used for the calculation of turn-over frequencies and rate constants (see also SI for more details). Our highest level electronic structure calculations performed are unrestricted DFT calculations with the MN15 hybrid density functional (Yu et al., 2016) selected for its balanced performance across main-group and transition-metal systems and inclusion of dispersion effects (Dandu et al., 2018). We also employed the B3LYP functional to monitor the effect of the missing non-covalent interaction terms. In every case, we have performed stability checks to ensure that the self-consistent cycles have converged to the lowest energy electronic configuration (Slater determinant).

The reaction in this study involves an adamantane-like cluster comprising the reactive central atoms (RCAs), which are: the metal anion (Co −, Ni −, Cu −), oxygen, and the sp 3 hybridized carbons that are directly bound to the metal. Other C and H atoms in the cluster are referred to as peripherals. For geometry optimizations, the RCAs and atoms of the substrate molecules (CH 4 and N 2 O) are treated using aug-cc-pVDZ basis set to account for a better description of the negative charge shared by these atoms. We used the cc-pVDZ basis set for peripheral atoms, which do not directly participate in the reaction. We subsequently performed single-point calculations using the aug-cc-pVTZ basis for RCAs, keeping the cc-pVDZ basis set for peripheral atoms, to improve the calculated energetics.

Molecular models were initially constructed using Avogadro (Hanwell et al., 2012; Avogadro Team, 2022). GaussView and IQMol were then used for detailed visualization of optimized structures, molecular orbitals, and vibrational modes (Frisch et al., 2016; IQmol, 2026).

Stability of the active site of the catalyst

We first focus on the stability of the nickel oxide unit in comparison to the possible insertion of oxygen into the metal-ligand M-C bond. If oxygen atom gets between the carbon and the metal center, it becomes less available for transfer to methane, and the catalyst ceases to function as a reactive “O-atom donor”. To this end, we calculated the two structures A(C 3 NiO) − and A(C 2 NiOC) − (see Figure 2) to compare their energies. In addition, we examined the stability of the earlier studied model species (CH 3) 4 NiO − and (CH 3) 3 NiOCH 3 − (Claveau et al., 2023b).

Regarding the tetramethyl-nickel catalyst (CH 3) 3 NiOCH 3 − is favored over the active (CH 3) 4 NiO − form (Figure 2). In the low-spin state (S = 1/2) (CH 3) 3 NiOCH 3 − is significantly more stable than (CH 3) 4 NiO − by 49.2 kcal/mol. This preference remains essentially the same at high-spin state (S = 3/2), by an energy difference of 43.2 kcal/mol. With these large energy separations, oxidation of nickel strongly drives the system toward (CH 3) 3 NiOCH 3 − formation regardless of the spin state. Likewise, the Gibbs free energy correction stabilizes (CH 3) 3 NiOCH 3 − species relative to (CH 3) 4 NiO − by 49.2 kcal/mol and 46.5 kcal/mol for S = 1/2 and S = 3/2, respectively. In contrast, the presently devised A(C 3 NiO) − species becomes more stable than the A(C 2 NiOC) − counterpart. This model favors A(C 3 NiO) − by 3.7 kcal/mol at low-spin state (S = 0) and 7.4 kcal/mol at triplet state (S = 1). The Gibbs free energy values of 7.4 (S = 0) and 9.4 kcal/mol (S = 1) show a stronger preference towards the desirable A(C 3 NiO) −. Further calculations revealed that Cu − and Co − clusters are less susceptible to O-atom insertion. The A(C 3 CuO) − and A(C 3 CoO) − are respectively 12.1 kcal/mol and 10.0 kcal/mol (electronic energies) more stable than their A(C 2 MOC) − analogue at low-spin doublet state. At high-spin quartet state, the undesired A(C 2 MOC) − becomes less accessible with a 35.7 kcal/mol and 21.8 kcal/mol energy difference for Cu − and Co −. Interestingly, we observed a further ∼2.5 kcal/mol A(C 3 CuO) − stability for both S = 1/2 and S = 3/2 with Gibbs free energy correction, while A(C 3 CoO) − becomes more stable by 3.7 kcal/mol at S = 1/2 and 3.2 kcal/mol at S = 3/2. Conclusively, theoretical calculations can assist in identifying appropriately designed ligand frameworks with the desired structural properties.

Reaction mechanism and electronic structure considerations

We turn to the catalytic activity for the activation of methane. The mechanism is illustrated in Figure 3. The C-H bond cleavage in the initial encounter complex of the reactants (ECR) proceeds via a hydrogen transfer transition state (TS1), forming the intermediate (IM) radical species that releases CH 3 •. This mechanism is supported by the singly occupied orbitals of ECR and IM shown in Figure 4. Both ECR and IM have two unpaired electrons localized on carbon atoms orbitals of the porphyrin-like ring. Meanwhile, ECR has one electron localized in the NiO unit oxygen terminal, and IM has an unpaired electron in CH 3. The NiO electron abstracts a hydrogen atom from CH 4, forming the OH bond, while the second electron of the ruptured CH bond remains on carbon. The coupling of CH 3 • with the OH terminal coordinated to the metal forms a C-O bond (TS2) and triggers the transfer of an electron to the metal. The encounter complex of the products (ECP) includes the weak interaction of the produced methanol with the reduced metal center A(C 3 Ni) − …CH 3 OH. The reduced metal center A(C 3 Ni) − is finally oxidized by N 2 O, forming a short-lived encounter complex (OXR) and proceeding via an oxygen-atom transfer transition state (TS3) to regenerate the active A(C 3 NiO) − catalyst and N 2, which form a weakly bound encounter complex (OXP).

N 2 O was chosen as the oxidant in this work for two reasons. Firstly, N 2 O has a very small electron affinity (0.22 eV ± 0.1) (Wu and Tiernan, 1981; Nalley et al., 1973; Coe et al., 1986) and is smaller than the involved metal centers (0.66 eV for Co, 1.16 eV for Ni, 1.24 eV for Cu) (Scheer et al., 1998; Liu et al., 2002; Feigerle et al., 1981; Wu et al., 2010; Leopold et al., 1987; Bilodeau et al., 1998). The use of O 2 (EA = 0.45 eV ± 0.002), (Schiedt and Weinkauf, 1997) or O 3 (EA = 2.10 eV ± 0.004), (Comita and Brauman, 1985; Novick et al., 1979; Arnold et al., 1994), may trigger the electron transfer from the metal center to the oxidation agent and thus alter the electronic structure of the metal complex or prevent the oxygen reload to the metal center. Secondly, the MO bonds have larger binding energies (87.5 ± 0.7 kcal/mol for Ni, 70.1 ± 0.7 kcal/mol for Cu, 95.0 ± 2.8 kcal/mol for Co) (Haynes, 2012; Luo, 2007; Carta et al., 2014; Parry et al., 2013) are stronger than N 2 -O bonds (39.5 ± 0.01 kcal/mol) (Haynes, 2012; Kaufman, 1967) which facilitates the transfer of oxygen to the metal.

To confirm the electron-rich character of the metal center and that oxygen has an unpaired electron in all three A(C 3 MO) − complexes, we report the Mulliken charges and spin densities of the metal and oxygen atoms for all structures and spin states in Supplementary Table S1 of SI. The metallic charge is about −1.0 for ECR and becomes about −2.0 for ECP. On the other hand the charge on the oxygen atom is about −1.0 for ECR and becomes −0.5 or less for ECP. Mulliken charges generally depend on the basis set, but these results indicate clearly the electron rich nature of the metal, even in the metal-oxide form (ECR) of the catalyst. At the same time the spin density on the oxygen atom is found to be about 1.0 for ECR and 0.0 for ECP. This in agreement with the orbital of Figure 4A, and that oxygen is incorporated in methanol for ECP.

Structural information for the reaction coordinate

All intermediate and transition state structures are displayed in Figure 5. Starting from ECR, CH 4 interacts with the A(C 3 MO) − through dispersion and weak electrostatics. Methane reorients such that a single C-H bond points directly toward the terminal oxygen atom of A(C 3 MO) − to form TS1. At TS1, the reactive C–H bond is increased from 1.10 Å to 1.33 Å; the H atom is roughly midway between C and O, as the C center begins to acquire partial radical character. This resulted in the formation of a CH 3 radical in the IM, which then moves behind the OH to approach the oxygen atom with a favorable angle. At TS2, the CH 3 • collides onto the oxygen to form a strong C-O bond as methanol is produced. The methanol formed interacts weakly with A(C 3 M) −, which facilitates its release. Next, N 2 O aligns its N-O bond pointing the metal center to cause the A(C 3 MO) − catalyst regeneration.

Free energy diagrams

From the energy diagram, Figure 6, the high and low spin states are nearly degenerate across the full reaction coordinate. The initial attractive forces stabilize the CH 4 …A(C 3 NiO) − at the ECR by 8.7 kcal/mol for S = 0 and 9.2 kcal/mol for S = 1. Gibbs free energy correction further stabilizes the low-spin state by 1.2 kcal/mol, whereas the triplet state becomes less stable by 0.2 kcal/mol relative to the fragments. The system proceeds via a barrier (ECR→TS1) of 14.0 kcal/mol and 13.8 kcal/mol for singlet and triplet states after Gibbs correction. A shallow well characterizes the metastable intermediate IM (Zugic et al., 2019; Zhang et al., 2020; Cao et al., 2021), which is slightly higher in energy than the ECR by 1.3 kcal/mol and 40.3 kcal/mol less stable compared to the ECP for S = 0.

Interestingly, the TS2 is lower in energy compared to TS1 by 5.6 kcal/mol for triplet state and 6.3 kcal/mol for singlet state; the lower barrier of TS2 drives the reaction towards the products (ECP), suppressing side reactions of CH 3 • with surrounding molecules. Likewise, the TS2 is entropically favored and becomes only 1.2 kcal/mol (S = 0) and 1.4 kcal/mol (S = 1) lower than TS1 after free energy correction. It is noteworthy that between TS2→ECP there is a crossing point leading to S = 0 ECP ground state. Next, the methanol formed desorbs readily from the A(C 3 Ni) − complex. In the subsequent oxidation step, N 2 O reacts with A(C 3 Ni) − complex via a small barrier (TS3) of 4.3 kcal/mol and 4.7 kcal/mol for the singlet and triplet state, which results in fast catalyst regeneration A(C 3 NiO) −. The process is downhill, favoring N 2 release. The reason for this facile oxidation of the metal center with N 2 O is that after it coordinates to the metal, one electron is transferred from the metal to a π*(NN-O), weakening the N-O bond (see Supplementary Figure S6 of SI).

To emphasize the importance of non-covalent interactions in the energy diagram, we contrast our MN15 and B3LYP (no special treatment for non-covalent interactions) energy landscapes (compare Figure 7; Supplementary S1 of SI). As expected, the non-covalent interactions result in clearly more stable ECR, IM and ECP encounter complexes, but they also lower the energy of transition states decreasing the activation barrier for methane activation by about 5 kcal/mol.

Moving to the left of the periodic table, i.e., using A(C 3 CoO) − as catalyst, the near degeneracy of the low (S = 1/2) and high (S = 3/2) spin states is retained (Figure 7A). Conversely, the TS2 is higher in energy than TS1; this is pronounced at low spin (S = 1/2) and may result in CH 3 • build-up, but the IM being less stable than the ECR favors a backward reaction. With sufficient energy, the reaction will proceed, especially via the quartet spin state. Of the three metals, A(C 3 Co) − oxidation process is facile and spontaneous through a barrierless TS3, and N 2 release is entropically stabilized.

Focusing on the right (Figure 7B), the energy landscape changes considerably for A(C 3 CuO) −. The forward reaction is facilitated by the low barrier from ECR to IM and the two-state reactivity from IM to ECP. IM forms an unstable CH 3 •, which reacts towards ECP via a two-state reactivity process, changing spin from S = 1/2 to 3/2 and back to S = 1/2 (Michelini et al., 2008; Schröder et al., 2000). Once the A(C 3 Cu) − is achieved, the oxidation proceeds with a minimal kinetic resistance via TS3.

Selectivity for methanol production

Next, we examine the selectivity of each catalyst towards C-H bond activation of either methane or methanol in terms of their relative activation barriers. Table 1 lists the energetics for the reaction of the three metal oxides with methane and methanol with respect to the lowest energy reacting fragments. The transition states (TS) for CH 3 OH are lower in energy with respect to the fragments for CH 3 OH, but their ECRs are more stable as well. As a result, the barriers calculated as the energy difference between ECR and TS are competitive for methane and methanol (differ by less than 1 kcal/mol) except for A(C 3 CoO) – at (S = 1/2) with a clear kinetic preference for CH 4 by 7.8 kcal/mol. This trend is markedly different from the literature observations where methanol has on average 0.57 eV lower activation barriers and the improvement of selectivity occurs at the expense of efficiency (Latimer et al., 2018; Ravi et al., 2017).

Based on our results (see Table 1; Figure 8), A(C 3 CuO) – is selective towards activating CH 4, favored by 0.9 kcal/mol and 0.4 kcal/mol for S = 1/2 and S = 3/2, respectively. A(C 3 CoO) – demonstrated a stronger preference for CH 4 activation at S = 1/2 by 7.8 kcal/mol, but at the high-spin quartet state it favors methanol activation by a 0.8 kcal/mol lower energy barrier. A(C 3 NiO) – catalyst is CH 3 OH selective with a competitive difference of 0.8 kcal/mol S = 0 and 0.7 S = 1 kcal/mol in energy barrier. Although our methods cannot account accurately for energy differences of 1–2 kcal/mol (limited accuracy of chosen DFT functional, absence of solvent effects, incomplete basis set), our calculations indicate that negatively charged metal centers can inherently improve selectivity towards methane due to kinetic arguments. This has been observed for rhodium ammonia complexes, where the barriers of methanol are increased due to hydrogen bonding of methanol with the ligands (Claveau et al., 2023b).

Other mechanisms, which can lead to the formation of byproducts or deactivation of the catalyst, are initiated when the CH 3 radical present in IM escapes to the solution before the formation of ECP (Snyder et al., 2021). Our calculated interaction energies between CH 3 and the hydroxide species of IM are 20 kcal/mol or more (20.9 kcal/mol for copper, 28.9 kcal/mol for nickel, and 30.2 kcal/mol for cobalt). All of these values are higher than the IM→ECP activation barriers and thus the formation of methanol is expected to be more favorable.

A different mechanism that can lead to deactivation of the catalyst is the activation of the O-H bond of methanol. This can lead to the formation of methoxy groups which may bind to the metal center and shut down the catalytic cycle. To see if this side path is possible, we considered the activation of the O-H of methanol by both A(C 3 M) – and A(C 3 MO) –. In the A(C 3 M) – case, we calculated the geometries and energies of A(C 3 MH(OCH 3)) –, i.e., formation of methoxy group, and compared them with the A(C 3 M) – + CH 3 OH reacting species (ECP). The optimized geometries and energies are given in Supplementary Table S6 of SI, and the results indicate that the activation of the OH bond of methanol is unfavorable by at least 30 kcal/mol (see Supplementary Table S6). In the A(C 3 MO) – case, we compared the energies of A(C 3 MO) – + CH 3 OH, A(C 3 MOH) – + CH 3 O, and A(C 3 MOH) + CH 3 O −, but only for M = Cu (see Supplementary Table S7 of SI). We found that the lowest energy fragments in the gas-phase are A(C 3 MOH) – + CH 3 O, followed by A(C 3 MO) – + CH 3 OH 4.4 kcal/mol higher, and finally by A(C 3 MOH) + CH 3 O − at 10.7 kcal/mol. These numbers indicate that the release of a methoxy group (that could poison some catalytic centers) cannot be excluded, but we believe that the energetics can be tuned to prevent the release by changing the ligands or solvent polarity.

Assessment of the catalytic performance

To assess the catalytic efficiency of A(C 3 MO) – we first applied the energetic span model (Kozuch and Shaik, 2011). Using our free energy landscapes we estimate their turnover frequency (TOF) for MTM at 298 K and determine the TOF-determining transition state (TDTS) and the TOF-determining Intermediate (TDI). To this end, the lowest energy of each species is considered. For Ni − and Cu − the TDI is the encounter complex of methanol with the reduced form of the catalyst (ECP), and TDTS is the produced fragments (see Supplementary Figure S7 of SI), indicating the methane activation (ECR→IM) and recombination (IM→ECP) energy barriers are not TOF-determining steps, but rather the desorption of methanol is. A(C 3 CoO) – acts differently where ECR is the TDI and TS2 is the TDTS.

The fact that the desorption step is the rate-determining step suggests that solvent effects can play a crucial role in the TOF values. Without solvent effects, A(C 3 NiO) – is the best performing catalyst with a TOF of 140 s –1 (see Supplementary Figure S7 of SI). If a 2.5 kcal/mol reduction in the desorption step barrier is assumed due to solvent effect the TOF increases to 2,100 s –1 highlighting the role of the solvent. At the same time the TDTS/TDI switched to the CH 4 activation step. Similar solvent treatment on A(C 3 CuO) – desorption step will increase its catalytic efficiency by two orders of magnitude from 0.14 s –1 to 9.7 s –1. To achieve the same catalytic performance as A(C 3 NiO) –, a 4–5 kcal/mol reduction in TDTS/TDI barrier with solvent is required, because A(C 3 CuO) – activates CH 4 more easily. It should be emphasized that anionic metal centers are advantageous over cationic metal centers since they offer smaller interaction energies with methanol (Claveau et al., 2023a).

Temperature is another parameter we examined. Increasing the temperature from 298 K to 400K, the TOF increases considerably to 5.3 × 10 5 s –1 for A(C 3 NiO) – and 1.3 × 10 4 s –1 for A(C 3 CuO) –. A(C 3 CoO) – on the other side experiences little improvement with solvent effect and temperature change due to its low initial activity towards CH 4 activation, having a TOF of 1.8 × 10 −5 s –1. Considering the competitive kinetics for methane/methanol activation and the temperature sensitivity of TOF, these systems and specifically A(C 3 CuO) – offer ideal conditions for the efficient and selective activation of methane. In addition, appropriately solvated A(C 3 CuO) – and A(C 3 NiO) – will make effective catalyst considering how diffusion dominant the reactions of CERMAs are.

For comparison, we also calculated the maximum TOF for the same catalytic cycles but not assuming the steady-state approximation exploited in the energetic span model. To this end, we used the COPASI software (Hoops et al., 2006) to solve the chemical kinetic equations and calculate the time dependence of the concentrations of all species. For more technical details and plots see SI. Our results are in absolute agreement with the energetic span model. The two sets (energetic span model/no-steady-state approximation) of TOFs are 1.80 × 10 −5 /1.75 × 10 −5, 140/140.25, 0.14/0.14 s –1 for Co, Ni, Cu, respectively, being in perfect agreement.

In this work, we employed a theoretically designed CERMA to examine the efficiency of converting methane to methanol. The employed tri-dentate ligand (adamantane-porphyrin-type) was designed to anchor with a metal-carbon bond, which secures the negative charge on the metal. The oxidation of CERMAs with N 2 O is fast and spontaneous and produces a negatively charged oxide appropriate for methane activation. The present ligand was also designed to avoid the insertion of oxygen in the coordinating metal-carbon bonds. Using DFT calculations, we unraveled the reaction mechanism, predicted all intermediate structures and transition states for three different metals (Co., Ni, Cu), and calculated TOFs based on the free energy landscapes. We found that CERMA offers promising performance tackling the selectivity and efficiency issues reported in the literature. Specifically, the reported catalysts are composed of Earth-abundant metals, offer small methane activation barriers, and (within the accuracy of the employed methodology) bear inherently competitive activation barriers for methane and methanol. It was shown that the release of methanol, and not the activation or recombination steps, is the TOF-determining step. It was demonstrated that large TOFs can be achieved by tuning the temperature (increase of 100 K) of the reaction and/or choosing proper solvents. Comparing the three metals, copper was found to provide the most efficient and selective catalyst within the present computational framework. We hope that our findings will motivate further future experimental studies and open a new avenue for solving one of the most challenging chemical transformations using electron rich metal centers.