Modeling the roles of rigidity and dopants in single-atom methane-to-methanol catalysts

Abstract

Doped graphitic single-atom catalysts (SACs) with isolated iron sites have similarities to natural enzymes and biomimetics that can convert methane to methanol via a radical rebound mechanism with high-valent Fe(IV)=O...

New Strategies for Direct Methane-to-Methanol Conversion from Active Learning Exploration of 16 Million Catalysts

“…Indeed, exothermic HAT thermodynamics with a methane substrate have been observed on HS Fe(II) catalysts 73 with weak-field oxygen-coordinating ligands and on LS Fe(II) SACs with O, N, or S coordination. 114 Similarly, HAT thermodynamics from larger substrates (e.g., ethane, propylene, or 2-propanol) are near thermoneutral 45 or negative 35 for HS Fe(II) metal–organic framework catalysts. Over this initial 1.2 M catalyst design space, EGO reveals ligands that have been understudied (e.g., 3p-coordinating ligands) combined with LS Fe(II) will lead to catalysts with a good balance between Δ E (HAT) and Δ E (release), as long as the LS state is the ground state for the complex (see Section 4.3 ).…”

“…The compounds that have the most favorable HAT thermodynamics at the cost of binding methanol more tightly primarily contain oxygen-coordinating macrocycles, whereas those that release methanol more readily but do not favor HAT contain 3p-coordinating macrocycles (Figure and Supporting Information, Figure S18). Indeed, exothermic HAT thermodynamics with a methane substrate have been observed on HS Fe­(II) catalysts with weak-field oxygen-coordinating ligands and on LS Fe­(II) SACs with O, N, or S coordination . Similarly, HAT thermodynamics from larger substrates (e.g., ethane, propylene, or 2-propanol) are near thermoneutral or negative for HS Fe­(II) metal–organic framework catalysts.…”

Using Computational Chemistry To Reveal Nature’s Blueprints for Single-Site Catalysis of C–H Activation

“…The 57 Fe Mössbauer spectroscopic studies necessary to assign the precise oxidation/spin states of the FeN x C y moiety remain challenging due to the distribution of sites that must be obtained from spectral fits. , Typically, SACs are modeled with plane-wave, semilocal DFT, in which the metal oxidation and spin states are either erroneously predicted or not precisely defined (i.e., due to fractional occupation of frontier states with smearing using semilocal DFT). To reveal the electronic structure of the metal and its relationship to the catalytic reactivity, efforts to understand SAC reactivity via molecular mimics have probed the effects of nitrogen type (e.g., pyridinic or pyrrolic), typically embedded in 14- or 16-membered macrocycles. ,, DFT modeling of finite size nanoflakes that represent the infinite system also help address the challenges in periodic systems …”

“…208,228,229 DFT modeling of finite size nanoflakes that represent the infinite system also help address the challenges in periodic systems. 24 DFT has also been a useful tool for mechanistic understanding 230,231 and fast screening of new SACs. 232,233 However, density functional approximation (DFA) sensitivity 234 and improved electronic structure methods for accurate descriptions of spin-and oxidation-state-dependent properties 235 remain active areas of research (see Section 5).…”

“…Zeolites, MOFs, and SACs are promising materials for practical use, because they can be more readily separated from products and reactants. The active sites in metalloenzymes have inspired incorporation of isolated Fe atoms in these materials that can also perform C–H bond activation. , The complex nature of these systems and the challenges of achieving atomic precision with spectroscopic techniques have required a tight interplay between characterization and simulation. Nevertheless, further developments are needed both in increasing the computational speed (e.g., with machine learning) and accuracy (e.g., by going beyond DFT) to enable rapid discovery and design.…”