In Situ Active Site for CO Activation in Fe-Catalyzed Fischer–Tropsch Synthesis from Machine Learning

Abstract

In situ-formed iron carbides (FeC x ) are the key components responsible for Fischer–Tropsch synthesis (FTS, CO + H2 → long-chain hydrocarbons) on Fe-based catalysts in industry. The true active site is, however, highly controversial despite more than a century of study, which is largely due to the combined complexity in both FeC x structures and mechanism of CO hydrogenation. Herein powered by machine learning simulation, millions of structure candidates for FeC x bulk and surfaces are explored under FTS conditions, which leads to resolving the active site for CO activation. This is achieved without a priori input from experiment by first constructing the thermodynamics convex hull of bulk phases, followed by identifying the low surface energy surfaces and evaluating the adsorption ability of CO and H, and finally determining the lowest energy reaction pathway of CO activation. Rich information on FeC x structures and CO hydrogenation pathways is gleaned: (i) Fe5C2, Fe7C3, and Fe2C are the three stable bulk phases under FTS in producing olefins, where Fe7C3 and Fe2C have multiple energetically nearly degenerate bulk crystal phases; (ii) only three low surface energy surfaces of these bulk phases, namely, χ-Fe5C2(510), χ-Fe5C2(111), and η-Fe2C­(111), expose the Fe sites that can adsorb H atoms exothermically, where the surface Fe:C ratio is 2, 1.75, and 2, respectively; (iii) CO activation via direct dissociation can occur at the surface C vacancies (e.g., with a barrier of 1.1 eV) that are created dynamically via hydrogenation. These atomic-level understandings facilitate the building of the structure–activity correlation and designing better FT catalysts.

Selective and Stable In-Promoted Fe Catalyst for Syngas Conversion to Light Olefins

“…We note that the phases of indium in the sample were undetectable via XRD. Extensive studies have already shown that Fe 2 C and Fe 7 C 3 are two of the major carbide phases formed during the FTS reaction. − Both of them were reported to promote C–C coupling toward olefin and C5+ hydrocarbon formation under the specific reaction conditions, − which was kept in line with our study. Details about the effect of carbide phases on catalytic reactivity are not the focus of this study.…”

Light olefin synthesis from a diversity of renewable and fossil feedstocks: state-of the-art and outlook

“…The carbide phase composition depends on the H 2 /CO ratio, iron dispersion, promoters, support, the extent of iron reduction and temperature. 319 Recent machine learning simulation 320 indicated that Fe 5 C 2 , Fe 7 C 3 , and Fe 2 C were the three stable bulk phases under FT synthesis, producing olefins.…”

Mutual modulationviacharge transfer and unpaired electrons of catalytic sites for the superior intrinsic activity of N2reduction: from high-throughput computation assisted with a machine learning perspective

“…Recently, data-driven method brought about great success in computer vision 20 , natural language processing 21 and speech recognition 22 . With the inspiration and opportunities of machine learning (ML), amounts of related studies using MLassisted method have emerged for prediction of formation energy of crystals 23 , superhard compounds 24 and catalytic activity [25][26][27][28][29][30][31] . In general, material features should be properly selected for descriptor-to-property mappings in ML.…”