Structural and elemental influence from various MOFs on the performance of Fe@C catalysts for Fischer–Tropsch synthesis
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Bibliographic record
Abstract
The structure and elementary composition of various commercial Fe-based MOFs used as precursors for Fischer–Tropsch synthesis (FTS) catalysts have a large influence on the high-temperature FTS activity and selectivity of the resulting Fe on carbon composites. The selected Fe-MOF topologies (MIL-68, MIL-88A, MIL-100, MIL-101, MIL-127, and Fe-BTC) differ from each other in terms of porosity, surface area, Fe and heteroatom content, crystal density and thermal stability. They are re-engineered towards FTS catalysts by means of simple pyrolysis at 500 °C under a N <sub>2</sub> atmosphere and afterwards characterized in terms of porosity, crystallite phase, bulk and surface Fe content, Fe nanoparticle size and oxidation state. We discovered that the Fe loading (36–46 wt%) and nanoparticle size (3.6–6.8 nm) of the obtained catalysts are directly related to the elementary composition and porosity of the initial MOFs. Furthermore, the carbonization leads to similar surface areas for the C matrix ( <italic>S</italic> <sub>BET</sub> between 570 and 670 m <sup>2</sup> g <sup>−1</sup> ), whereas the pore width distribution is completely different for the various MOFs. The high catalytic performance (FTY in the range of 1.9–4.6 × 10 <sup>−4</sup> mol <sub>CO</sub> g <sub>Fe</sub> <sup>−1</sup> s <sup>−1</sup> ) of the resulting materials could be correlated to the Fe particle size and corresponding surface area, and only minor deactivation was found for the N-containing catalysts. Elemental analysis of the catalysts containing deliberately added promoters and inherent impurities from the commercial MOFs revealed the subtle interplay between Fe particle size and complex catalyst composition in order to obtain high activity and stability next to a low CH <sub>4</sub> selectivity.
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Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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