Fischer-Tropsch synthesis parameters

Table 6.11.3 Data on chemical media and reaction conditions of Fischer-Tropsch synthesis. Parameter...

Effect of a Novel Nitric Oxide Calcination on the Catalytic Behavior of Silica-Supported Cobalt Catalysts during Fischer-Tropsch Synthesis, and Impact on Performance Parameters... 

This leads to a selectivity limitation in the Fischer Tropsch synthesis, as is shown in Figure 8 [42], which clearly demonstrates that it is impossible to develop FT catalysts selectively yielding only one compound, except the Ci cmnpounds methane and methanol, although selectivity tailoring to broader product distributions such as diesel (C9 - 2 ) is viable. It is important to keep in mind that once the progression coefficient a is fixed, the whole product distribution is determined. The constant a depends on both catalyst composition and particle size used and also on rcactitm parameters 43,44],... 

Sekclivitv control in Fischer Tropsch synthesis by reaction parameters and catalyst... 

Fig. 23. The effect of catalyst structural parameter ix) on Fischer-Tropsch synthesis activation energy and kinetics (473 K, 2000 kPa, H2/CO = 2.1 55-65% CO conversion, > 24 h onstream).

Kinetic data for Fischer-Tropsch synthesis on unsupported iron catalysts have been obtained as part of an overall study of the deactivation of iron catalysts. Data for unpromoted and potassium-promoted catalysts reacted at 1 aim total pressure are reported. At the reaction conditions used in this study, kinetic parameters for the potassium-promoted catalyst cannot be obtained without effects of deactivation. Reaction o ers in the power-law expression for the unpromoted catalyst are 1.4 and 0.60 for Ph2 and Pco> respectively. The unpromoted catalyst exhibits a deactivation order of 1 when the generalized power-law expression is used. 

This paper discusses research efforts towards the prediction of hydrocarbon product distribution for the Fischer-Tropsch synthesis (FTS) on a cobalt-based catalyst using a micro-kinetic model taken fiom the literature. In the first part of the study, a MATLAB code has been developed which uses the Genetic Algorithm Toolbox to estimate parameter values for the kinetic model. The second part of the study describes an ongoing experimental campaign to validate the model predictions of the fixed-bed reactor FTS product distribution in both conventional (gas phase) and non-conventional (near-critical and supercritical phase) reaction media. 

This corttmttrtication reviews the main parameters controlling the coating of metalhc monoliths and rtticrochatmel reactors on the basis of oirr experience studying different systems catalysts for Fischer-Tropsch synthesis [8], methane combustion... 

Hydrocarbon distributions in the Fischer-Tropsch (FT) synthesis on Ru, Co, and Fe catalysts often do not obey simple Flory kinetics. Flory plots are curved and the chain growth parameter a increases with increasing carbon number until it reaches an asymptotic value. a-Olefin/n-paraffin ratios on all three types of catalysts decrease asymptotically to zero as carbon number increases. These data are consistent with diffusion-enhanced readsorption of a-olefins within catalyst particles. Diffusion limitations within liquid-filled catalyst particles slow down the removal of a-olefins. This increases the residence time and the fugacity of a-olefins within catalyst pores, enhances their probability of readsorption and chain initiation, and leads to the formation of heavier and more paraffinic products. Structural catalyst properties, such as pellet size, porosity, and site density, and the kinetics of readsorption, chain termination and growth, determine the extent of a-olefin readsorption within catalyst particles and control FT selectivity. 

Since iron carbonyls are not only involved in chemical synthesis (of e.g., iron nanoparticles) but also can occur in heterogenous iron catalysts during reaction conditions (e g., Fischer Tropsch reactions), we wiU briefly discuss the Mossbauer parameters of this class of compounds. 

The catalytically active phase was assumed to be exclusively a-Fe, and Fe304 was assumed not to be active for the Fischer-Tropsch reaction. Kinetic parameters for the simulations were obtained independently in separate oxidation/reduction studies. Balancing the oxidation and reduction rates for the CO/CO2 and the H2/H2O systems independently and describing the rate of synthesis in Fischer-Tropsch reactions by a standard expression, Caldwell could predict the oscillations with a simplified model for a tubular reactor fairly well. 

The Fischer-Tropsch (FT) synthesis involves catalytic reactions in which CO and H are reacted to form mainly aliphatic straight-chain hydrocarbons (C Hy). The kind of liquid obtained is determined by the process parameters (temperature, pressure), the kind of reactor, and the catalyst used. Typical operation conditions for the FT synthesis are a temperature range of 200-3 5 0 C and pressures of 15-35 bar, depending on the... 

Early SBCR models were reviewed by Ramachandran and Chaudhari (5) and by Deckwer (9). They require hold-up correlations as an input and do not compute flow patterns. The most complete and useful of these models applied to the Fischer-Tropsch (F-T) conversion of synthesis gas in a SBCR is that of Prakash and Bendale (79). They sized commercial SBCR for DOE. They gave syngas conversion and production as a function of temperature, pressure and space velocity. Input parameters with considerable uncertainty that influenced production rates were the gas hold-up, the mass transfer coefficient and the dispersion coefficient. Krishna s group (77) extended such a model to compute product distribution using a product selectivity model. Air Products working with Dudukovic measured dispersion coefficients needed as an input into such model. The problem with this approach is that the dispersion coefficients are not constant. They are a function of the local hydrodynamics. 

Developments in the Fischer-Tropsch synthesiis at the Bureau of Mines from 19 5 to I960 include a simple mechanism for chain growth and the use of iron nitrides as catalysts. The chain-growth schene can predict the carbon-number and isomer distributions for products from most catalysts with reasonable accuracy using only 2 adjustable parameters. Iron nitrides are active, durable catalysts that produce high yields of alcohols and no wax. During the synthesis, the nitrides are converted to carbonitrides. 

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