(92e) Simulation of Rate and Product in the Fischer-Tropsch Synthesis Based On the Dynamic Kinetics

INTRODUCTION It is well known that the FTS products contains fairly large amount of olefins (mainly 1-olefin), its contents decreases with increasing carbon number(c-number) of the products and usually the C20+ products contains little olefins [1]. Fujimoto has demonstrated that the contents of olefin are high and almost independent on the c-number of the FTS products over C4-C25 in the reaction under supercritical n-hexane solvent [2] or in the trickle bed reaction with n-paraffin solvent. The phenomenon has been attributed to the quick extraction of 1-olefin from the active site and the quick transfer of it out of the catalyst pores, which minimize the successive hydrogenation of 1-olefins [2, 3]. On the basis of experimental results, a new reaction network including the reactive 1-olefin was presented [4]. In this paper, we show a reaction model and analyze it by a simulation method to elucidate the rate parameters which control the carbon number distributions, and also the effect of added olefins. EXPERIMENTAL Catalyst preparation: A 20 wt.% Co/SiO2 catalyst was prepared by an incipient wetness method. The cobalt nitrate was used as the precursor of cobalt and a commercially available silica gel (Fujisilica, average pore diameter: 6 to 30 nm) was used as the support. The apparent dispersion of Co was about 3%. The catalyst used in this work was pressed, crushed and sieved to 20-40 mesh size. The catalyst (1.0 g) was diluted with silica gel before loading into the reactor. The detailed catalyst preparation has been written elsewhere [2][3]. Reaction procedure and product analysis: The configuration of reactor for the conventional or olefin-added FT reaction was shown in the previous paper in detail [4]. Syngas and solvent (or co-fed olefin in the solvent) were fed to the vaporizer by a mass flow controller and a high pressure liquid pump, and then entered into the reactor concurrently. The effluent gas and liquid from the reactor passed through an ice-cooled condenser, where the solvent and FT products were condensed continuously, and uncondensed products with unreacted syngas were depressurized and led to an online gas chromatograph. n-Hexane, n-octane, n-nonane or n-dodecane was utilized as the solvent fluids. 1-octene, 2-octene or 1-decene was selected as the co-fed olefin. The temperature of the vaporizer is 240°C. Typical reaction conditions were: Ptotal = 2.1 MPa, W/Fsyngas = 5 g/(mol/h) ,T = 230 °C. The c-number simulation was conducted by the REX file supplied by Optience Corporation [4]. RESULT AND DISCUSSION Reaction model and simulation We proposed a new simplified reaction model, which contain the carbine species on the surface of catalyst, by using molecular reactions to identify as follows: Hydrogenation: H2+CnH2n+2→CnH2n+2 (Rnh, n³a3) Chain growth:2H2+CO+CnH2nÌCn+1H2n+2+H2O(Rng, n³a3). Rate equations are Langmuir-Hinshelwood type ones. Simulation result: We show the one of the results in Figure 1(a), which is shown in comparison with the experimental data. It can be seen from the calculated data that the amount of C11+ product increased while the amount of C9- product is decreased. Then the c-number distribution jumps from C9 to C11 when a small amount of 1-decene is added to the FTS system (16% to CO in carbon base). Also, the CH4 formation was suppressed. This simulation behaviour agreed well with the experimental data in each case. Uncertainty of CO conversion, which is 100x |COconv_cal-COconv_measured|/COconv_measured, is within 10%. It is clear from the calculated data fit well to the experimental data except the reaction under high pressure simulation case. Also, rate constants for the chain growth and hydrogenation on the Q-15 based catalyst are shown in Figure 1(b). Is is clear from the figure that rate constants of either chain growth and hydrogenation increased with increasing carbon number of the product hydrocarbons. The marked increase in the rate constant of chain growth explains the deviation of c-number distribution from ASF plot. REFERENCES [1]K.Yokota, K.Fujimoto, I&EC Res.30(1991)95 [2]X.H.Liu, W.S.Linghu, X.H.Li, K.Asami, K.Fujimoto, Appl.Catal.A:Gen.303(2006) [3]X.H.Liu, X.H.Li,K.Fujimoto, Catalysis Communications 8 (2007)1329 [4]Y.Suehiro,X.H.Liu,T.Jiu, K.Fujimoto, AIchE The Annual Meeting (2008)