Search Results (3)

This study focuses on simulating and optimizing cumene (isopropylbenzene) production via the alkylation of benzene with propylene using a beta zeolite catalyst. Two process configurations were evaluated: a conventional setup without a transalkylation reactor and an enhanced configuration incorporating a transalkylation unit to convert byproducts back into cumene. The process was modeled under steady-state conditions in Aspen HYSYS using plug flow reactors and the Peng–Robinson fluid package, with reaction kinetics derived from established literature on zeolite-catalyzed systems. Optimization studies examined the effects of reactor temperature, pressure, and the benzene-to-propylene molar ratio. Increasing the reactor temperature to 178 °C improved propylene conversion to 96.20%, while raising the pressure from 3540 kPa to 3600 kPa further enhanced it to 96.24%. By optimizing the benzene-to-propylene molar feed ratio to approximately 1.02:1 and increasing the fresh benzene feed to 138.5 kmol/h, cumene production reached 135.792 kmol/h while minimizing byproduct formation. Comparative analysis revealed that the configuration without a transalkylation reactor generated 4.171 kmol/h of diisopropylbenzene (DIPB) as waste, representing both economic loss and environmental concern due to its toxicity. In contrast, the integration of a transalkylation reactor enabled the conversion of DIPB into additional cumene, significantly improving process efficiency and sustainability. These findings demonstrate that optimizing reaction conditions and integrating a transalkylation step substantially enhances cumene yield and reduces waste, leading to a more viable and environmentally friendly industrial process. Full article

Commercial heavy reformate is converted over MCM-41 on zeolite beta composite catalyst to produce mixed xylenes in a fluidized-bed batch reactor. The heavy reformate feedstock contains 67.4 wt.% trimethyl benzenes (TMBs) and 31.1 wt.% methyl ethyl benzenes (MEBs). The experiments were carried out at 300, 350 and 400 °C, while the reaction times were varied between 5 and 20 s. The conversion of MEBs was more than two times the conversion of TMBs. The selectivity to xylenes was quite high (60–65 wt.%) but changed very little with reaction time or temperature. A kinetic model was developed using a five-reaction network. The product composition obtained from the estimated kinetic parameters closely matches the experimental results, which confirms the validity of the assumptions made for kinetic modeling. The trend in the apparent activation energies of the reactions was in accordance with the relative size of the reactant molecules, and the lowest activation energy was for the transalkylation of TMBs with toluene to produce xylenes. Full article

Soft sensors are used for fault detection and prediction of the process variables in chemical processing units, for which the online measurement is difficult. The present study addresses soft sensor design and identification for deactivation of zeolite catalyst in an industrial-scale fixed bed reactor based on the process data. The two main reactions are disproportionation (DP) and transalkylation (TA), which change toluene and C₉ aromatics into xylenes and benzene. Two models are considered based on the mass conservation around the reactor. The model parameters are estimated by data-based modeling (DBM) philosophy and state dependent parameter (SDP) method. In the SDP method, the parameters are assumed to be a function of the system states. The results show that the catalyst activity during the period under study has approximately a monotonic trend. Identification of the system clearly shows that the xylene concentration has a determining role in the conversion of reactions. The activation energies for both DP and TA reactions are found to be 43.8 and 18 kJ/mol, respectively. The model prediction is in good agreement with the observed industrial data. Full article