Modeling of Catalyst Deactivation in Bioethanol Dehydration Reactor

Abstract

The catalytic ethanol dehydration route is a reality for the production of polyethylene from renewable sources. Ethanol dehydration process is performed in the presence of acid catalysts, under temperatures ranging from 500 K to 800 K, obtaining ethylene selectivity ranging from 95% to 99% and ethanol conversion of >98%. Despite the favorable values of conversion and selectivity, catalyst deactivation by coking is a well-known phenomenon that occurs in this process. This phenomenon leads to catalyst regeneration cycles, given that the catalyst’s life cycle is dependent on the process operating conditions. Thus, obtaining a mathematical model to optimize the ethanol dehydration process is of great interest to industry, allowing process optimization and optimal design of reactors. This work presents a phenomenological model of an ethanol dehydration fixed-bed reactor considering the catalyst deactivation and several chemical species. The developed mathematical model for catalyst deactivation considers species present in the reaction system as coke precursors. The predictive ability of the model, which has been validated with industrial plant data, are shown in the results, presenting deviations of <5% in the reactor temperature profile.

The mathematical catalyst deactivation models: a mini review

“…A generalized power-law model (eqn (7)) has been extensively applied to represent catalyst deactivation. [44][45][46][47][48][49] Accordingly, by taken deactivation power as either a "1" or "2" through integration eqn (7), the algebraic expressions for catalyst activity can be achieved as shown in eqn ( 8) and ( 9) respectively:…”

“…A generalized power-law model (eqn (7)) has been extensively applied to represent catalyst deactivation. 44–49 Accordingly, by taken deactivation power as either a “1” or “2” through integration eqn (7), the algebraic expressions for catalyst activity can be achieved as shown in eqn (8) and (9) respectively: a = e − k d t for n = 1In addition, Chen and Lua 50 added the term residence time to the power-law deactivation model as shown in eqn (10). Bartholomew 51 confirmed that a generalized power-law expression (GPLE) with residual activity was represented by catalyst deactivation, which was enhanced compared to the power-law expression.…”

A Zeolite-Based Cascade System to Produce Jet Fuel from Ethylene Oligomerization

“…In this context, biomass-derived fuels offer a promising sustainable solution. , Biomass-derived alcohols such as bioethanol can be easily converted into ethylene, butenes, and other short-chain olefins through dehydration reactions. − In turn, these light olefins can be transformed into longer-chain jet fuel range chemicals through heterogeneous zeolite-catalyzed oligomerization. − Zhang et al have performed a comprehensive life cycle and techno-economic assessment of ethylene oligomerization within the context of an ethanol-based biorefinery, concluding that there are good prospects for this process. Many other authors consider ethylene oligomerization a process to investigate in the near future because it is a key intermediate step in transforming biomass-derived streams .…”