Catalyst Deactivation Model Research Articles

Multiscale modeling of catalyst deactivation in dry methane reforming

Dry methane reforming (DRM) presents a promising strategy to convert greenhouse gases (CH4 and CO2) into syngas, a valuable precursor for the production of long-chain alkanes. However, catalyst deactivation remains a major issue, primarily caused by the deep cracking of CH4 and CO2 as well as the metal-catalyzed growth of carbon whiskers. To address this challenge, we introduce a multiscale model that analyzes DRM reactions on the Ni surface and predicts whisker formation. The multiscale modeling approach integrates microscopic kinetic Monte Carlo (kMC) simulations for surface reactions, mesoscopic pellet-scale modeling for predicting whisker growth length and macroscopic modeling to consider packed bed porosity and pressure drop across the reactor. Further, by systematically introducing time-steppers using the gap-tooth scheme, we significantly improved the computational efficiency, reducing the computational time from 17 days to 6 h at the expense of minimal accuracy loss in predicting whisker length. Based on this, we assert that such a multiscale model enables the analysis of various operating conditions affecting catalyst deactivation and kinetics of surface reaction, aiding in the design and optimization of DRM process.

Eco-Friendly Transformation of Bioethanol into Ethylene over Bimetallic Nickel-Copper Catalysts.

The conversion of bioethanol to ethylene in gas phase and atmospheric pressure was investigated over γ-Al2O3 supported copper and nickel catalysts. These catalysts were prepared by co-precipitation and pre-treated with hydrogen at 450 °C. Six catalysts were studied at 450 °C under a nitrogen atmosphere. It was found that the monometallic Cu/γ-Al2O3 catalyst exhibited the highest ethylene concentration, with a selectivity of around 90 %. The bioethanol conversion obtained was between 57 %-86 %. Another catalyst that exhibited high concentration values was the NiCu1 : 7 bimetallic catalyst. The catalysts were characterised using XRD, SEM, EDS, TEM, TGA, FTIR, Raman, and N2-physisoption techniques. Furthermore, the Cu/γ-Al2O3 catalyst was studied under different reduction temperatures and gas flow conditions. It was found that the catalysts reduced at 350 °C and 35 ml/min N2 flow presented ethylene concentrations between (0.18-0.21) g/L. Moreover, the catalyst deactivation was identified to be first order and the equation of the Cu/γ-Al2O3 catalyst deactivation model was determined. Carbonaceous deposits over the used sample were not detected by Raman and FTIR. It was determined that the Cu/γ-Al2O3 catalyst deactivation could be mainly attributed to the blocking of the catalytic sites by strongly adsorbed compounds and hydroxylation of the catalyst surface.

A framework for modeling of catalyst deactivation and coking free of main-reaction kinetics in methanol to gasoline process

Optimizing the methanol-to-gasoline technology necessitates a profound comprehension of catalyst deactivation and coke formation kinetics. However, conventional mathematical models cannot capture catalyst deactivation without relying on complex main-reaction kinetic models, and they treat the prediction of coking as a separate problem. Addressing these challenges, this research introduces a computational framework to identify the optimal model for the kinetics of deactivation and coking. The key novelty is leveraging the concept of active site loss to eliminate the requirement for main-reaction kinetic models while facilitating the prediction of coking according to the site loss model. Experimental data of an HZSM-5 catalytic bed under diverse operating conditions (WHSV: 10–100 h−1, temperature: 325–375 °C) were employed to validate method efficiency for predicting reactor outputs, including oxygenates, light olefins, and gasoline. The proposed approach demonstrates a 0.52 % Root-Mean-Square-Error in simulating product weights and a 66 % reduction in deactivation kinetic constants. This study reveals assuming a critical volume for each grown coke precursor justifies experimental data by R2 of 99.71 %. This volume was computed around 100 Å3 and exhibits a linear Arrhenius temperature dependency. These results highlight the high accuracy and extreme simplicity this framework offers. Moreover, the method transforms deactivated catalyst data at varying WHSVs into a larger unified dataset for the fresh catalyst at each isotherm. Hence, it also positively impacts the kinetic study of main reactions. Consequently, the developed framework is a promising tool for direct assessment of catalyst deactivation and coking in similar processes toward advancing catalyst design strategies and fuel production efficiency.

Revisit the pathway and kinetics for transformation of light olefins over ZSM-5 modeling: Influence of steam-pretreatment

Previous kinetic studies on light olefins transformation over ZSM-5 catalyst were carried out either with pristine zeolite powders (research catalyst), or with commercial catalysts (technical catalyst) as-received without steam pretreatment, meanwhile, a rational procedure to discern the reaction network was lacking, thus a gap inevitably existed between the kinetic model established and the industrial practice. Herein, we revisited the kinetics of light olefins (C3–C7) interconversion over the commercial ZSM-5 catalyst, and special attention was paid to the effect of steam treatment. Comparative analysis was performed between the pristine and the steam-treated catalysts in terms of acid property, catalytic activity, and deactivation behavior. With the help of Delplot analysis, a rational and reliable kinetic model was developed for olefins interconversion as simple as possible, and a temporal kinetic model for catalyst deactivation was also proposed. These models can provide kinetic foundations for design and retrofit of MTO or MTP reactors.

The mathematical catalyst deactivation models: a mini review.

Catalyst deactivation is a complex phenomenon and identifying an appropriate deactivation model is a key effort in the catalytic industry and plays a significant role in catalyst design. Accurate determination of the catalyst deactivation model is essential for optimizing the catalytic process. Different mechanisms of catalyst deactivation by coke and metal deposition lead to different deactivation models for catalyst activity decay. In the rigorous mathematical models of the reactors, the reaction kinetics were coupled with the deactivation kinetic equation to evaluate the product distribution with respect to conversion time. Finally, selective and nonselective deactivation kinetic models were designed to identify catalyst deactivation through the propagation of heterogeneous chemical reactions. Therefore, the present review discusses the catalyst deactivation models designed for CO2 hydrogenation, Fischer-Tropsch, biofuels and fossil fuels, which can facilitate the efforts to better represent the catalyst activities in various catalytic systems.

Investigating a HEX membrane reactor for CO2 methanation using a Ni/Al2O3 catalyst: A CFD study

In this contribution, viability of processing of the flue gas streams as a source of carbon dioxide for the thermo-catalytic conversion was investigated. For this purpose, a Ni/Al2O3 commercial catalyst with known chemical kinetics was utilized. Moreover, a transient mathematical model for dynamic catalyst deactivation was developed and validated with experimental results available in the open literature. The developed model was then utilized to understudy an air-cooled membrane reactor. Different tube configurations were understudied and compared to choose the conditions under which high conversion was feasible. Sensitivity analysis revealed that, the space velocity, cooling rate, and feed distribution were all considered to be critical factors. It was revealed that, the presence of membrane resulted in higher conversion through the undertaken reactor. It made it possible to enhance reaction yield of non-membrane reactor through evenly distributing hydrogen along its length. A designed heat-exchanger (HEX) membrane reactor achieved 99% CO2 conversion when the coolant flow rate was reached to 10% of the coolant gravimetric flow rate, feed space velocity was set at 100 h−1 and the feed pressure was set at 10 bars.

Modeling of Catalyst Deactivation in Humic Acid Degradation

Modeling of Catalyst Deactivation in Humic Acid Degradation

Experiment and modeling of coke formation and catalyst deactivation in n-heptane catalytic cracking over HZSM-5 zeolites

Since paraffins catalytic cracking was of significant importance to light olefins and aromatics production, this work was intended to gain insights into the feature and model of coke formation and catalyst deactivation in n-heptane catalytic cracking over HZSM-5 zeolites. 18 tests of n-heptane catalytic cracking were designed and carried out over HZSM-5 zeolites in a wide range of operating conditions. A particular attention was paid to the measurement of the conversion, product distribution, coke content, and the porosity and acidity of the fresh and spent HZSM-5 zeolites. It was found that alkene and aromatic promoted coke formation, and it reduced the pore volume and acid site of HZSM-5 zeolites, tailoring its performance in n-heptane catalytic cracking. The specific relationship between HZSM-5 zeolites, n-heptane conversion, product distribution and coke formation was quantitively characterized by the exponential and linear function. Based on the reaction network, the coupled scheme of coke formation and catalyst deactivation were specified for n-heptane catalytic cracking. The dual-model was proposed for the process simulation of n-heptane catalytic cracking over HZSM-5 zeolites. It predicted not only the conversion and product distribution but also coke content with the acceptable errors.

Modeling and simulation of catalyst deactivation and regeneration cycles for propane dehydrogenation - comparison of different modeling approaches

Direct dehydrogenation is one well-established process for the provision of short chain alkenes and suffers from rapid catalyst coking. Kinetic modeling of coke built-up and catalyst deactivation due to coking is essential to optimize the total production process consisting of alternating deactivation and regeneration cycles.In this contribution two different deactivation approaches will by studied and evaluated. The first one, introduced by Janssens, describes deactivation as a loss of active catalyst mass depending on the conversion of the reactant. The second, an advanced microkinetic approach, was suggested by Dumez and Froment and explains the loss of activity by coke formation during the production process. Thus, a time dependent activity function is derived and correlated with the reaction rate.Results of experiments performed in a lab scale tubular reactor on a VOx catalyst provided the basis for extending and parametrizing models for reaction kinetics, coke built-up and deactivation, respectively. Temperature and oxygen concentration have been varied to describe the activity dependence on time and reactor position.Finally, modeling the cyclic operation of deactivation and regeneration was possible and allowed optimizing the individual time intervals to maximize total space time yield. A first proposal of an optimized cyclic process regime is presented.

Development and experimental validation of reactor kinetic model for catalytic cracking of eugenol, a potential bio additive fuel blend

Abstract An integrated kinetic model representing catalytic cracking of eugenol in a fixed bed reactor is developed. Eugenol, a major component of clove oil can act as the most potential bio additive fuel for improving the diesel quality thereby reducing the exhaust emission of the engine. The proposed integrated model includes four lump kinetic model which is plugged with catalyst deactivation model. The reactor design parameters are also included in the integrated model. The effectiveness of the proposed integrated model is compared with the conventional kinetic models and the results are presented. The proposed integrated model is validated against the real time data obtained by conducting an experiment in a real time setup with MoS2(Ni2P) Al-SBA-15(10) as the catalyst. The advantages of the proposed integrated model are highlighted.

Multiscale Modeling of a Direct Nonoxidative Methane Dehydroaromatization Reactor with a Validated Model for Catalyst Deactivation

Due to the recent boom in shale gas production, aromatics production using direct nonoxidative methane dehydroaromatization (DHA) is being investigated extensively. However, due to rapid coke forma...

Kinetic modeling of catalyst deactivation and regeneration of a VOx catalyst during the selective dehydrogenation of propane

Kinetic modeling of catalyst deactivation and regeneration of a VO_x catalyst during the selective dehydrogenation of propane

Application of kinetics and computational fluid dynamics in pinene isomerization

A reliable kinetic model to describe the effects of various factors on the reaction rate and selectivity of pinene isomerization is developed. Furthermore, computational fluid dynamics (CFD) is applied to simulate the solid–liquid dispersion in reactor. The catalyst TiM is obtained by improving the composition and structure of hydrated titanium dioxide. The kinetic equation of pinene isomerization is deduced based on reaction mechanism and catalyst deactivation model. The kinetic equation of pinene isomerization reaction is fitted, and the results show that the fitted equation is correlated with the experimental data. The rate and selectivity of pinene isomerization reaction are affected by the amount of catalyst, deactivation of catalyst, structure of catalyst, reaction temperature and water content of catalyst. The solid–liquid distribution of the reactor is calculated by computational fluid dynamics numerical simulation, and the solid–liquid dispersion in commercial scale reactor is more uniform than that in lab-scale reactor. • Establish a more complete kinetic model by introducing deactivation model • The kinetic model correlates well with experimental data. • The lab-scale reactor and commercial scale reactor are investigated by CFD numerical simulation. • The factors affecting the rate and selectivity of the pinene isomerization reaction are systematically studied.

Full cycle dynamic optimisation maintaining the operation margin of acetylene hydrogenation fixed-bed reactor

Abstract In an acetylene hydrogenation reactor, the slowly falling catalyst activity affects ethylene plant performance in an operating cycle. To maximize the integral economic benefit in a regeneration cycle or achieve the longest regeneration cycle, the full cycle operation optimisation must be a long time-scale dynamic optimisation for which the method of control vector parameterization is adopted. Because of various uncertain disturbances, some distances must be reserved for process constraints and the desired effect of full cycle optimisation is hardly fully achieved. Thus, based on the strictly slowly-time-varying catalyst deactivation model, the operation margin consumption is estimated. Furthermore, a modified full cycle operation optimisation strategy is presented which takes the operation margin consumption as additional constraints. To obtain the maximum integral economic benefit or the longest regeneration cycle, we present a realizable full cycle optimized operation plan that considers the sufficient operation space reserved for uncertain disturbances.

Catalytic Production of Glucose-Galactose Syrup from Greek Yogurt Acid Whey in a Continuous-Flow Reactor.

The hydrolysis of lactose in aqueous solutions and dairy waste streams was studied using Amberlyst 70 as a heterogeneous acid catalyst in a continuous-flow packed-bed reactor. The catalyst was stable during hydrolysis of an aqueous lactose feed but deactivated owing to mineral poisoning when the dairy waste Greek yogurt acid whey (GAW) was used as the feedstock. A catalyst deactivation model was developed and showed that the deactivation of the Amberlyst 70 catalyst was proportional to the amounts of cations, urea and amino acids flowing through the catalyst bed. The Amberlyst 70 catalyst was regenerable with an aqueous acid regeneration treatment. Based on the experimental data, a rigorous technoeconomic analysis was performed for the production of glucose-galactose syrup (GGS) via lactose hydrolysis of GAW using three different catalysts. This approach shows that the GGS produced from GAW could become a valuable revenue stream for Greek yogurt manufacturers.

Activation of catalysts in commercial scale fixed-bed reactors: Dynamic modelling and guidelines for avoiding undesired temperature excursions

During the exothermic gas phase activation (e.g. reduction) or passivation (oxidation) of a catalyst in a commercial scale fixed bed, the interaction of the heat wave propagation phenomenon and the (desired) exothermic gas-solid reaction(s) may give rise to local temperature excursions way beyond the adiabatic temperature rise of the reactions. Inspired by a decoking study by Westerterp et al. (1988), a full dynamic model for generic gas-phase catalyst activation and deactivation (reduction/oxidation) in an adiabatic fixed-bed reactor was developed. Counter intuitive effects were elucidated, e.g. for cases where a lowering of the reactant concentration or the presence of a significant reactor wall heat capacity can lead to a further increase of the maximum catalyst temperature. An easy-to-use expression was derived, initially using simplifying assumptions of full rate control by external mass transfer and neglecting heat losses and reactor wall effects. This was subsequently tested on its adequacy for more general cases accounting for (1) slower reaction kinetics, (2) significant heat losses and (3) the reactor wall heat capacity. Only for the latter effect the original expression had to be adjusted. The modified expression proved to be remarkably robust and remained relevant as a simple tool to prevent local temperature excursions also for slower reaction kinetics and significant heat losses.

Two-component model for catalyst deactivation

Texture evolution of alumina hydrotreating catalyst was theoretically modeled using geometrical characteristics calculated via Monte-Carlo methods and methods of the graph theory. In the prescribed model deactivation was specified by monotonic increase of alumina grain radius, which imitated deposition of coke and metal species onto the pore surface. A novel two-component nonhomogeneous model was designed based on the diffusion of asphaltene molecules inside the cylindrical pellet according to Fick’s law and deposition of the coke particles from heavy oil on the surface of the catalyst. The model resulted in non-monotonous coke distribution with a distinct maximum in the inner region of the pellet, which, nevertheless, shifts to the center at later deactivation stages due to the higher hydrogenation performance of pellet border region. Model can be applied to describe profiles of coke depositions during deactivation process for a pellet with an arbitrary boundary.

Modeling of Catalyst Deactivation in Bioethanol Dehydration Reactor

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 tem...

Effect of temperature on deactivation models of alumina supported iron catalyst during Fischer-Tropsch synthesis

Determination of catalyst deactivation model plays prominent role in process controlling. The aim of this study is to investigate deactivation models of Fe/Al2O3 catalyst at different temperature during the Fischer-Tropsch synthesis. Data analysis determined the suitability of second-order GPLE model to describe deactivation behavior of the catalyst. Comparing model parameters at different conditions demonstrated that the catalyst deactivation rate increased by temperature elevation. Analysis of the models also revealed that the catalyst deactivation involves two stages, the first stage occurs at high temperatures while the next step happens at low temperatures, and the deactivation energy of both stages was calculated.

Pore network modeling of catalyst deactivation by coking, from single site to particle, during propane dehydrogenation

A versatile pore network model is used to study deactivation by coking in a single catalyst particle. This approach allows to gain detailed insights into the progression of deactivation from active site, to pore, and to particle—providing valuable information for catalyst design. The model is applied to investigate deactivation by coking during propane dehydrogenation in a Pt‐Sn/Al2O3 catalyst particle. We find that the deactivation process can be separated into two stages when there exist severe diffusion limitation and pore blockage, and the toxicity of coke formed in the later stage is much stronger than of coke formed in the early stage. The reaction temperature and composition change the coking rate and apparent reaction rate, informed by the kinetics, but, remarkably, they do not change the capacity for a catalyst particle to accommodate coke. Conversely, the pore network structure significantly affects the capacity to contain coke. © 2018 The Authors. AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers. AIChE J, 65: 140–150, 2019