Deactivation function for coking

Pore-averaged deactivation function for coking versus time. Parameter aL From Beeckman and Froment [1982]. 

The kinetics of the coking and the deactivation functions for coking were determined by means of a microbalance. The catalyst was placed in a stainless steel basket suspended at one balance arm. The temperature was measured in two positions by thermocouples placed just below the basket and between the basket and the quartz tube surrounding it. The temperature in the coking experiments ranged from 480°C to 630°C, the butene pressure from 0.02 to 0.25 bar, the butadiene pressure from 0.02 to 0.15 bar. Individual components as well as mixtures of butene and butadiene, butene and hydrogen, and butadiene and... 

The deactivation functions for the isomerisation reactions of n-hexane were shown to be exponential functions of the coke content. The deactivation constant, the parameter of these functions, did not differ significantly for the various isomerisation reactions leading to tertiary carbenium ions. The deactivation constant for the isomerisation to 2,2-di-Me-butane, formed out of a secondary carbenium ion, was larger. 

Pt- and alumina sites was assumed to remain constant i e. Independent of time or coke content. Coking and hydrogenolysis were shown to occur on the B ulle sites, and their deactivation functions were identical exp(-aQCQ). The deactivation function for the... 

When the coke content of the catalyst is measured a distinction can be made between the deactivation function for the main reaction, (p, and that for the coking reaction tpc defined by ... 

Figure 7. Averaged deactivation function for the main reaction as a function of averaged coke content for several site densities a in a single ended pore with length L.

The deactivation function for the dehydrogenation was also determined by means of the microbalance, by measuring simultaneously the coke content and the composition of the exit gases as functions of time. To eliminate the effect of bypassing, the conversions were all referred to the first value measured. Figure 2 shows the relation tHlrn° = u versus the coke content, easily derived from the measurements versus time and coke content versus time. Althoi h... 

The deactivation function for the coking reaction in the absence of diffusion limitations can be written... 

The approach followed in deactivation studies is often different from the one outlined here. The alternate approach does not consider a coking rate equation and uses an empirical time-related deactivation function for the particle or bed O = /( called activity [Szepe and Levenspiel, 1971 Wojchiechowski, 1968]. Linear, hyperbolic or exponential functions of time were used. Deriving the activity O with respect to time gives the corresponding rates of change of the activity and defines a so-called order of deactivation, from which it has been attempted to get some insight into the mechanism of deactivation—an attempt... 

The deactivation function is expressed in terms of the coke content of the catalyst, not in terms of time as has been done frequently. Indeed, time is not the true variable for the deactivation, as discussed earlier. The deactivation functions for the coking used here are still empirical in the sense that they do not explicit the mechanism of the deactivation-site coverage or blocking or both, as will be attempted in Example 5.3.3.B. 

Coke formation on these catalysts occurs mainly via methane decomposition. Deactivation as a function of coke content (see Fig. 3 for Pt/ y-AljO,) seems to involve two processes, i e, a slow initial one caused by coke formed from methane on Pt that is non reactive towards CO2 (see Table 3) In parallel, carbon also accumulates on the support and given the ratio between the support surface and metal surface area at a certain level begins to physically block Pt deactivating the catalyst rapidly. The coke deposited on the support very close to the Pt- support interface could be playing an important role in this process. 

Catalytic oxidative dehydrogenation of propane by N20 (ODHP) over Fe-zeolite catalysts represents a potential process for simultaneous functionalization of propane and utilization of N20 waste as an environmentally harmful gas. The assumed structure of highly active Fe-species is presented by iron ions balanced by negative framework charge, mostly populated at low Fe loadings. These isolated Fe sites are able to stabilize the atomic oxygen and prevent its recombination to a molecular form, and facilitate its transfer to a paraffin molecule [1], A major drawback of iron zeolites in ODHP with N20 is their deactivation by accumulated coke, leading to a rapid decrease of the propylene yield. 

All the previously cited models and works also consider, and some explicitly cite, this assumption—that the catalyst activity varies with time-on-stream (or with coke concentration [12]) in the same manner or with the same deactivation function (VO for all reactions in the network. That is, a nonselective deactivation model is always used. Corella et al. (16) have recently demonstrated that in the FCC process this assumption is not true and that it would be better to use a selective deactivation model. Another work (17) also shows how this consideration, when applied to catalytic cracking, influences the yield-conversion curves. Nevertheless, to avoid an additional complication, we will use in this chapter a nonselective deactivation model with the same a—t kinetic equation and deactivation function (VO for all the cracking reactions of the network. 

A problem with monofunctional reactions, e.g., cracking, alkylation, etc. is that they have a tendency to quickly deactivate because of coke deposition. This problem is usually not of concern with bifunctional reactions, e.g., those that employ a metal function in addition to the acid sites. However, we avoided the use of metal function because of the possible unknown modifications that could be introduced to a given sample by the metal deposition procedure. This is especially important when dealing with samples like VPI-5. Thus, to minimize the rate of deactivation, the alkylation experiments were conducted at 463 K. This low temperature introduces another problem, namely, the adsorption of reactants and products. At the experimental conditions employed here, the catalyst bed becomes saturated at time of 10 minutes or less (depending on sample). From this point onward, deactivation is clearly observable via the decrease in conversion with time. The data reported here were obtained at 11-13 minutes on-line. Since meta-diisopropylbenzene proceeds through several reaction pathways that lead to a number of products, it is most appropriate to compare the catalytic data at the constant level of conversion. Here we report selectivities at approximately 25 % conversion. For each catalyst, the results near 25 % conversion were repeated three times to ensure reproducibility. 

Equations for the kinetic mechanisms of coke formation with the exponential form of the deactivation function are obtained by integrating eqs. (6)—(8) ... 

A trickle-bed reactor was used to study catalyst deactivation during hydrotreatment of a mixture of 30 wt% SRC and process solvent. The catalyst was Shell 324, NiMo/Al having monodispersed, medium pore diameters. The catalyst zones of the reactors were separated into five sections, and analyzed for pore sizes and coke content. A parallel fouling model is developed to represent the experimental observations. Both model predictions and experimental results consistently show that 1) the coking reactions are parallel to the main reactions, 2) hydrogenation and hydrodenitrogenation activities can be related to catalyst coke content with both time and space, and 3) the coke severely reduces the pore size and restricts the catalyst efficiency. The model is significant because it incorporates a variable diffusi-vity as a function of coke deposition, both time and space profiles for coke are predicted within pellet and reactor, activity is related to coke content, and the model is supported by experimental data. 

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