Catalytic Degradation of High-Density ... - ACS Publications

Jan 19, 2008 - Michael D. Wallis, Sandeep Sarathy, Suresh K. Bhatia,* and P. Massarotto. DiVision of Chemical ... Edward Kosior. Nextek Proprietary Li...
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Ind. Eng. Chem. Res. 2008, 47, 5175–5181

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Catalytic Degradation of High-Density Polyethylene in a Reactive Extruder Michael D. Wallis, Sandeep Sarathy, Suresh K. Bhatia,* and P. Massarotto DiVision of Chemical Engineering, The UniVersity of Queensland, Brisbane, QLD 4072, Australia

Edward Kosior Nextek Proprietary Limited, 3 Saint Thomas Street, Bronte, NSW 2024, Australia

Alain Mercier Granit Systems SA, Rue du Grand-Cheˆne 5, CH-1003, Lausanne, Switzerland

The catalytic degradation of high-density polyethylene was conducted in a reactive extruder at reaction temperatures of 425, 450, and 475 °C using silica-alumina as the cracking catalyst. A continuous kinetic model was proposed and compared to the carbon number distribution of the reaction products. The model prediction of the product selectivity described the experimental data well for a reaction temperature of 425 °C; however, it was too simplistic to predict the decrease in C4 and increase in C3 occurring at higher reaction temperatures. The liquid product obtained from the reactive extruder was comparable to gasoline; however, it did show a significantly higher C5 fraction. 1. Introduction Developing environmentally friendly methods for the recycling and disposal of waste plastic is important for both the efficient use of resources and environmental sustainability. A large base of literature is available reporting the influence of various operating variables, reactor designs, and catalyst selections on the product distributions of the catalytic degradation of polyethylene (PE) due to its prevalence in solid municipal waste and simple molecular structure.1,2 Silica-alumina catalysts are some of the most widely investigated solid acid catalysts for PE degradation and are often used to benchmark novel catalysts. Reactive extrusion has been shown to be a flexible and useful method for the degradation of PE. Previously reactive extruders have been used for the thermal and catalytic degradation of PE3,4 and PE/lubricating oil mixtures5 for the production of liquid fuel, as well as a moving bed reactor which conveys both sand and polypropylene for fuel-gas production. However, these studies have not proposed any kinetic model to describe the experimental data obtained. The main advantages of using the reactive extrusion are the controllable residence time of the reactor and the ability to feed and mix very viscous liquids easily. The complex nature of the catalytic degradation of PE along with differences in reactor configuration, starting material, and reporting convention makes the comparison and validation of kinetic models difficult.7 Modeling approaches range from simplistic nth order reaction kinetics to detailed models that extrapolate kinetic rate behavior from that of small model molecules. A full description of the complex reaction mechanism by which PE degrades would require many different rate constants that both are difficult to estimate8 and require very detailed experimental data.7 A balance between complexity and robustness of the kinetic model must be found. The modeling of polymer degradation using continuous kinetics9 has shown to be an effective way to describe the size reduction of the entire * To whom correspondence should be addressed. E-mail: s.bhatia@eng.uq.edu.au.

distribution of molecular sizes. The advantage of using continuous reaction kinetics is that the essential dynamics of the system is captured with a small number of parameters.10 Here we report the kinetics of the catalytic degradation of high-density polyethylene using a continuous kinetic model. Experimental data for the calibration of the kinetic model has been obtained using a reactive extruder.11 This article is structured as follows: section two describes the materials, experimental equipment, and experimental procedures used in all the experiments conducted; section three develops a continuous kinetic model that describes the product carbon number distribution of the reaction products. The model predictions are then compared to the experimental data and the product distribution compared to literature values. 2. Experimental Section 2.1. Materials Characterization. All experiments used highdensity polyethylene (HDPE) obtained from QENOS as HDPE fluff. The molecular weight distribution of the HDPE was determined by high-temperature gel permeation chromatography using a GPCV 2000 fitted with both a refractive index detector and a viscometer. The molecular weight distribution of the HDPE is shown in Figure 1 and had a number average (x˜avg) of 5218 g/mol.

Figure 1. Molecular weight distribution of the HDPE.

10.1021/ie0714450 CCC: $40.75  2008 American Chemical Society Published on Web 01/19/2008

5176 Ind. Eng. Chem. Res., Vol. 47, No. 15, 2008

Figure 2. Pore size distribution of the silica-alumina catalyst determined by ASAP.

Figure 3. Pore size distribution of the silica-alumina catalyst determined by mercury porosimetry.

Silica-alumina with a Si/Al atomic ratio of 3.19 was obtained from Sigma-Aldrich and used as the cracking catalyst. A Micromeritics accelerated surface area and porosimetry analyzer (ASAP) 2010 with liquid argon as the adsorbate and the cylindrical pore Saito/Foley method was used to calculate the pore size distribution of the silica-alumina. The pore size distribution obtained from the ASAP is shown in Figure 2 and indicates a broad distribution of pore sizes with peaks at the pore diameters of 15 and 150 Å. The meso-macroporous pores of the silica-alumina help the polymer access the catalytic sites by minimizing both diffusional and steric hindrances of the bulky HDPE molecules. The bimodal structure in the mesomacroporous range is typical of silica-alumina.1 To test for the presence of large pores beyond the accessible range of ASAP, mercury porosimetry in a Micrometrics 9320 mercury porosimeter was carried out on the silica-alumina. The results of the mercury porosimetry are shown in Figure 3 and agree qualitatively with that obtained from the ASAP. The mercury porosimetry showed that no pores larger than those obtained from ASAP analysis were present. 2.2. Reactive Extruder. Experiments were carried out in a 20 mm diameter constant depth, constant pitch single-screw extruder as shown in Figure 4. The extruder had five controllable heating zones as shown in Figure 4: upper hopper (T1), lower hopper (T2), barrel feed (T3) directly below the hopper; a first reaction zone controlled by thermocouple T4 with two temperature indicators T4A and T4B and a second reaction zone controlled by thermocouple T5 with two temperature indicators T5A and T5B. All thermocouples embedded into the barrel and hopper walls were used to approximate the reactor temperature without interfering with the flow patterns of the reactants. The six barrel thermocouples were distributed 7 cm apart down the length of the 48 cm barrel.

Figure 4. Reactive extruder (HT ) heating tape; T1, T2, T3, T4, T5 ) control thermocouples; T4A, T4B, T5A, T5B ) measurement thermocouples).

The hopper components included two heaters controlled by thermocouples T1 and T2, inlet and outlet valves, and a removable lid with a gasket. The lid of the hopper was fitted with a glass window to allow for visual inspection of hopper contents during the reactor operation. A nitrogen gas supply was fitted to the hopper inlet valve and a pressure indicator and purge line to the outlet valve. This allowed nitrogen to be flushed over the hopper contents during normal operation. At the end of the barrel the die (L-shaped 20 mm tube) was heated to ensure that products could easily flow through into a glass condenser. The glass condenser at the exit of the extruder was immersed in an ice bath, and a gas bag was attached to the condenser exit valve. In a typical experiment the catalyst was thoroughly mixed with HDPE in a paint mixer to achieve a mixture of 2% by weight catalyst. The mixture was then transferred from the paint mixer directly into the hopper of the extruder. The hopper lid was attached with the hopper gas outlet valve closed so that nitrogen would be flushed through the reactor. Nitrogen was introduced via the hopper inlet valve and flowed through the bed of HDPE to the barrel and then through the condenser. This purged the air from the reactor. The nitrogen flow was then turned off and the hopper outlet valve opened so that the HDPE in the hopper was melted under atmospheric pressure. Returning the hopper to atmospheric pressure aided melting and avoided excess nitrogen bubbles being captured in the HDPE melt. The reactor heating zones were activated and set to the conditions of the experiment. The reactor was left for 2 h to completely melt all of the HDPE in the hopper. The molten state was confirmed by visual inspection of the hopper contents through the glass window in the lid of the hopper. Once the contents of the hopper were melted, the hopper pressure was set to 0.1 bar gauge by flowing nitrogen over the hopper contents. The increased hopper pressure allowed the viscous melt to enter the barrel faster, which increased the mass flow rate of the extruder and ensured a more consistent feed rate into the barrel. The nitrogen gas was confined to the hopper and did not pass into the reaction zone as the melt acted as a material seal. After the hopper pressure reached the set point, the screw was started at the desired screw rate. The gas bag and condenser were both replaced after every hour of extruder operation. Products collected within the first hour of operation were disregarded as the reactor was assumed to be at unsteady state. A 100 µL sample of the product gas collected each hour was taken directly from the gas bag and immediately used for compositional analysis. The remaining product gas was then transferred from the gas bag to a calibrated cylinder used to measure the temperature, volume, and pressure

Ind. Eng. Chem. Res., Vol. 47, No. 15, 2008 5177

of the gas. The total amount of product gas (number of moles) for each hour was calculated using the state variables measured by the cylinder and the ideal gas law. The reaction products collected in the condenser were centrifuged to separate any insoluble wax from the liquid product. This was particularly important for the lower temperature runs as some phase separation between a waxy fraction and the liquid was observed at room temperature. The clarified liquid was weighed and sampled for analysis via gas chromatography. The wax fraction when present was also weighed, sampled, and analyzed via gas chromatography. After each experiment was completed, the extruder die was cleaned to remove any accumulated spent catalyst. The reactive extruder feed heating zones (upper hopper, lower hopper, and barrel feed) were maintained at 200 °C for all experiments. A series of experiments were conducted with both the first and second reaction zone control temperatures kept equal, so that the reactor approached isothermal conditions. Reaction zone temperatures 425, 450, and 475 °C were investigated at both 4 and 16 rpm with an extra screw speed of 12 rpm included at a reaction temperature of 475 °C. 2.3. Gas Chromatography. Gas chromatography (GC) was used to determine the carbon number distribution of all the gaseous, liquid, and waxy fractions collected from catalytic degradation of HDPE within the reactive extruder. A Varian CP-3800 fitted with a flame ionization detector and a 50 m paraffin-olefin-naphthene-aromatic (PONA) column of WCOT fused silica with a CP-Sil PONA CB stationary phase was used primarily to analyze the reaction products. During analysis, the gas and liquid samples were injected directly into the column while the wax fraction was dissolved in cyclohexane at 80 °C prior to injection. The composition of the wax fraction was corrected appropriately to remove the cyclohexane solvent. The analysis of each fraction was combined to a single carbon number distribution of the total product for each hour of operation by combining the relative composition from the GC and their respective measured amounts. The carbon number distribution of each experiment was checked for molecules larger than the maximum accessible by the PONA column (greater than 15 carbon number) by injecting samples into a 10 m WCOT fused silica CP-SimDist simulated distillation column. The simulated distillation column could measure to components up to those with a final boiling point of 538 °C. However, negligible components with a carbon number greater than 15 were detected for any of the reaction products. 3. Mathematical Model The aim of the mathematical model developed was to formulate a simple model able to predict the distribution of the product molecules from the reactive extruder. The model utilizes continuous kinetics and assumes that the reactive extruder is a plug flow reactor. The continuous variable which characterizes the reaction mixture was assumed to be molecular weight. The reaction mixture was assumed to consist of linear molecules of differing sizes that undergo binary scission. The adsorption and reaction rate characteristics of the reaction mixture are assumed to be similar to those of linear paraffins, an assumption that has been used previously to approximate the behavior of complex hydrocarbon mixtures found in fluidized catalytic cracker (FCC) feedstocks.12 The continuous kinetic model was assumed to be valid for the entire range of possible molecular weights and thus had a minimum molecular size (x˜min) equal to that of methane (16 g/mol). It is convenient to define a dimensionless size that ranges from zero to infinity. Thus, the

molecular weight of a molecule in g/mol (x˜) was rescaled to a dimensionless size (x) as follows: x)

x˜ - x˜min x˜avg

(1)

The reaction mixture at any time was described by the normalized number of molecules n(x,t) as defined below, in which P(x,t) is defined as the molar concentration of polymer in the reactive extruder with dimensionless size in the range from x to x + dx at time t and y is a dummy variable used for integration. n(x,t) )

P(x,t)





0

(2)

P(y,0) dy

The rate of change of the normalized number of molecules in the reactive extruder at any time t is given by the population balance ∂n(x,t) ) ∂t





0

Ω(x,y) s(y,t) n(y,t) dy - s(x,t) n(x,t)

(3)

where s(x,t) is the rate of scission of a reactant of size x and the breakage kernel Ω(x,y) represents the number of molecules of x produced from breakage of a molecule of a larger size y. The assumed reaction stoichiometry, molecular linearity, and rescaling of molecular size allows the breakage kernel (Ω) originally developed by McCoy and Wang13 to be used without the inclusion of a minimum size. This breakage kernel has been utilized as it is a flexible function that can represent a range of behavior from totally random to midpoint scission. The form presented below is that of the more general function suggested by Diemer and Olson14 in which B(V,V) is the beta function15 of the breakage kernel parameter V. Ω(x,y′) )

2zV-1(1 - z)V-1 , y ′B(V,V)

z≡

x y′

(4)

This form of the breakage kernel is presented to show the potential to relax the linear molecule and binary scission assumptions made in the model to further incorporate more complex reaction mechanisms. The rate of scission of a reactant of dimensionless size x is commonly assumed to be a separable function of x and t of the form shown below.16 s(x,t) ) kr(T) K(x) D(t)

(5)

In the equation above kr(T) is the reaction rate constant with units time-1, which is assumed to be a function of temperature (T) and catalyst reaction rate properties. The function D(t) is a catalyst deactivation function which represents the change in the fraction of active catalytic sites with time. The dimensionless kinetic distribution K(x) describes how the rate of molecular scission depends on molecular size. It is convenient to define a warped time scale or dimensionless time (θ) by combining all of the time-dependent quantities as shown below. dθ ) kr(T) D(t) dt

(6)

The above ordinary differential equation can be solved when the functions D(t) and kr(T) are known for a particular catalyst, feed composition, and reactor configuration. The detailed information required to define these functions is beyond the scope of this article. However, since the aim of the model was to predict the size distribution of the reaction products, this information was not necessary as the dimensionless time scales

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with the rate of reaction and does not impact the relative selectivity of the reaction products. Therefore, the solution to eq 6 does not need to be found explicitly and the value of the dimensionless time can be used as a fitted parameter in the model. The rate of change of the normalized number of molecules in the dimensionless time scale is given below. ∂n(x,θ) ) ∂θ





0

Ω(x,y) K(y) n(y,θ) dy - K(x) n(x,θ)

(7)

A number of simple correlations for the cracking rate of linear paraffins over solid acid catalysts that increase continuously with chain length have been reported.12,17 The relation for the rate of cracking used was that of Abbot and Dunstan12 given below, where Cn represents molecules with n carbon atoms. K(x) ∝ Cn(Cn - 5)

(8)

The form of the equation above was developed from two main assumptions. The first main assumption was that the adsorption constant was proportional to the size of the molecule. The second main assumption was that the reactivity was proportional to the number of crackable bonds (Cn - 5), a concept that is derived from the observation that insignificant quantities of methane and ethane are produced during catalytic degradation. These two assumptions are combined in a reduced form of the Langmuir expression (assuming that the adsorption constant was much less than one) and show good correlation to experimental data for molecules up to 35 carbon numbers. Using the proportionality given in eq 8, the dimensionless kinetic distribution can be written in terms of the dimensionless size x using the molecular weight of pentane (72 g/mol). The dimensionless kinetic distribution is given below.

K(x) )

{

(

x+

)(

x˜min - 2 72 - x˜min x˜xavg x˜avg

)

xg x