Effects of Switching Frequency of a Periodic Switching Polymerization

Article pubs.acs.org/IECR

Effects of Switching Frequency of a Periodic Switching Polymerization Process on the Microstructures of Ethylene−Propylene Copolymers in Polypropylene/ Poly(ethylene-co-propylene) in-Reactor Alloys Zhou Tian,† Xue-Ping Gu,† Gang-Liang Wu,† Lian-Fang Feng,*,† Zhi-Qiang Fan,‡ and Guo-Hua Hu*,§,⊥ †

State Key Laboratory of Chemical Engineering, Zhejiang University, Hangzhou 310027, P. R. China MOE Key Laboratory of Macromolecular Synthesis and Functionalization, Zhejiang University, Hangzhou 310027, P. R. China § Laboratory of Reactions and Process Engineering, CNRS-Nancy University, ENSIC-INPL, 1 rue Grandville, BP 20451, 54001 Nancy, France ⊥ Institut Universitaire de France, Maison des Universités, 103 Boulevard Saint-Michel, 75005 Paris, France ‡

ABSTRACT: This work deals with the effects of the switching frequency of a periodic switching polymerization process (PSPP) with a Ti-based Ziegler−Natta catalyst on the microstructures of ethylene−propylene copolymers in polypropylene/ poly(ethylene-co-propylene) (PP/EPR) in-reactor alloys. The compositions and structures of PP/EPR in-reactor alloys are investigated by solvent fractionation, 13C NMR, gel permeation chromatography (GPC), successive self-nucleation and annealing (SSA) by differential scanning calorimetry (DSC), and statistical deconvolution. The sequence distributions of ethylene− propylene random copolymer (EPR) and ethylene−propylene segmented copolymer (EPS) are successfully deconvoluted from the 13C NMR spectra of fractionated samples. The results are consistent with the expected effects of the switching frequency on the composition and microstructures of EPR and EPS. A higher switching frequency between the homopolymerization of propylene and the copolymerization of ethylene and propylene increases not only the ratio between the EPS and EPR but also the fractions of long PP segments and long PE segments in the EPS. The effect of the mean residence time on the composition and microstructure of PP/EPR in reactor alloys is also discussed.

1. INTRODUCTION The past two decades have seen great academic and industrial interest in polypropylene/ethylene−propylene rubber (PP/EPR) in-reactor alloys because of their excellent properties. They are often made by a multistage polymerization process which consists of the polymerization of propylene in the first stage and the copolymerization of ethylene and propylene in the second stage over the same Ziegler−Natta catalyst system. The resulting product is a mixture of ethylene−propylene random copolymers (EPR), ethylene−propylene segmented copolymers (EPS), and isotactic polypropylene (IPP). Its microstructure is complex, and its morphology is of heterophasic nature.1−11 The two types of ethylene−propylene copolymers with distinct microstructures (EPR and EPS) originate from different groups of catalyst active centers.12,13 Their fractions and microstructures can be controlled by the multicenter nature of the Ti-based Ziegler− Natta catalyst and the polymerization process.1,14 Recently, a multistage sequential polymerization process was proposed to control the morphology and mechanical properties of PP/EPR in-reactor alloys.15 In a previous work, a novel process called “periodic switching polymerization process” (PSPP) was developed to control the compositions and microstructures of PP/EPR in-reactor alloys without any change in the catalyst system.1 The policy of periodic feeding and discharging of monomers was adopted. This work aims at unraveling the mechanism of the PSPP with a Ti-based Ziegler−Natta catalyst through detailed analysis © 2012 American Chemical Society

of the compositions and microstructures of EPR and EPS in PP/EPR in-reactor alloys. The effect of the mean residence time of the gas phase on the compositions of the in situ PP/EPR blends is also studied. The compositions of the alloys and the microstructures of the individual components are characterized by solvent fractionation, gel permeation chromatography (GPC), and 13C NMR. Statistical deconvolution is introduced in order to separate the atactic PP and moderate isotactic PP from the EPR and EPS when calculating the sequence distributions of the latter. The compositional heterogeneities of the EPS are further studied by successive self-nucleation and annealing (SSA) with differential scanning calorimetry (DSC).

2. MECHANISTIC CONSIDERATION It is well-known that a Ziegler−Natta catalyst contains several types of active centers. They may exhibit different steroselectivities, copolymerization kinetics, and abilities for α-olefins to copolymerize with ethylene. On the basis of the multicenter nature of the Ziegler−Natta type of catalyst,12,13,16−22 this work proposes a mechanism for the PSPP (see Figure 1). The catalyst contains two groups of active Received: Revised: Accepted: Published: 2257

August 15, 2011 December 4, 2011 January 4, 2012 January 4, 2012 dx.doi.org/10.1021/ie201821j | Ind. Eng.Chem. Res. 2012, 51, 2257−2270

Industrial & Engineering Chemistry Research

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produced at the centers of group B (see Figure 1g). Meanwhile, some of the living chains formed at the centers of group B in the homopolymerization stage can produce block copolymers of PP and EPS denoted as PP-b-EPS during the copolymerization stage (Figure 1h). The same is true for Figure 1d. If the above mechanism is correct, it is expected that an increase in the switching frequency of a PSPP will lead to the following results: (1) An increase in the EPS/EPR ratio. In the case of a PSPP (switching frequency >1), since propylene is present in an alternative manner over time, dormant sites are formed in an alternative manner (Figure 1b), limiting the formation of the EPR. On the other hand, the EPS are formed through the copolymerization of propylene with ethylene by centers of group B (Figure 1g) and the switching between propylene and the mixture of ethylene and propylene. An increase in the switching frequency increases the probability of the formation of the PP-b-EPS (Figure 1d,h), a block copolymer of long PP segments and EPS. It should be pointed out that PP-b-EPS is also a kind of EPS because of similarity in solubility in the solvent used for fractionation. (2) An increase in the content of long PP segments in the EPS. This is because an increase in the switching frequency increases the probability of the formation of PP-b-EPS, which has long PP segments. (3) Improved compatibility between EPR and PP owing to an increase in the content of PP-b-EPS, which may act as a good compatibilizer for the PP and EPR alloys.

Figure 1. Mechanism of the periodic switching polymerization process with a Ti-based Ziegler−Natta catalyst.

centers: A and B. The centers of group A have poor stereoselectivity but easily copolymerize α-olefins with ethylene. They are formed and decay rapidly. In contrast, the centers of group B exhibit high stereoselectivity but poor copolymerization ability. They are formed and decay much more slowly that the centers of group A. A PSPP is composed of the homopolymerization of propylene and the copolymerization of ethylene and propylene.1 The key factor of the PSPP is the frequency of switching between the homopolymerization of propylene and the copolymerization of ethylene and propylene. Concerning the propylene homopolymerization stage, some of the centers of group A generate atactic PP (Figure 1a) while most of them are dormant due to the 2, 1 propylene (secondary) insertion (Figure 1b). In contrast, the centers of group B generate isotactic PP, which is the main component of the polymer product during the homopolymerization (Figure 1c). As for the ethylene and propylene copolymerization stage, the presence of ethylene at this stage can awake a large number of the dormant sites of group A (Figure 1f). Therefore, EPR may originate from two parts: the centers of group A that are formed during the copolymerization stage (Figure 1e) and the dormant sites that are awakened by ethylene (Figure 1f). EPS is mainly

3. EXPERIMENTAL SECTION Materials. The catalyst system used was a high activity spherical Ziegler−Natta catalyst, supplied by BRICI, SINOPEC (Beijing, China), with TiCl4 supported on MgCl2. Triethyl aluminum was used as a cocatalyst and dicyclopentyl dimethoxy silane, a so-called D-donor, was used as an external electron donor. In all polymerization runs, the Al/Ti and Si/Ti molar ratios were kept constant at 100 and 5, respectively. The fraction of titanium of the catalyst was 2.7 wt %. n-Heptane was used as a solvent for the catalyst system. Periodic Switching Polymerization Process. Figure 2 shows the periodic switching polymerization process (PSPP) of PP/EPR in-reactor alloys. Details can be found in ref 1. Figure 3 is the experimental setup. The polymerization reactions were carried out in a 0.8 L stainless steel autoclave reactor from Büchi. The batch reactor was equipped with a helical impeller agitator, mounted on a stirrer shaft. Electronic pressure gauges and thermocouples were used to measure the pressure and temperature of the monomers in the reactor. The temperature of the reactor was kept constant with circulating water through two thermostatted water baths. The polymerization procedure was composed of the following

Figure 2. Schematic representation of a periodic switching polymerization process (PSPP). 2258

dx.doi.org/10.1021/ie201821j | Ind. Eng.Chem. Res. 2012, 51, 2257−2270


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Figure 3. Polymerization setup. I: 0.8 L autoclave polymerization reactor. II: Control system. III: Gas tanks. IV: Gas purification systems.

could be calculated by the following equation:

three steps: prepolymerization of propylene in slurry, homopolymerization of propylene in slurry, and gas phase polymerization in a switching mode. The temperature and pressure of propylene in the prepolymerization stage were 20 °C and 1 atm, respectively. At the end of the prepolymerization (typically 20 min), the reactor was brought to the slurry propylene homopolymerization conditions, typically 60 °C and 0.6 MPa. The propylene homopolymerization lasted 60 min. The prepolymerization and homopolymerization of propylene were operated in a semibatch mode; namely, propylene was continuously fed to the reactor from its top, and there was no discharge of monomer or product from the reactor. At the end of the homopolymerization of propylene in slurry, propylene and the solvent were removed by evacuation for 10 min. The homopolymerization of propylene in the gas phase and the copolymerization of ethylene and propylene in the gas phase then began to proceed in an alternative manner (switching mode). The switching between propylene and a mixture of ethylene and propylene was carried out using tanks 1 and 2 through valves A and B. Those two valves could operate in an alternative manner using four timer relays (H3BA-N/N8H). For example, propylene of a constant pressure (0.3 MPa or 0.4 MPa) was continuously fed to the bottom of the reactor at 60 °C through valve A, and the unreacted ones were continuously discharged from its top. After a given period of time I for the homopolymerization of propylene in the gas phase, the process was switched to the copolymerization of ethylene and propylene in the gas phase by feeling a mixture of propylene and ethylene of a constant composition (propylene/ethylene molar ratio = 1.5) and a constant pressure (0.3 MPa or 0.4 MPa) to the reactor at 60 °C through valve B. After a given period of time II, the polymerization process was switched back to the homopolymerization of propylene in the gas phase. The above polymerization process procedure was repeated until the total polymerization time reached 80 min and the ratio between times I and II was 3. The mean residence time (τ) of the gas phase in the reactor is also a key process parameter for a periodic switching polymerization process. In order to investigate its effect, two sets of experiments were designed. Table 1 shows the polymerization conditions. It also shows a set of polymerization experiments reported in a previous paper.1 This allows comparing polymer products obtained with three different values of τ. The latter

τ=

V αβF

(1)

where V is the reactor volume and F is the feed rate of monomers calibrated by nitrogen in the standard state. The unit of F is standard liters per minute (SLM). The parameters α and β are the conversion coefficients of the gas flow rate and state, respectively. According to eq 1, an increase in the feed rate of monomers (an increase in α) or a decrease in the gas phase pressure (an increase in β) could be used to reduce the transition time during the switching between propylene and the mixture of propylene and ethylene. Solvent Fractionation. A polymer sample of approximately 1.5 g was fully dissolved in 200 mL of boiling n-octane and then precipitated by gradual cooling of the solution to room temperature overnight. The insoluble part was separated from the solution by centrifugation and filtration. The fraction dissolved in n-octane was recovered from the solution by rotating evaporation. Both the insoluble and soluble fractions were vacuum-dried. The soluble fraction was designated as Fraction 1. The insoluble one was further fractionated by n-heptane into n-heptane soluble (Fraction 2) and insoluble fractions (Fraction 3) using a modified Kumagawa extractor.23 The n-heptane soluble fraction was obtained by rotating evaporation, and the insoluble one was recovered from the extractor. They were vacuum-dried and weighed. The above solvent fractionation procedure allowed one to obtain the following three fractions: Fraction 1 (n-octane soluble), Fraction 2 (n-heptane soluble), and Fraction 3 (nheptane insoluble). A polypropylene homopolymer produced with the same catalyst system and operating conditions was also fractionated into the following three fractions: n-octane soluble, n-heptane soluble, and n-heptane insoluble. Gel Permeation Chromatography. The molar mass and molar mass distribution of the polymers were measured by gel permeation chromatography (GPC) in a PL 220 instrument (Polymer Laboratories Ltd.). Samples were dissolved in 1,2, 4-trichlorobenzene at 150 °C and passed through three linear Polymer Laboratories columns which were calibrated with polystyrene standards and operated with a flow rate of 1 mL/min. 2259



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Table 1. Operating Conditions for the Periodic Switching Polymerization Process retention time (min) sample

pressure,a MPa

feed rate,b SLM

mean residence time,c min

switching frequency

propylene homopolymerization

ethylene−propylene copolymerization

1 2 3 4 5 6 7 8 9 Ad Bd Cd Dd

0.3 0.3 0.3 0.3 0.3 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4

8 8 8 8 8 10 10 10 10 6 6 6 6

0.5 0.5 0.5 0.5 0.5 0.6 0.6 0.6 0.6 1.0 1.0 1.0 1.0

1 4 8 12 20 1 4 12 20 1 4 8 20

60 15 7.5 5 3 60 15 5 3 60 15 7.5 3

20 5 2.5 1.7 1 20 5 1.7 1 20 5 2.5 1

Pressure of the gas phase polymerization in the circulating mode. bLiters per minute at the standard state: 0.1 MPa, 23 °C, and nitrogen criteria. Mean residence time of the mixture of ethylene and propylene in the gaseous phase is calculated according to eq 1. The reactor volume is 0.8 L; the value of α is 0.46 and that of β is 0.4 for 0.3 MPa and 60 °C and 0.3 for 0.4 MPa and 60 °C. dSamples A−D are from a previous work.1 a c

13

C NMR Characterization. 13C NMR spectra were recorded on a Varian Mercury 300-plus spectrometer at a resonance frequency of 75 MHz. o-Dichlorobenzene-d4 was used as a solvent, and the concentration of the polymer in the solution was 10 wt %. The spectra were recorded at 120 °C with hexamethyldisiloxane as an internal chemical shift reference. Cr(acac)3 was used to reduce the relaxation time of carbon atoms, and the delay time was set as 3 s. The pulse angle was 90°, and typically, 6000 transients were collected. Successive Self-Nucleation and Annealing (SSA). Differential scanning calorimetry of type TA-Q200 DSC apparatus was used for measuring the thermal properties of PP/EPR in-reactor alloys. About 4−6 mg of the sample was sealed in an aluminum pan. The precision of the temperature measured was ±0.05 °C. The SSA was performed according to the following procedure: samples were first held at 200 °C for 5 min and then cooled to 25 °C at a rate of 10 °C/min to create an initial “standard” thermal history. They were heated to a prescribed first self-seeding temperature (Ts) at a rate of 10 °C/min and were held at that temperature for 5 min. This step resulted in partial melting and annealing of unmelted crystals while some of the melted species might isothermally crystallize. Crystallization after the self-nucleation was achieved by subsequent cooling of the samples to 255 °C at a rate of 10 °C/min. The first Ts was set at 170 °C; the fraction window was 5 °C, and the annealing time was 5 min. The scanning rate used during the thermal conditioning steps was 10 °C/min. The temperature for the thermal fractionation ranged from 170 to 25 °C. After the completion of the thermal fractionation process, the samples were heated from 25 to 200 at 10 °C/min and the corresponding endothermic curves were recorded.

PP from EPR or mi-PP from EPS. In this work, a methodology is developed that combines deconvolution and solvent fractionation in order to assess the sequence distributions of the EPR and EPS. Markovian statistics are often utilized to fit polymer sequence distribution data24−28 but are rarely employed in a deconvolution process to determine the compositions of a mixture of copolymers and homopolymers. An exception is that Randall proposed a deconvolution procedure using the first order Markovian model to determine the compositions of highimpact polypropylenes.29 In this work, the PP/EPR in-reactor alloys are first separated into three fractions: the n-octane soluble Fraction 1 (mixture of EPR and a-PP), the n-heptane soluble Fraction 2 (mixture of EPS and mi-PP), and the insoluble Fraction 3 (hi-PP). For each of the above two solvent soluble fractions, the contribution of aPP and mi-PP to the total PPP triad is designated as PPPx. The aim of the deconvolution is to eliminate the effects of a-PP and mi-PP on the triad distributions of EPR and EPS, respectively. On the basis of the triad sequence distributions of Fractions 1 and 2 obtained from 13C NMR, the deconvolution procedure was carried out according to Figure 4. The key of the procedure is the deconvolution equations. For example, when the first Markovian model is chosen to describe the triad distribution of a copolymer of ethylene and propylene (see details in Appendix 1), the corresponding equations are as follows:

([EEE]mix /(1 − [PPPx])) = [EEE]cor = [EEE]cal = Ppe(1 − Pep)2 /(Ppe + Pep)

4. DECONVOLUTION USING STATISTICAL MODELS The PP in a PP/EPR alloy may be composed of atactic PP (a-PP), isotactic PP with moderate iso-regularity (mi-PP), and isotactic PP with high iso-regularity (hi-PP). The solvent fractionation cannot separate the a-PP from the EPR. It cannot separate the mi-PP from the EPS either. There are no reports on methods allowing for successful and quantitative separation of a-

(2)

([PEE + EEP]mix /(1 − [PPPx])) = [PEE + EEP]cor = [PEE + EEP]cal = 2PpePep(1 − Pep)/(Ppe + Pep) 2260

(3)



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nonlinear least-squares method. The objective function to minimize is as follows: 6

f = min ∑ ([triadcor]i − [triadcal]i )2 (8)

i=1

where “triad” represents a triad sequence distribution, for example, [EEE]. The values of the parameters, Ppe, Pep, and the PPPx triad, can be obtained by iteration upon minimizing the standard deviations between the calculated and corrected triad sequence distributions. The two first order Markovian statistical parameters, Ppe and Pep, are allowed to vary between zero and one, while PPPx is between zero and PPPmix. Table 2 summarizes various statistical models used for describing the triad distributions of copolymers.24−28 Pmn designates the Table 2. Various Statistical Models and Their Parameters types

models a

single site

M1 M2b

parameters

references

Pep, Ppe Pppe, Ppep, Pepe, Peep

29 24

parameters

Figure 4. Diagram of the deconvolution procedure.

P-sitec

E-site

fractiond

references

two sites

BBe BMf MMg

Pe1 Pe Pep1, Ppe1

Pe2 Pep, Ppe Pep2, Ppe2

fp fp fp

27 28 28

First order Markovian model. bSecond order Markovian model. P-site polymerizes propylene preferentially, and the other site (E-site) polymerizes ethylene preferentially. dMolar fraction of copolymer produced at P-site. eBB represents that the copolymers produced at the two sites (E-site and P-site) follow the Bernoullian model. fBM represents that the copolymer produced at P-site follows the Bernoullian model and that the one produced at E-site follows the first Markovian model. gMM represents that both the copolymers produced at the two sites (E-site and P-site) follow the first Markovian model. c

= [PEP]cor = [PEP]cal (4)

([EPE]mix /(1 − [PPPx]))

probability of an n-monomer to be added to an m-monomer-ended chain, and Pkmn is the probability of an n-monomer to be added to an m-monomer-ended and k-monomer peultimate-ended chain.

= [EPE]cor = [EPE]cal = PepPpe2/(Ppe + Pep)

models

a

([PEP]mix /(1 − [PPPx]))

= Pep2Ppe/(Ppe + Pep)

types

(5)

5. RESULTS AND DISCUSSION Fractionation of PP/EPR In-Reactor Alloys. Figure 5 shows the results of the fractions of the PP/EPR alloys

([PPE + EPP]mix /(1 − [PPPx])) = [PPE + EPP]cor = [PPE + EPP]cal = 2PpePep(1 − Ppe)/(Ppe + Pep)

(6)

(([PPP]mix − [PPPx])/(1 − [PPPx])) = [PPP]cor = [PPP]cal = Pep(1 − Ppe)2 /(Ppe + Pep)

(7)

where the subscript “mix” represents the triad distributions of Fractions 1 or 2 obtained by 13C NMR, “cor” is for those of the pure EPR or EPS (after correction of PPPx), and “cal” is for those calculated by the first Markovian model. In the case of the first order Marovian model, there are six eqs 2−7 for three parameters, Ppe, Pep, and PPPx. The degree of freedom is less than zero. Therefore, they are determined by a

Figure 5. Effect of the switching frequency on the mass percentages of Fractions 1 and 2 for samples 1−5, respectively.

(samples 1−5) obtained by the solvent fractionation. It is expected that Fraction 1 is mainly composed of the amorphous 2261



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EPR and atactic polypropylene homopolymer (a-PP) while Fraction 2 is composed of the semicrystalline EPS and likely isotactic polypropylene with moderate isotacticity (mi-PP). It is noted that Fraction 1 decreases with increasing switching frequency whereas Fraction 2 has an opposite trend. This is in line with the first effect of switching frequency expected from the mechanism of the PSPP outlined above; namely, the EPS/EPR ratio increases with increasing switching frequency. Effects of the Mean Residence Time of the Gas Phase. The mean residence time of the gaseous monomers is directly related to the time in which a prescribed monomer composition can be reached when the propylene feed (homopolymerization of propylene in the gas phase) is switched to the feed of a mixture of ethylene and propylene (copolymerization of ethylene and propylene in the gas phase) or vice versa. This transition time may affect the composition of the monomers in the gas phase during the transition period and consequently the composition of PP/EPR in-reactor alloys during that period of time. Figure 6 shows the effect of the mean residence time (τ) on the composition of the gas phase for two different switching frequencies (1 and 4). In the case of a low switching frequency of 1, the total transition time is negligible compared to the total polymerization time, whatever the value of τ (0.5 or 1 min). In other words, the time during which the real composition of the monomers is different from the targeted one is negligible. Note that the case of τ = 0 can only exist conceptually and cannot exist in practice. It is used as an idealized reference. In the case of a higher switching frequency of 4, the higher the value of τ, the more important the total transition time becomes compared to the total copolymerization time. In the case of τ = 1 min, the total transition times accounts for a great part of the total polymerization time. This means that the time during which the real composition of the monomers is different from the targeted one is no longer negligible. In the copolymerization stage, the composition of propylene is higher than the targeted one while that of ethylene is lower than the targeted one. In the hopolymerization stage, the trend is the opposite. Figure 7 shows the effect of the mean residence time on the ratio between Fractions 2 and 1 which corresponds more or less

Figure 7. Effect of the mean residence time on the ratio of Fraction 2 to Fraction 1.

to the EPS/EPR ratio. In the case of the longest mean residence time (τ = 1 min), the ratio between Fractions 2 and 1 increases remarkably with increasing switching frequency. It only increases to a limited extent when the mean residence time is shorter (τ = 0.6 or 0.5 min). The EPS/EPR ratio is dictated by two factors: switching frequency and transition time. As discussed above, the latter is related to the mean residence time and switching frequency. An increase in switching frequency leads to an increase in the formation of PP-block-EPS at group B centers, as shown in Figure 1d,h. On the other hand, during the transition period, the gas phase is composed of propylene. As a result, a fraction of the EPR formed at group A centers under this condition may contain a high content of propylene and consequently may remain in Fraction 2 after the solvent fractionation. The longer the mean residence time and switching frequency, the longer is the total transition time and consequently the higher the fraction of the insoluble EPR is expected to be. In the case of a long mean residence time of τ = 1 min, an increase in either switching frequency or the mean residence time leads to an increase in EPS/EPR, especially the second one. In the case of a shorter mean residence time of τ = 0.5 min, the influence of the second factor becomes much less important because the time necessary

Figure 6. Schematic representation of the effect of the mean residence time on the composition of the monomers in the gas phase. 2262



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Determination of the Compositions of Fraction 1 and Fraction 2. To confirm the compositions of Fractions 1 and 2, a polypropylene homopolymer obtained by the PSPP under the same conditions as those for the PP/EPR alloys is fractionated into three fractions: a-PP, mi-PP, and hi-PP (see Experimental Section). Figure 9 compares the GPC curves of the fractions of the neat PP homopolymer with those of the corresponding ones for sample 1. The GPC curve of Fraction 1 of sample 1 exhibits a single peak, despite the fact that it may contain two different types of polymers, namely, a-PP and EPR, and that their molar masses could differ significantly. This could be explained by the fact that the amount of a-PP is much lower than that of EPR. Unlike Fraction 1, the GPC curve of Fraction 2 of sample 1 shows two peaks corresponding to mi-PP and EPS, respectively. Elimination of a-PP from Fraction 1 (Mixture of EPR and a-PP) by Deconvolution. Figure 10 shows the triad distributions (mol %) of Fraction 1 of samples 1−5 before and after the triad sequence distributions are corrected for [PPPx]. The detailed deconvolution results are gathered in Table A1 of Appendix 2. The first order Markovian model describes well the sequence distributions after correction for PPPx upon using two probability parameters, Pep and Ppe. The reactivity ratio product is close to 1, indicating that EPR exhibits both a random sequence distribution and a narrow compositional distribution. From Figure 10b, the diad distributions of the five samples are calculated and the results are shown in Table 3 ([PP], [PE + EP], and [EE]). It is inferred that the group of these active centers preferentially promotes the copolymerization between propylene and ethylene, since the sum of the PE and EP diads, [PE + EP], accounts for the biggest part of the sequence distributions. Elimination of mi-PP from Fraction 2 (Mixture of EPS and mi-PP) by Deconvolution. Figure 11a shows the triad sequence distribution of Fraction 2 measured by 13C NMR. The triad [EEE] and [PPP] strongly dominate the mixture, indicating that Fraction 2 mainly contains long PE segments and PP ones. The first order Markovian model (M1) has

for the real composition of the monomers in the gas phase to reach the targeted one is much shorter. Thus, the EPS/EPR increases only slightly with increasing switching frequency. To further confirm the above interpretation, the effect of the mean residence time on the ethylene content in copolymers was analyzed. Figure 8 shows that, in the case of the longest mean

Figure 8. Effect of the mean residence time on the ethylene content in Fractions 1 and 2.

residence time of τ = 1 min, the ethylene content in copolymers decreases remarkably with increasing switching frequency. This indicates that the transition time becomes very important compared with the polymerization time, especially at high switching frequency. In the case of the shortest mean residence time of τ = 0.5 min, the ethylene content in copolymers decreases slightly, indicating that the change in composition of the gas phase is small. Therefore, in order to reduce the undesired effect of the transition time on the analysis of the composition and microstructures of PP/EPR in reactor alloys, the set of experiments with the shortest mean transition time (τ = 0.5 min) will be chosen for the subsequent discussion.

Figure 9. Comparison of GPC curves of three different fractions between the PP homopolymer and sample 1. 2263



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Figure 11. Triad sequence distributions of Fraction 2 for samples 1−5: (a) before correction for PPPx (measured directly by 13C NMR) and (b) after correction for PPPx.

Figure 10. Triad sequence distributions of Fraction 1 for samples 1−5: (a) before correction for PPPx (measured directly by 13C NMR) and (b) after correction for PPPx.

for samples 1−5. Figure 11b shows the corrected triad sequence distributions. The [EEE] and [PPP] triads dominate the triad sequences, corroborating the conclusion that the copolymer of ethylene and propylene in Fraction 2 is a block copolymer. Characterization of EPS by SSA. Figure 12 shows the SSA results for Fraction 2. Multiple melting peaks are observed for each

Table 3. Diad Sequence Distributions and Reactivity Ratio Product of EPR for Samples 1−5 sample

PP

EP + PE

EE

rerp

1 2 3 4 5

25.9 34.5 35.5 39.2 32.1

49.3 45.7 44.7 42.6 44.4

24.8 19.9 19.9 18.2 23.6

1.1 1.3 1.4 1.6 1.5

encountered problems that do not exist for Fraction 1 which is a mixture of EPR and a-PP. It yields zero for PPPx and fits the overall distribution as a single component (EPS) (see Table A2 in Appendix 2). When the method proposed by Randall29 is adopted, the deconvolution procedure still does not yield a satisfactory solution. It is inferred that Fraction 2 contains block copolymers of ethylene and propylene or its composition is very heterogeneous. In either case, the first order Markovian model fails. To overcome these problems, the second order Markovian model (M2) is used. It deconvolutes the mixtures of EPS and mi-PP satisfactorily

Figure 12. DSC endotherms of Fraction 2 for samples 1−5 after the SSA treatment. 2264



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annealing step. The peaks below 130 °C represent the crystalline PE segments in the EPS, and those above that temperature correspond to the crystalline PP segments in the EPS or mi-PP. Each endotherm represents a population of crystals with almost the same thermodynamic stability. In order to assign these peaks, the mi-PP from the polypropylene homopolymer is also subjected to SSA (Figure 13). Seven melting peaks appear, and they are all above

gathers the results of crystalline ethylene sequence length (CESL) and lamellae thickness of the EPS for samples 1−4. It does not contain the results of CESL for the EPS of sample 5. This is because in this case some of the melting peaks of the PE segments and PP ones overlap below 130 °C (see the inset in Figure 12). The average ethylene sequence length determined by the SSA is about 4−6 times that calculated from the results of 13C NMR. This could be explained as follows. EPS contains not only crystalline PE segments and PP ones but also a large amount of random sequences that could not crystallize. Furthermore, although the values of the average CESL of the EPS in all the samples are almost the same (from 30.8 to 33.5), those of the sequence length distribution are different. For example, the EPS in sample 4 has a higher content of longer CESL (30−120) than sample 1 (Figure 14). In other words, the PE

Figure 13. Comparison of the DSC endotherms of the moderate isotactic polypropylene of the polypropylene homopolymer and Fraction 2 of sample 1 after the SSA treatment.

120 °C. This means that the melting endotherms below 120 °C in Fraction 2 of PP/EPR in-reactor alloys can be attributed to the EPS. As the normalized area under each endothermic peak is proportional to the number of lamellae that melt within the prescribed temperature interval, the lamellae thickness and crystalline methylene sequence length (CMSL) and their distributions can thus be calculated (Appendix 3).30,31 Table 4

Figure 14. Crystalline ethylene sequence length distributions of EPS.

segments of the EPS in sample 4 are longer than those in sample 1, despite the fact that its [EEE] triad is lower (see Figure 11b). Considering the results of Figure 11b, it is interesting to note that an increase in the switching frequency leads to an increase in both the long PP segments and PE segments. The long sequence of PE or PP segments can enhance the compatibility between the PP matrix and the EPR dispersed phase in PP/EPR alloys. This is expected to be a key to reaching high toughness with a relatively low ethylene content in PP/EPR alloys.1 Effects of Switching Frequency. The results of PPPx from the data of Fractions 1 and 2 can be used to determine the mass percentages of the a-PP and mi-PP in a PP/EPR alloy, respectively:

Table 4. Crystalline Ethylene Sequence Length and Lamellar Thickness Distributions of EPS ethylene sequence length

methylene sequence length

lamellar thickness

sample

SSAa

NMRb

L̅n (nm)

L̅w (nm)

I

L̅n (nm)

L̅ w (nm)

I

1 2 3 4

30.8 32.9 33.4 33.5

7.3 6.6 6.7 5.7

7.8 8.3 8.5 8.5

11.9 12.2 12.0 12.2

1.52 1.46 1.42 1.44

4.3 4.5 4.6 4.6

5.2 5.3 5.4 5.4

1.19 1.18 1.17 1.17

a

Average ethylene sequence length, calculated from SSA. bAverage ethylene sequence length, measured by 13C NMR.

a‐PPwt % =

mi‐PP wt % =

{Fraction 1 × 3 × [PPPx]} ×% [3([PPPx] + [PPP] + [PPE + EPP] + [EPE]) + 2([PEP] + [PEE + EEP] + [EEE])]

{Fraction 2 × 3 × [PPPx]} ×% [3([PPPx] + [PPP] + [PPE + EPP] + [EPE]) + 2([PEP] + [PEE + EEP] + [EEE])]

After the mass percentages of the a-PP, mi-PP, and their contributions to the total PPP triad intensity are established, it is straightforward to determine the mass percentages of the EPR and EPS, on the one hand, and those of ethylene in the

(9)

(10)

EPR and EPS, on the other hand. Table 5 summarizes the compositions of samples 1−5 in terms of the mass percentages of the a-PP, EPR, mi-PP, and EPS, on the one hand, and in terms of the ethylene content in the sum of all copolymers of 2265



Article

the EPR and EPS as a function of the switching frequency. In the case of the EPR, using the first order Markovian model, the switching frequency has a small effect on the probabilities, Pee, and Ppp, where Pee = 1 − Pep and Ppp = 1 − Ppe, respectively. The reactivity ratio product rerp can be calculated as follows:

Table 5. Compositions for Samples 1−5 by Mass Percent sample

EPR

EPS

a-PP

miPP

1 2 3 4 5

17.6 14.8 15.3 16.3 15.0

3.7 4.0 4.9 4.7 5.8

3.6 1.1 0.4 0.1 2.6

1.7 1.5 1.9 1.8 1.5

hi-PP

ethylene unit in all copolymers

ethylene unit in PP/ EPR

73.4 78.6 77.5 77.1 75.1

43.6 37.8 37.3 33.4 35.5

9.3 7.1 7.6 7.0 7.4

rerp =

PeePpp = PepPpe [EP + PE]2 4[EE][PP]

(11)

In Randall’s work, the catalyst system was similar to the one used in this work, the reactivity ratios rerp were close to 1.1.29 In this work, they range from 1.1 to 1.6, revealing a random sequence distribution and a narrow composition distribution. These results agree with Figure 16. As for the EPS, an increase in the switching frequency leads to an increase in Pppp and a decrease in Peee (see Figure 17b). In other words, an increase in the switching frequency increases the probability of forming long PP segments in EPS. This result is consistent with Figure 11b and the second effect of the switching frequency expected from the mechanism for a PSPP.

ethylene and propylene and in PP/EPR alloys, on the other hand. From Figure 15a, an increase in the switching frequency leads to a decrease in the fraction EPR and an increase in the fraction of EPS. From Figure 15b, the EPS/EPR mass ratio increases with increasing switching frequency. These results are in line with Figure 7 and the first expected effect of switching frequency for a PSPP. Figure 16 shows the effect of the switching frequency on the ethylene contents of EPR and EPS before and after the elimination of the effects of a-PP and mi-PP. The ethylene content in EPR is relatively insensitive to the switching frequency whereas that in EPS decreases remarkably. The result is consistent with the second expected effect of switching frequency for a PSPP. Figure 17 shows the values of the statistical models parameters that describe the triad sequence distributions of

6. CONCLUSIONS This paper reports on the mechanism of a periodic switching polymerization process (PSPP) with a Ti-based Ziegler−Natta catalyst and the effects of the switching frequency on the compositions and microstructures of ethylene−propylene copolymers in PP/EPR in-reactor alloys. A methodology that combines solvent fractionation, 13C NMR, and statistical

Figure 15. Effect of the switching frequency on the contents of EPR and EPS and the EPS/EPR ratio for samples 1−5. (a) Contents of EPR and EPS; (b) EPS/EPR mass ratio.

Figure 16. Effect of the switching frequency on the ethylene contents in EPR and EPS for samples 1−5: (a) before elimination of the effects of a-PP and mi-PP; (b) after elimination of the effects of a-PP and mi-PP. 2266



Article

Figure 17. Effect of the switching frequency on the statistical model parameters for describing copolymers of (a) EPR and (b) EPS for samples 1−5.

E or P. Therefore,

deconvolution is developed to determine the compositions and sequence distributions of five basic components of a PP/EPR in-reactor alloy: ethylene−propylene random copolymer (EPR), ethylene−propylene segmented copolymer (EPS), atactic polypropylene (a-PP), polypropylene with a moderate level of isotacticity (mi-PP), and polypropylene with a high level of isotacticity (hi-PP). The effects of the mean residence time of the gas phase and switching frequency on the compositions of PP/EPR inreactor alloys are investigated. When the mean residence time is long, the transition time necessary for the targeted composition of the monomers to be reached is long compared to the total copolymerization time. This is especially true when the switching frequency is high. Therefore, an increase in switching frequency together with a corresponding increase in the transition time leads to a remarkable increase in the EPS/EPR ratio and a decrease in the ethylene content in the copolymers. In the case of short mean residence time, the effect of the transition time on the targeted composition of the monomers in the gas phase is small and the results obtained are in line with the proposed mechanism in terms of the effects of the switching frequency on the compositions and microstructures of ethylene−propylene copolymers in PP/ EPR in-reactor alloys. An increase in switching frequency increases the EPS/EPR ratio and the content of long PP segments in the EPS.

Pp = PpPpp + PePep

(13)

Pe = PpPpe + PePee

(14)

From the above equations, one obtains

Pp = Pep/(Pep + Ppe)

(15)

Pe = Ppe/(Pep + Ppe)

(16)

A sequence of any length in a copolymer chain can now be defined in terms of only two transition probabilities, Pep and Ppe. The first order Markov description for a normalized [EEE] triad distribution is given below:

[EEE] = PePeePee=Ppe(1 − Pep)2 /(Pep + Ppe)

The other triad distributions can be deduced in a similar manner.

■

APPENDIX 2

Table A1. First Order Markovian and Observed Triad Sequence Distributions (mol %) for Fraction 1 in Samples 1−5 after Correction of PPP for PPPx, the Homopolymer Contribution

■

sample modela

APPENDIX 1 According to Randall’s work,32 in a first order Markovian statistical scheme, the probability for finding the first unit of the sequence is defined as follows:

1

2

M

M

Pp = probability of finding a P unit at any location in a 3

copolymer chain Pe = probability of finding a E unit at any location in a

4

M

M

copolymer chain 5

and

Pp + Pe = 1

(17)

(12)

M

EEE mixd cor cal mix cor cal mix cor cal mix cor cal mix cor cal

12.0 14.4 12 9.9 10.6 8.7 8.8 9 9.5 7.3 7.3 8.8 12.5 14.7 11.9

SSc/ PEE + PPE + EEP PEP EPE EPP PPP PPPxb 10−4 17.2 20.7 24.4 17.4 18.6 20.9 21.2 21.7 21.1 21.7 21.8 19.9 15.2 17.8 22.5

11.9 10.1 14.3 12.1 12.5 11.9 12.7 8.6 13.5 9.2 12.5 9.1 11.2 8.4 11.5 8.6 11.7 8.6 10.4 7.6 10.4 7.6 11.2 7.5 11.3 8.1 13.3 9.5 10.7 8.8

20.8 25 25.5 25.6 27.3 27.7 26.7 27.4 27.3 27.3 27.4 27.4 21.6 25.3 26.3

28.1 13.4 13.7 25.8 20.8 21.1 23.8 21.8 21.7 25.6 25.5 25.2 31.2 19.4 19.8

16.9

23.9

6.3

10.1

2.5

0.7

0.2

6.5

14.7

38.1

a

Model M is abbreviated M. bMolar percent of the actactic polypropylene homopolymer in Fraction 1, calculated from deconvolution. c Sum of the squares of the deviations. dTriad sequence distribution of Fraction 1 (EPR and a-PP mixture), measured by 13C NMR.

In terms of transition probabilities, the probability of finding either a P or E unit anywhere in a copolymer chain follows from the consideration that the preceding unit can only be an 2267



Article

Table A2. Calculated and Observed Triad Sequence Distributions for Fraction 2 of Samples 1−5 after Correction of PPP for PPPx sample

modela

1

M1 BB BM MM M2

2

M1 BB BM MM M2

3

M1 BB BM MM M2

4

M1 BB BM MM M2

5

M1 BB BM MM M2

cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal cor cal

EEE

PEE + EEP

PEP

EPE

PPE + EPP

PPP

0.538 0.541 0.367 0.363 0.483 0.483 0.423 0.423 0.546 0.546 0.576 0.589 0.383 0.383 0.543 0.543 0.381 0.381 0.497 0.497 0.338 0.350 0.338 0.338 0.571 0.571 0.338 0.338 0.489 0.489 0.274 0.282 0.274 0.273 0.456 0.456 0.274 0.274 0.402 0.402 0.187 0.189 0.187 0.183 0.213 0.213 0.196 0.196 0.244 0.244

0.148 0.159 0.101 0.086 0.133 0.133 0.116 0.116 0.150 0.150 0.121 0.161 0.080 0.081 0.114 0.114 0.080 0.080 0.104 0.104 0.046 0.078 0.046 0.047 0.078 0.079 0.046 0.046 0.067 0.066 0.058 0.085 0.058 0.053 0.097 0.096 0.058 0.058 0.085 0.085 0.106 0.125 0.106 0.088 0.121 0.121 0.111 0.111 0.139 0.138

0.023 0.012 0.016 0.035 0.021 0.021 0.018 0.018 0.024 0.024 0.055 0.011 0.036 0.036 0.051 0.051 0.036 0.036 0.047 0.047 0.041 0.004 0.041 0.039 0.069 0.066 0.041 0.041 0.059 0.059 0.036 0.006 0.036 0.042 0.060 0.060 0.036 0.036 0.053 0.053 0.040 0.021 0.040 0.062 0.046 0.045 0.042 0.042 0.052 0.052

0.035 0.029 0.024 0.043 0.032 0.032 0.028 0.028 0.036 0.036 0.061 0.035 0.041 0.040 0.058 0.058 0.041 0.041 0.053 0.053 0.025 0.003 0.025 0.024 0.042 0.040 0.025 0.025 0.036 0.036 0.020 0.004 0.020 0.026 0.033 0.034 0.020 0.020 0.029 0.030 0.022 0.010 0.022 0.044 0.025 0.025 0.023 0.023 0.029 0.029

0.125 0.125 0.085 0.070 0.112 0.112 0.098 0.098 0.126 0.126 0.106 0.113 0.070 0.071 0.100 0.100 0.070 0.070 0.091 0.092 0.077 0.080 0.077 0.078 0.130 0.133 0.077 0.077 0.111 0.112 0.089 0.090 0.089 0.084 0.148 0.148 0.089 0.089 0.131 0.131 0.141 0.145 0.141 0.124 0.161 0.161 0.148 0.148 0.184 0.184

0.131 0.134 0.407 0.403 0.220 0.220 0.317 0.317 0.118 0.118 0.081 0.091 0.389 0.389 0.134 0.134 0.392 0.392 0.208 0.208 0.473 0.486 0.473 0.473 0.110 0.111 0.473 0.473 0.237 0.237 0.523 0.532 0.523 0.522 0.206 0.206 0.523 0.523 0.300 0.300 0.504 0.509 0.504 0.500 0.435 0.435 0.480 0.480 0.352 0.352

PPPxb

SSc/10−4

31.8

3.23

0

12.04

24.0

0

13.2

0

33.8

0

39.6

45.14

9.2

0.01

35.9

0

8.7

0

30.0

0

0

31.16

0

0.09

40.8

0.25

0

0

30.9

0

0

20.2

0

1.31

39.9

0

0

0

31.9

0

0

9.2

0

16.2

12.2

0

4.6

0

23.5

0

a

Models M1, M2, BB, BM, and MM are abbreviated M, M2, BB, BM, and MM, respectively. bMolar percent of the moderate isotactic polypropylene homopolymer in Fraction 2, calculated from deconvolution. cSum of the squares of the deviations.

■

APPENDIX 3

CMSL = 0.2534X /(1 − X )

According to Keating’s method, the CMSL of a fraction can be calculated by:30

− ln(X ) = − 0.331 + 133.5/Tm

(19)

where X is the molar fraction of ethylene monomer and Tm is the melting point for each fraction obtained from SSA. The statistical arithmetic mean L̅ n, mass mean L̅ w, and the polydispersity index I of CMSL of ethylene-based copolymers

(18) 2268



Article

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can be calculated by:

Ln = =

n1L1 + n2L 2 + n3L3 + , ···, + n jL j n1 + n2 + n3 + , ···, + n j

∑ fj L j

(20)

n1L12 + n2L 2 2 + n3L32 + , ··· , + n jL j2 Lw = n1L1 + n2L 2 + n3L3 + , ··· , + n jL j =

I=

∑ fj L j2 ∑ fj L j

Lw Ln

(21)

(22)

where nj is the normalized peak area of fraction j and Lj is the corresponding CMSL or lamellae thickness. The relationship between the melting temperature T and lamellae thickness l of ethylene-based copolymers is31

l=

2σTm 0

ΔH v(Tm 0 − Tm) (23) where Tm0 is the equilibrium melting temperature of an infinitely thick lamella (418 K), σ is the lamellar surface free energy (70 × 10−3 J/m2), and ΔHv is the enthalpy of fusion for infinitely thick lamellae (288 × 106 J/m3).

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (L.-F.F.); guo-hua.hu@ensic. inpl-nancy.fr (G.-H.H.).

■

ACKNOWLEDGMENTS The authors thank the National Basic Research Program of China (Grant no. 2011CB606001) and the State Key Laboratory of Chemical Engineering for the Special Funds for Open Research Projects (SKL-ChE-08D03). They are also grateful to the reviewers for their pertinent and constructive comments.

■

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Effects of Switching Frequency of a Periodic Switching Polymerization

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