Effect of Silica Nanoparticles Modification on the Thermal, Structural, and Decomposition Properties...

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Full PaperMacromolecularChemistry and Physics

wileyonlinelibrary.com DOI: 10.1002/macp.201400030

Effect of Silica Nanoparticles Modifi cation on the Thermal, Structural, and Decomposition Properties of a β-Nucleated Poly(propylene- co -ethylene) Matrix

Dimitrios G. Papageorgiou , George Vourlias , Dimitrios N. Bikiaris , Konstantinos Chrissafi s *

In the current investigation, nanocomposites containing a β-nucleated poly(propylene- co -ethylene) (PPR) matrix fi lled with untreated (SiO 2 ) and methacrylate-modifi ed silica nano-particles (SiO 2 -MAA) are prepared. Transmission electron microscopy (TEM) reveals the improvement in the quality of dispersion due to the surface modifi cation of the nanoparticles. Also, from differential scanning calorimetry (DSC) and X-ray diffraction (XRD), it is found that the β-nucleating agent and silica nanoparticles work syner-gistically in order to increase the relative β-content in the nanocomposite samples. The thermal stability of each sam-ples is evaluated by means of thermogravimetric analysis (TGA) and the enhancement of the thermal stability of the nanocomposites is attributed to the nanoconfi nement of the macromolecular chains caused by the presence of the fi llers.

D. G. Papageorgiou, Dr. G. Vourlias, Prof. K. Chrissafi s Solid State Physics Section, Department of Physics, Aristotle University of Thessaloniki, 541 24 , Thessaloniki , Greece E-mail: hrisafi [email protected] Dr. D. N. Bikiaris Laboratory of Polymer Chemistry and Technology, Department of Chemistry, Aristotle University of Thessaloniki, 541 24 , Thessaloniki , Greece

1. Introduction

Polypropylene is one of the most used thermoplastics around the world since its exceptional physical prop-erties ensured its worldwide commercial penetration in applications including packaging, labeling, textiles, laboratory equipment, automotive, domestic plumbing, and so on. Almost all these applications can be affected from the degree of crystallinity and crystal structure of

polypropylene (PP). Generally, polypropylene can crystal-lize in three different forms: α-, β-, and γ-form. [ 2,3 ] The most used crystalline form of polypropylene is the α-form due to its thermodynamic stability and the fact that it pre-dominates under most processing conditions. The physical properties of β-form polypropylene present some differen-tiations from the α-form, which include improved elonga-tion, impact strength, and heat distortion. [ 5,6 ] Therefore, β-polypropylene has attracted much interest from both industry and academia, leading to numerous publications and commercial products. [ 8–15 ] Furthermore, the simulta-neous existence of α- and β-crystals can give materials with much more improved mechanical properties. However, even in this case the particular material has low impact strength. The addition of ethylene monomer in polypro-pylene in a content ranged from 5 to 9 wt% can be overcame this problem and the produced poly(propylene ethylene) copolymers have suffi cient impact strength values. These copolymers behave as partially elastomers but they have lower tensile strength values, compared with neat poly-

Early View Publication; these are NOT the final page numbers, use DOI for citation !!

Macromol. Chem. Phys. 2014, DOI: 10.1002/macp.201400030© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

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D. G. Papageorgiou et al.

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propylene. The introduction of rigid nanoparticles into polypropylene has proved to be an effi cient way to improve several physicochemical properties of the initial material as well as its mechanical properties. Silica nanoparticles are one of the most useful and interesting fi llers, due to the reinforcing effect that they have already brought up in a variety of polymeric matrixes. [ 18,19 ] The main problem with the specifi c nanofi ller is the fact that the polar groups that silica nanoparticles contain, lead them to form precipitates inside the polymeric matrix. The precipitates act as stress concentrators and reduce the improvement of the physico-chemical properties of the polymer nanocomposites. For this reason, the surface modifi cation of the nanoparticles has been applied in various cases quite successfully. [ 21,22 ] The surface treatment of SiO 2 nanoparticles with acrylate groups enables the change in the surface of the silica nanoparticles from highly hydrophilic to hydrophobic, increasing in this way the interaction between the polymer and the nanoparticles. In the current work, efforts were made to improve even further the dispersion of the nano-particles with the use of a compatibilizer such as maleic anhydride. The low molecular weight of the compatibilizer allows the breakup of the aggregates of the nanoparticles and improved dispersion is achieved.

The current article aims to explore the thermal, struc-tural, and decomposition properties of the β-nucleated poly(propylene- co -ethylene) nanocomposite samples prepared with untreated silica and surface-treated silica with methacrylate groups in which maleic anhydride was also added as compatibizer. Emphasis was also given to the thermal decomposition kinetics of the samples with the estimation of activation energy by means of isocon-versional and model-fi tting methods.

2. Experimental Section

2.1. Materials

Poly(propylene- co -ethylene) random copolymer (PPR) was sup-plied by Basell Polyolefi nes under the commercial name Hostalen PP H5416 Random copolymer containing 7 wt% ethylene con-tent and melt fl ow rate 0.29 g/10 min (190 °C/5 kg). Fumed silica (SiO 2 ) nanoparticles used for the nanocomposite preparation were supplied by Degussa AG (Hanau, Germany) under the trade name AEROSIL 200. The average primary particle size was 12 nm, the specifi c surface area was 200 m 2 g −1 , and the SiO 2 content was >99.8%. 3-(Trimethoxysilyl)propyl methacrylate (98%) and maleic anhydride (purity >99%) were supplied from Aldrich company.

2.2. Synthesis of Calcium Pimelate Nucleator

The calcium pimelate nucleator was synthesized by double decomposition. In detail, calcium pimelate was prepared through the reaction between equimolar CaCl 2 and sodium pimelate aqueous solution with stirring. The precipitation was fi ltered,

washed twice with distilled water and ethanol, respectively, and dried in a vacuum at room temperature. The calcium pime-late was used at concentration 0.1 wt% as β-nucleator for the poly(propylene- co -ethylene) random copolymer. The β-nucleated polymeric matrix will be denoted as PPR throughout the article.

2.3. Silica Nanoparticles Modifi cation

Functionalization of silica nanoparticles with methacrylate groups attached to their surface was conducted using the fol-lowing procedure. To a stirred suspension of dried silica (10 g) in toluene (200 mL) and nitrogen fl ow rate, a solution of 3-(tri-methoxysilyl)propyl methacrylate (TPM) (15 g) in dry toluene (60 mL) was added dropwise over 25 min. The mixture was refl uxed under nitrogen for 8 h. After cooling to room tempera-ture, the suspension was fi ltered and washed with toluene. The unreacted 3-(trimethoxysilyl)propyl methacrylate was extracted with toluene using a Soxhlet apparatus for 8 h. The methacrylate-modifi ed silica was dried in vacuum at 100 °C for 6 h and stored in a desiccator over P 2 O 5 . The methacrylate-treated silica nano-particles will be denoted as SiO 2 -MAA from now on.

2.4. Maleic Anhydride Grafting Procedure to PPR (PPR- g g -MA)

The grafting procedure of the maleic anhydride to PPR was carried out in a four-neck round-bottom fl asks equipped with an overhead stirrer, condenser, thermometer, and a nitrogen gas inlet. The temperature was maintained with accuracy of ±0.5 °C by using a contact thermometer in an oil bath. A known amount of PPR was dissolved in toluene at 110 °C. Nitrogen gas was purged throughout the reaction to remove dissolved oxygen. To this homogenized solution, lauroyl peroxide (0.15% w/v) in toluene was added and after 10 min, maleic anhydride solution (1.25% w/v) in toluene was also added. The reaction was continued for 6 h and the reaction mixture was poured into 1.5 L of acetone under vigorous stirring. The precipitated graft copolymer was isolated and washed several times with acetone, while the unreacted maleic anhydride and traces of toluene were removed with acetone using a Soxhlet for 16 h. Finally, the collected PPR- g -MA was dried under reduced pres-sure at 70 °C till a constant weight and the grafted maleic anhydride percentage from FTIR spectroscopy measurements was calculated equal to 5.2 wt%.

2.5. Nanocomposites Preparation

PPR/SiO 2 nanocomposites containing 0.5, 2.5, and 5 wt% of modifi ed and neat nanosilica were prepared by melt mixing in a Haake–Buchler Reomixer (model 600) at 220 °C and 30 rpm for 15 min. Prior to melt mixing, the nanoparticles were dried by heating in a vacuum oven at 130 °C for 24 h. The components were physically premixed before being fed into the reomixer. Spe-cifi cally, the two sets of samples prepared were: i) the β-nucleated poly(propylene- co -ethylene) matrix and untreated silica nano-particles (PPR/SiO 2 ) and ii) the β-nucleated poly(propylene- co -ethylene) matrix and methacrylate-treated silica nanoparticles in the concentrations mentioned previously (PPR/SiO 2 -MAA)



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Effect of Silica Nanoparticles Modification on the Thermal, Structural, and Decomposition Properties...

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in which maleic anhydride-grafted PPR (PPR- g -MA) was added at a concentration of 10 wt%. In order to achieve a better disper-sion of the nanoparticles in PPR, a RETSCH planetary ball mill, model S100 was used. The PPR fl akes along with the proper amount of nanoparticles and the compatibilizer were fed into a “C”-type stainless-steel grinding jar with a capacity of 25 mL. Five steel spheres were also added as a grinding medium. The milling was set at 500 rpm for a period of 2 h. The characteris-tics of the polymeric matrix (PPR) prior and after the ball milling were studied and no transformations owing to the high-energy ball milling process were observed since the results were practi-cally identical.

2.6. Transmission Electron Microscopy (TEM)

TEM observations were made on ultrathin fi lm samples of the various nanocomposites prepared by an ultra-microtome. These thin fi lms were deposited on copper grids. TEM images were obtained using a JEOL 120 CX microscope operating at 120 kV.

2.7. Differential Scanning Calorimetry (DSC)

The melting behavior of the samples was studied using a Perkin–Elmer, Pyris Diamond differential scanning calorimeter (DSC), calibrated with indium and zinc standards. Samples of 5 ± 0.1 mg were used in tests. They were sealed in aluminum pans and heated at a heating rate 20 °C min −1 to 200 °C, which is above the equilibrium melting point of PPR. The samples were held at 200 °C for 3 min in order to erase any thermal history. Next, the samples were cooled down at 10 °C min −1 . A fresh sample was used in each run.

2.8. X-ray Diffraction (XRD)

XRD analysis was performed on the polymeric matrix and the nanocomposite materials using a Rigaku Ultima+ diffrac-tometer using Cu K α radiation, a step size of 0.05° and a step time of 3 s, operating at 40 kV and 30 mA. In order to present consistent results with DSC, the samples were prepared in the same way with the DSC samples in order to erase their thermal history.

2.9. Polarizing Light Microscopy (PLM)

A polarizing light microscope (Nikon, Optiphot-2) equipped with a Linkam THMS 600 heating stage, a Linkam TP 91 control unit and also a Jenoptic ProgRes C10 plus camera with the Capture Pro 2.1 software was used for PLM observations. The specimens were prepared by placing a small amount of the polymer or nano-composite on a thin circular cover glass and by placing another circular cover glass on top of the material. This “sandwich” was slid onto the heating stage and heated from room temperature to 200 °C. A thin fi lm was then obtained by applying a slight pressure on the top cover glass. Next, the specimen was cooled at 90 °C min −1 to 110 °C, at which temperature it was maintained for 20 min in order to crystallize isothermally.

2.10. Thermogravimetric Analysis (TGA)

TGA was carried out with a SETARAM SETSYS TG-DTA 16/18. Samples (5.5 ± 0.5 mg) were placed in alumina crucibles. An empty alumina crucible was used as reference. For the initial characterization of the thermal stability of the samples, all the materials were heated from ambient temperature to 550 °C in a 50 mL min −1 fl ow of dry air at heating rate of 20 °C min −1 . Addi-tional measurements at heating rates of 5 and 10 °C min −1 were performed for the application of the kinetic methods for TGA. Continuous recordings of sample temperature, weight, and heat fl ow were performed throughout the measurements.

3. Results and Discussion

3.1. Transmission Electron Microscopy (TEM)

TEM was employed in order to observe the effect of the modifi cation of silica and the presence of the compatibi-lizer on the quality of dispersion of the fi ller particles. Thus, as it can be seen from the images of the nanocomposite samples (Figure 1 a), the untreated silica nanoparticles form very large aggregates, which will act as failure points during the examination of the physicochemical properties of the samples. However, when the use of compatibilizer (PPR- g -MA) and the modifi cation of silica nanoparticles were applied simultaneously (Figure 1 b), the quality of dispersion was signifi cantly better even at the highest con-centration of the fi ller particles and the size of the aggre-gates was quite small (50–150 nm). This is an indication that the aggregates have broken into smaller fragments, a fact which is expected to attribute a signifi cant enhance-ment on the physicochemical properties of the nanocom-posite material. Similar fi ndings were also reported in a previous study by our group.

3.2. Differential Scanning Calorimetry (DSC)

In order to evaluate the effect of the simultaneous pres-ence of the β-nucleating agent in polypropylene matrix and silica nanoparticles, the melting behavior of all nanocomposites was studied by DSC and is presented in Figure 2 . For all the nanocomposite samples, two melting peaks appear; the fi rst one corresponds to the melting of β-crystals and the second one corresponds to the melting of α-crystals, respectively. The twinning of the melting peak of α-crystals is attributed to a modifi cation transition mechanism from alpha1 (α1) to alpha2 (α2) crystals. The α1 phase is less stable, while the α2 phase corresponds to more perfect crystals and appears at higher tempera-tures. The melting point of both crystalline phases pre-sents small variations for both sets of nanocomposites, since the differences that can be observed are in the vin-cinity of ±2 °C. In the samples fi lled with untreated silica,



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the fact that the area under the peak of β-crystals is sig-nifi cantly larger than that of α-crystals, is an indication of the higher β-content of the nanocomposites, which leads us to conclude that the β-nucleating agent and silica nanoparticles act synergistically in order to increase the β-content in the nanocomposites. In the case of the sam-ples fi lled with surface-treated silica, a different melting behavior was observed. Initially, for the samples fi lled with low concentrations of SiO 2 -MAA nanoparticles, the α-crystals melting peak is more intense due to the high percentage of grafted maleic anhydride, which decreased the regularity of the chains and lead to reduced crys-tallization tendency. For this reason, the ability of the β-nucleated random copolymers to crystallize in the β-form decreased due to the lower chain regularity in the nanocomposite samples. [ 26 ] However, when the SiO 2 -MAA content increased (5 wt%), the area of the peak owing to the β-crystals increased, which is an indication of the β-nucleating ability of the SiO 2 -MAA nanoparticles in

combination with their synergistic effect with the nucle-ating agent, which has been also verifi ed in a previous report. The DSC melting curves of the samples fi lled with 2.5 wt% untreated and surface-treated silica were not included in Figure 2 , for brevity reasons since they did not exhibit signifi cant differences from the samples fi lled with 0.5 wt% silica in both cases. In an attempt to con-fi rm further the above results, the samples were exam-ined with XRD, in order to calculate the exact amount of β-phase in the nanocomposites.

3.3. X-ray Diffraction (XRD)

The nucleating ability of the silica nanoparticles was also evaluated with XRD. In Figure 3 , the diffractograms of the samples fi lled with untreated silica (Figure 3 a) and with surface-trated silica (Figure 3 b) are presented. The strong peak at 16.1° confi rms the fact that the samples crystal-lized mainly in β-form, while the peaks corresponding to equal to 14.2°, 17° and 18.8° correspond to the refl ections from the α-crystalline phase. The K value representing the content of β-crystalline form was calculated according to the equation proposed by Turner-Jones et al.: [ 28 ]

K I

I I I Ia a a

(300)

(110) (300) (040) (130)=

+ + +ββ

β (1)

where I α(110) , Ι α(040) , and Ι α(130) are the intensities of the dif-fraction peaks owing to the α-crystals which correspond to angles 2θ = 14.2°, 17°, 18.8°, and I β(300) is the intensity of the β-diffraction peak at 16.1°. The overall crystallinity was calculated from the well-known equation:

X A

A Acc

c a=

+ (2)

where A c and A α are the areas under the crystalline peaks and amorphous halo, respectively. A deconvolution of the X-ray diffractograms was performed prior to the calcula-tions in order to estimate the area under each peak.



Figure 1. TEM images of PPR nanocomposites: a) PPR/SiO 2 5 wt%, b) PPR-SiO 2 -MAA 5 wt%. The scale in both images is 50 nm.

Figure 2. DSC melting curves of PPR and nanocomposite samples.

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The crystalline sizes of the formed crystals in the direc-tion perpendicular to (hkl) planes were estimated with the Scherrer formula: [ 29 ]

L 0.9

cosλ

β θ=

(3)

where λ is the X-ray wavelength of the radiation used, θ is the Bragg angle, and β is the refl ection breadth at half maximum.

As it is obvious from the diffractograms and Table 1 , the degree of crystallinity in samples containing untreated SiO 2 increases slightly at 0.5 wt% SiO 2 and reduces pro-gressively at higher contents. However, in all nanocom-posites, the degree of crystallinity is higher than the cor-responding of neat PPR. When PPR- g -MA compatibilizer was added to PPR, a great reduction was observed in the

values of the degree of crystallinity. This is because the presence of maleic anhydride into the PPR macromol-ecules reduces their ability to fold and create lamellas. However, the addition of surface-treated SiO 2 causes a great increase to the degree of crystallinity, which depends directly from the SiO 2 content. This is an indica-tion that SiO 2 nanoparticles can act as nucleating agents, increasing the crystallinity of PPR. Furthermore, it is also of high importance to see how these nanoparticles affect the formation of α- and β-crystals. As can be seen from Table 1 , SiO 2 nanoparticles can assist the formation of β-crystals, since in all nanocomposites, the β-crystalline content presented an increase. The β-nucleating effi -ciency of untreated silica nanoparticles is quite small, since the increase of β-crystalline content is almost 4% in the sample containing 5 wt% SiO 2 . In addition, the results from the DSC experiments are confi rmed in the case of surface-treated silica nanoparticles.

The use of the compatibilizer, as was mentioned earlier, disrupted the chain regularity of the polymeric matrix and this was also refl ected on the β-crystalline content. Thus, K β was reduced from 71.2% (neat PPR) to 43.5% in PPR/PPR- g -MA. In this case, the β-content was reduced almost 30% compared with neat PPR. Neverthe-less, the insertion of SiO 2 -MAA nanoparticles brought up a signifi cant increase in the β-crystalline content, indi-cating the synergistic effect of the simultaneous pres-ence of the nucleating agent and the surface-treated silica nanoparticles toward the increase of the β-content. Due to this synergistic effect, in the nanocomposite sample containing 5 wt% treated silica, the β-crystalline content is even higher than that of neat PPR or from the nano-composites containing untreated silica. In addition, the fact that a drop of the initial crystalline size was observed in the nanocomposite samples, strengthens the conclu-sion that the silica nanoparticles can act effi ciently as nucleating agents, since more nucleating sites are active in those samples. The samples fi lled with methacrylate-treated silica nanoparticles present the smallest crystal-line size from all samples, indicating the effect of the compatibilizer on the crystalline structure. Polarized optical microscopy was employed in order to observe visually the variations on the crystalline size of the nano-composite samples.

3.4. Polarized Optical Microscopy

All the prepared nanocomposites were studied with using polarized light microscopy (PLM), which is often used as a tool for the study of crystallization behavior and crys-talline size of the samples. For this reason, the crystalli-zation of poly(propylene- co -ethylene) random copolymer without a β-nucleating agent, poly(propylene- co -ethylene) random copolymer containing calcium pimelate at



Figure 3. X-ray diffractograms of the nanocomposite sam-ples fi lled with a) untreated SiO 2 , b) methacrylate-treated SiO 2 nanoparticles.

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0.1 wt%, and its nanocomposites containing 5 wt% SiO 2 and 5 wt% methacrylate-modifi ed SiO 2 were studied by PLM. From the obtained photographs (Figure 4 ), it is clear that after isothermal crystallization at 110 °C, neat PPR forms crystallites with sizes ranged between 20 and 40 μm (Figure 4 a). When calcium pimelate was added as β-nucleator, the size of crystallites was substan-tially reduced to 2–7 μm, indicating the effectiveness of this nucleator to alter the crystalline behavior of PPR (Figure 4 b). However, when neat or surface-treated SiO 2 nanoparticles (Figure 4 c,d, respectively) were used simul-taneously with calcium pimelate, the sizes of the crystal-lites are even smaller to the range that it is not possible to be measured. Thus, it can be said that the incorpora-tion of silica nanoparticles triggered a drop in the size of the crystallites, which are visible as the tiny white spots on the PLM photographs, proving that SiO 2 nanoparticles can act as nucleating agents for PPR crystallization. The results come in agreement with the fi ndings from XRD technique where it was found that the presence of silica nanoparticles and β-nucleating agent triggered a signifi -cant decrease of the crystalline size. This ability of SiO 2 nanoparticles was also mentioned for neat iPP.

3.5. Thermogravimetric Analysis (TGA)

It is well known that the addition of nanoparticles can affect signifi cantly the thermal properties of polymers. [ 32 ] For this reason, the thermal stability of the polymeric matrix and the prepared nanocomposites containing untreated and surface-treated SiO 2 nanoparticles were studied by means of TGA. Thus, the samples were initially heated with a heating rate of 20 °C min −1 and the start of the degradation process (i.e., mass loss >1%) was deter-mined in order to examine the thermal stability of the nanocomposite samples. As it can be seen from Figure 5 and the inset graphs, the presence of silica nanoparticles

into the PPR matrix brought up a signifi cant increase of the thermal stability of the samples, which in the case of the nanocomposites containing neat silica was in the vincinity of 4–11 °C, while in the case of methacrylate silica nanoparticles the stabilization effect was even higher, increasing the temperature of degradation almost 15 °C. The reason for this must be the improvement in the quality of the dispersion of the nanoparticles, along with the strongest adhesion between the polymeric matrix and SiO 2 -MAA nanoparticles, as it was proven in a previously published work. [ 27 ] What can also be observed is that in the case of untreated silica nanoparticles, the sample fi lled with 0.5 wt% silica presents the higher thermal stability at the beginning of thermal degradation, while the nano-composite samples with higher fi ller content present lower thermal stability due to the high number of aggregates, which behave as failure points for the material. On the contrary, the samples with the methacrylate-treated silica nanoparticles present increasing thermal stability with increasing fi ller content, a fact which strengthens once again the conclusion that the quality of dispersion and the strong adhesion between the matrix and the fi ller, retarded the degradation process. Generally, silica nanoparticles have been proved excellent stabilizers for several poly-meric matrixes, due to their insulating and mass transport barrier properties applied on the volatile products gener-ated during the decomposition process. [ 33,34 ] Two mecha-nisms are generally proposed for the interpretation of the increased thermal stability of polymer nanocomposites containing silica; i) silica forms a layer on the surface of the polymeric materials and ii) silica acts as a protective layer to the char formed from the polymer. However, in both cases, one can oppose the above conclusions, since even in a per-fect fi ller-dispersion case, the fi ller percentage corresponds to a very small fraction of the initial polymeric matrix. Thus, the decomposition products formed in a distance are expected to escape the bulk in the same time as with the polymeric matrix. The concept introduced by Chen et al. [ 36 ] is based on the nanoconfi nement theory in polymer nano-composite materials. In more detail, the fi ller particles can create locally confi ned areas where the macromolecular chains of the polymeric matrix do not maintain their reg-ular coil conformation. Furthermore, it has been demon-strated that the nanoconfi ned areas reduce the mobility of the macromolecular chains, a fact which leads to lower chemical reactivity of the chains and higher thermal sta-bility due to the presence of the nanofi llers. Regarding the nanoconfi nement effect on the studied nanocom-posites, it can be considered signifi cantly higher in the samples containing surface-treated silica (SiO 2 -MAA), since higher degree of dispersion (as was already proved with TEM) leads to larger nanoconfi ned area where the movement of the macromolecular chains of the polymer is hindered, resulting in the enhancement of thermal



Table 1. Calculated crystallinity, β-crystalline content, and crys-talline size from X-ray diffractograms for the nanocomposite samples.

Sample X c [%]

K β L (300) [nm]

PPR 51.3 71.2 25.38

PPR/SiO 2 0.5 wt% 54.3 73.2 25.1

PPR/SiO 2 2.5 wt% 53.1 74.1 24.86

PPR/SiO 2 5 wt% 52.8 75.3 24.39

PPR/PPR- g -MA 37.6 43.5 24.65

PPR/SiO 2 -MAA 0.5 wt% 42.7 50.7 24.08

PPR/SiO 2 -MAA 2.5 wt% 44.4 59.4 23.34

PPR/SiO 2 -MAA 5 wt% 48.2 84.6 22.87

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stability. Therefore, in the current set of samples, the results can be explained on the basis of the nanoconfi ne-ment theory.

3.5.1. Kinetic Analysis Based on Thermogravimetric Data

The data obtained by TGA can provide information not only on the thermal stability of the samples but also on the behavior of the degradation reactions throughout the decomposition process. Thus, useful conclusions can be exported regarding the decomposition mechanisms of each sample and the relation of those mechanisms with other physicochemical properties.

The experimental data that must be obtained in order to perform the kinetic analysis of a heterogeneous reac-tion should be exported from non-isothermal processes. The currently used methods for the calculation of kinetic parameters in a single-step reaction are based on the rate equation:

t TAf E

RTdd

dd

( )expα β α α= = −⎛⎝⎜

⎞⎠⎟

(4)

where α is the degree of conversion, E is the activation energy, A is the pre-exponential factor, f ( α ) is the differen-tial conversion function, and R is the gas constant. From the above equation, the so-called kinetic triplet ( E , A , f ( α )) can be calculated and practically describes the physicochem-ical changes during the heating procedure of a sample over time. The estimation of the kinetic parameters should be performed using data from several heating rates according to the recommendations of ICTAC.

The activation energy values can be initially calculated with the use of various model-free methods such as the ones proposed by Friedman, Ozawa–Flynn–Wall (OFW), [ 40 ] Kissinger–Akahira–Sunose (KAS), Starink [ 42 ] and others. In the current article, the integral method proposed by Starink and the differential method proposed by Friedman were applied to the set of data. The main reason why Starink method was selected in the current article was the accuracy of this method, as it was demonstrated in earlier literature reports. [ 44 ] The Starink method is given by:

TE

RTln const. 1.0008 a

a1.92β⎛

⎝⎜⎞⎠⎟

= −α

(5)



Figure 4. PLM photos of: a) pure PPR, b) PPR with β-nucleating agent, c) PPR/SiO2 5 wt%, and d) PPR/SiO2-MAA 5 wt% after crystallization at 110 °C. For better interpretation of the results, the reader is referred to the web version of the article.

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Using the Starink method, the apparent activation energy values can be calculated from the slope of the lin-ear-fi tted function of Tln( / )1.92β α versus 1/ T α .

Friedman proposed the use of the logarithm of the con-version rate as a function of the reciprocal temperature, thus the equation which represents his theory is: [ 38 ]

at

A fRT

ln dd

ln ln ( ) Ea

aβα⎛

⎝⎜⎞⎠⎟ =

⎛⎝⎜

⎞⎠⎟

+ − (6)

From Friedman’s equation, it can be seen that if the function f ( α ) is constant for a particular value of the degree of conversion, then the sum ln( A/β ) + ln f ( α ) is also constant. The activation energy values can be calcu-lated from the plots of ln[ β (d a/ d t )] versus 1/ T α obtained

from the thermogravimetric data from different heating rates.

3.5.2. Determination of the Activation Energy Using Isoconversional Methods

The initial part of a thermal degradation kinetics study involves the calculation of the kinetic triplet [activation energy E , pre-exponential factor A , and conversion function f ( α )] with the use of isoconversional methods. Generally, isoconversional methods are considered to give accurate values of the activation energy. Prior to the kinetics study, dynamic TG measurements should be performed at dif-ferent heating rates according to the recommendations of ICTAC. In the present work, three heating rates were used, namely 5, 10, and 20 °C min −1 (Figure 6 ).

An important information that can be exported after the application of isoconversional methods is the depend-ency of the apparent activation energy with the degree of conversion, which can afterward provide additional indi-cations regarding the multistep kinetics approach. These methods provide a way of obtaining the kinetic param-eters without any assumption on the reaction mecha-nisms. In addition, such methods involve the measuring of temperatures which correspond to fi xed values of α by experiments at different heating rates.

In the current article, the isoconversional methods of Starink and Friedman were applied to the set of thermo-gravimetric data. The results from the application of the above isoconversional methods can be seen in Figure 7 .

As is obvious from Figure 7 , the polymeric matrix presents lower values of activation energy from the nanocomposite samples. This was expected since it was previously found out that it presents lower thermal sta-bility compared with the samples fi lled with neat and



Figure 6. TGA thermograms of PPR/SiO 2 5 wt% sample at different rates: 1) 5 °C min −1 , 2) 10 °C min −1 , and 3) 20 °C min −1 .

Figure 5. TGA thermograms of PPR and nanocomposite samples with a) neat silica, b) methacrylate-modifi ed silica. The applied heating rate was 20 °C min −1 and the inset graphs represent the 1% mass loss for each nanocomposite sample. (For a better inter-pretation of the curves, the reader is referred to the web version of the article.)

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methacrylate-modifi ed silica. Also, the modifi cation of silica, which enhanced in a greater extend the thermal stability of the polymeric matrix than the untreated silica, brought up an important increase to the activa-tion energy values of the nanocomposites. In addition, in both isoconversional methods a quite similar trend is observed. At low values of the degree of conversion ( α < 0.3–0.4), the activation energy presents a rapid increase that corresponds to the small mass loss at the early stages of the degradation process, while from that point E remains quite stable, a mechanism corresponding to the main degradation phenomenon. The dependence of E on α is an indication that the degradation process is a quite complex reaction, which should be described with the use of at least two different mechanisms. The use of

two mechanisms for the description of thermal degrada-tion of polymers is quite typical in such analysis. [ 47,48 ]

3.5.3. Determination of the Activation Energy Using Model-Fitting Methods

The second step of the kinetic analysis of the thermal deg-radation process involves the use of various mathematical models, which are used in order to simulate the degrada-tion and export results regarding the values of the kinetic triplet ( E , f ( α ), A ). The model-fi tting method with nonlinear multivariate regression does not assume knowledge of E and f ( α ) in advance and is considered generally an accu-rate method, which gives reliable results regarding the parameters of each reaction step. Once again, multiple heating rates must be used during the study of the phe-nomena. Initially during the model-fi tting study, most often the assumption that the mass loss of the samples can be described by a single mechanism is made. The heating rates that were used during the experimental process were three: 5, 10, and 20 °C min −1 and the model-fi tting analysis of the thermal degradation of the nanocomposite samples was evaluated with the aid of Netzsch Thermokinetics software.

For the fi tting procedure, 16 different kinetic models were used. When one-step reactions were tested, the fi t-ting model that simulated more effi ciently the experi-mental results for all tested samples was the n -order model with autocatalysis ( Cn ). The specifi c model gener-ally describes quite adequately the thermal decomposi-tion of polymeric materials in fi rst-order reactions. Only the PPR and PPR/SiO 2 5 wt% samples will be shown in Figure 8 for brevity reasons.

As it can be seen from Figure 8 , the quality of fitting in the initial stage of degradation cannot be considered quite satisfactory, since some divergences appear espe-cially in the case of PPR. On the other hand, the region where the main mass loss takes place is described quite well from the specific model. Furthermore, the fact that the thermal degradation process of polymers involves complex reactions and mechanisms, leads to the conclusion that more than one reaction mecha-nisms should be tested. That was also inhibited by the dependence of activation energy on the degree of con-version (Figure 7 ).

Various combinations of the theoretical models were tested for the determination of the kinetic parameters. It is important to note that prior to the two-stage model-fi tting procedure with theoretical models, the following assumptions were originally made: fi rst, the two mecha-nisms are consecutive and second the mechanism, which we are trying to identify corresponds to a small mass loss in the beginning of the process. The combination of models, which gave the most accurate fi tting results,



Figure 7. Dependence of the activation energy on the degree of conversion, as calculated with the isoconversional methods of Starink and Friedman. 1) PPR, 2) PPR/SiO 2 0.5 wt%, 3) PPR/SiO 25 wt%, 4) PPR/SiO 2 -MAA 0.5 wt%, and 5) PPR/SiO 2 -MAA 5 wt%.

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was the two-step consecutive n -order model ( F n) (fi rst step) and n -order model with autocatalysis ( C n) (second step) ( F n– C n). Once again, for brevity reasons, only the samples fi lled with 0.5 wt% SiO 2 and 0.5 wt% SiO 2 -MAA will be shown in Figure 9 . The fact that the degradation mechanism of the polymeric matrix and the nanocom-posite samples is the same, leads to the conclusion that silica nanoparticles did not affect the degradation mecha-nism and enhanced the thermal stability of the matrix by confi ning the movement of its macromolecular chains. The results from the application of a single-step mecha-nism and the two-consecutive-step mechanisms on the thermal degradation of neat and nanocomposite samples are presented in Table 2 .

From the results presented in Table 2 , it can be deter-mined that the activation energies that correspond to

the fi rst stage of degradation ( F n model) are lower than those corresponding to the second stage of degradation ( C n model). Also the nanocomposite samples with the surface-modifi ed silica present signifi cantly higher acti-vation energy values than the samples containing neat silica nanoparticles as a result of their enhanced thermal stability due to better dispersion and improved interac-tions with the polymeric matrix, according to the nano-confi nement theory. Finally, the branching rate constant K cat , which is included in the n th-order autocatalytic model ( C n), is higher in the case of nanocomposites, due to the fact that the fi ller particles behave as imperfec-tions that promote continued reaction (i.e., branching) at the reaction interface and practically contribute to the decomposition process.



Figure 8. Mass-loss experimental data and fi tting curves from different heating rates: 1) β = 5 °C min −1 , 2) β = 10 °C min −1 , and 3) β = 20 °C min −1 . The fi tting model that was used in both cases was the n -order model with autocatalysis ( C n).

Figure 9. Mass loss experimental data and fi tting curves from dif-ferent heating rates: 1) β = 5 °C min −1 , 2) β = 10 °C min −1 , and 3) β = 20 °C min −1 . The fi tting model that was used in all cases was the consecutive n th-order model with autocatalysis ( C n) and n -order model ( F n).

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Keywords: β-polypropylene; nanocomposites; silica nanoparticles; surface modifi cation: thermal degradation

Received: January 15, 2014 ; Revised: February 14, 2014 Published online: ; DOI: 10.1002/macp.201400030



4. Conclusion

From the evaluation of thermal and structural properties of the nanocomposite samples, it was found out that the modifi cation of silica nanoparticles elucidates different effects on the physicochemical properties on the samples. Initially, TEM studies showed that the simultaneous pres-ence of the β-nucleating agent, the surface treatment of silica nanoparticles with methacrylate groups and the com-patibilizer (PPR- g -MA), enhanced the dispersion of the fi ller resulting in smaller aggregates compared with the samples containing unmodifi ed silica. Regarding the results from DSC, the untreated silica nanoparticles did not affect signif-icantly the melting point of the nanocomposites, while the increase of the relative β-content from XRD diffractograms was quite small (in the vincinity of 3–4%). In the case of the samples containing surface-treated silica, the pres-ence of the compatibilizer disrupted the chain regularity of the samples and the α -crystalline content was increased for the samples with low fi ller content. However, when the SiO 2 -MAA concentration increased, the β-crystalline content increased also, indicating the synergistic work of calcium pimelate and SiO 2 -MAA toward the increase of β-crystallites. Thus, the silica nanoparticles acted effi -ciently as nucleating agents. The thermal stability of the PPR/SiO 2 samples was lower than that of the PPR/SiO 2 -MAA samples, due to the improvement of the fi ller disper-sion in the specifi c set of samples. The enhancement of the thermal stability was attributed to the nanoconfi nement of the macromolecular chains caused by the presence of the fi llers. The calculated activation energy values with isocon-versional and model-fi tting methods amplifi ed even more

this conclusion, since the activation energy values of the samples containing SiO 2 -MAA nanoparticles were higher than those of the neat polymer and PPR/SiO 2 nanocompos-ites. Finally, thermal degradation of all samples was accu-rately described by the F n– C n consecutive model.

Acknowledgements: This research has been cofi nanced by the European Union (European Social Fund – ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF) – Research Funding Program: Heracleitus II. Investing in knowledge society through the European Social Fund.

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Effect of Silica Nanoparticles Modification on the Thermal, Structural, and Decomposition Properties...

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