Article A Study on the Early Degradation of the Non-Additive Polypropylene–Polyethylene Composite Sampled between the Polymerization Reactor and the Deactivation-Degassing Tank Joaquín Alejandro Hernández Fernández 1,2,3,4,* , Rodrigo Ortega-Toro 4 and Eduardo Antonio Espinosa Fuentes 5,* 1 Chemistry Program, Department of Natural and Exact Sciences, San Pablo Campus, University of Cartagena, Cartagena 130015, Colombia 2 Chemical Engineering Program, School of Engineering, Universidad Tecnológica de Bolivar, Parque Industrial y Tecnológico Carlos Vélez Pombo, Cartagena 130001, Colombia 3 Department of Natural and Exact Science, Universidad de la Costa, Barranquilla 080002, Colombia 4 Food Packaging and Shelf-Life Research Group (FP&SL), Food Engineering Department, Universidad de Cartagena, Cartagena de Indias 130015, Colombia; rortegap1@unicartagena.edu.co 5 Engineering Faculty, Universidad Libre, Barranquilla 080003, Colombia * Correspondence: jhernandezf@unicartagena.edu.co (J.A.H.F.); eduardo.espinosaf@unilibre.edu.co (E.A.E.F.) Abstract: The industrial production of polypropylene–polyethylene composites (C-PP-PE) involves the generation of waste that is not usable, resulting in a significant environmental impact globally. In this research, we identified different concentrations of aluminum (8–410 ppm), chlorine (13–205 ppm), and iron (4–100 ppm) residues originating from traces of the Ziegler–Natta catalyst and the triethyla- luminum (TEAL) co-catalyst. These residues accelerate the generation of plastic waste and affect the thermo-kinetic performance of C-PP-PE, as well as the formation of volatile organic compounds that reduce the commercial viability of C-PP-PE. Several families of organic compounds were quantified by gas chromatography with mass spectrometry, and it is evident that these concentrations varied directly with the ppm of Al, Cl, and Fe present in C-PP-PE. This research used kinetic models of Coats–Redfern, Horowitz–Metzger, Flynn–Wall–Ozawa, and Kissinger–Akahira–Sunose. The acti- Citation: Hernández Fernández, J.A.; vation energy values (Ea) were inversely correlated with Al, Cl, and Fe concentrations. In samples −1 Ortega-Toro, R.; Fuentes, E.A.E. A PP0 and W3, with low Al, Cl, and Fe concentrations, the values (Ea) were 286 and 224 kJ mol , Study on the Early Degradation of the respectively, using the Horowitz method. Samples W1 and W5, with a high ppm of these elements, Non-Additive Polypropylene– showed Ea values of 80.83 and 102.99 kJ mol−1, respectively. This knowledge of the thermodynamic Polyethylene Composite Sampled behavior and the elucidation of possible chemical reactions in the industrial production of C-PP-PE between the Polymerization Reactor allowed us to search for a suitable remediation technique to give a new commercial life to C-PP-PE and the Deactivation-Degassing Tank. waste, thus supporting the management of plastic waste and improving the process—recycling to J. Compos. Sci. 2024, 8, 311. https:// promote sustainability and industrial efficiency. One option was using the antioxidant additive doi.org/10.3390/jcs8080311 Irgafos P-168 (IG-P168), which stabilized some of these C-PP-PE residues very well until thermal Academic Editor: Fabrizio Sarasini properties similar to those of pure C-PP-PE were obtained. Received: 27 June 2024 Keywords: DFT; thermodynamic models; catalyst; polypropylene–polyethylene composites; activation Revised: 1 August 2024 energy; degradation Accepted: 6 August 2024 Published: 9 August 2024 1. Introduction Copyright: © 2024 by the authors. Polypropylene (PP) and polypropylene–polyethylene composites (C-PP-PE) are widely Licensee MDPI, Basel, Switzerland. used due to their advantageous properties, such as toughness, tensile strength, tear resis- This article is an open access article tance, flexibility, and chemical, thermal, and moisture resistance. They can be processed distributed under the terms and using techniques such as injection molding, film and fiber extrusion, thermoforming, and conditions of the Creative Commons blow molding, making them versatile and applicable in many areas. However, it is well Attribution (CC BY) license (https:// known that both PP and C-PP-PE are prone to degradation during processing and extended creativecommons.org/licenses/by/ use. Stabilizers are required to prevent this degradation. Consequently, the extensive use 4.0/). J. Compos. Sci. 2024, 8, 311. https://doi.org/10.3390/jcs8080311 https://www.mdpi.com/journal/jcs J. Compos. Sci. 2024, 8, 311 2 of 16 of PP and C-PP-PE is only possible thanks to their stabilization. The degradation and stabilization of post-polymerized pure polypropylene have been the subject of extensive studies, especially between the 1980s and the mid-2000s [1–4]. From the perspective of the linear economy, the life cycle of PP and C-PP-PE consisted of only a processing stage and usage stage before being discarded, following the take-make- use-dispose model. However, it is now recognized that once a material has reached the end of its useful life and is discarded, it should be considered a valuable resource. This approach reduces the demand for raw materials while simultaneously contributing to mitigating plastic pollution, aligning with the circular economy paradigm [5–8]. In the transition to a circular economy, increasing attention is focused on the im- portance of the industry, especially the petrochemical sector, which has shifted its focus toward post-consumer materials, such as plastic packaging waste, considering them a valuable resource [9–11]. Despite a significant portion of collected plastic packaging ending up in landfills or being used for energy recovery, research has intensified in technologies aiming to improve the recycling and chemical transformation of these post-consumer wastes, accounting for 42% of cases. Until 2018, the recycling of plastic packaging waste was mainly carried out through mechanical methods. Still, inherent limitations, such as extensive pre-treatment requirements, have sparked a growing interest in chemical recy- cling as an innovative solution [11–15]. Unlike mechanical recycling, where the chemical structure of the plastic is preserved, chemical recycling in-volves the de-polymerization of plastic packaging waste to obtain smaller hydrocarbons, often through catalytic or thermal processes [6,7]. The renewed interest in the degradation and stabilization of PP and C-PP-PE has emerged due to the need to understand how degradation affects their recyclability [12–14]. However, most of these studies focus solely on describing degradation during re-processing in a molten state, overlooking that degradation throughout the lifespan also exerts a considerable influence on the recyclability of PP and C-PP-PE [16–20]. The oxidation of PP and C-PP-PE is recognized as a heterogeneous process. The presence of catalyst residues, especially compounds containing titanium (Ti), is a possible reason for the heterogeneous onset of PP and C-PP-PE oxidation [21–27]. The influence of these catalyst residues on PP and C-PP-PE oxidation has been detailed in various publications. It is generally accepted as a source for the heterogeneous initiation of material degradation. Once initiated, degradation gradually spreads from these initial points to the rest of the material, progressively affecting the surroundings [28–31]. Sev-eral studies have observed the degradation spread from the initial oxidation point [32,33]. Using polarized optical microscopy, Nakatani and colleagues illustrated initiation and propagation in the amorphous phase of PP and C-PP-PE by adding a small amount of pre-oxidized PP [23–34]. Despite previous studies addressing aspects of the heterogeneous oxidation of PP and C-PP-PE, the present research stands out in its in-depth analysis of the complex mechanisms involved in material degradation [21,24,25,27,35]. While previous works, such as those by Richters [36], Billingham [37], and Blakey et al. [38], have demonstrated het-erogeneity in PP oxidation and the propagation of degradation throughout the polymer, our research delves into a more profound and detailed analysis of the kinetic mecha- nisms involved. This study differentiates itself by investigating in detail how impurities derived from the chemical recycling of plastic waste influence the final properties of the generated products. Understanding degradation kinetics is essential for designing more stable materials, reducing waste, and minimizing environmental impact, enabling the scientific community to optimize processes and foster innovations in various industries. This research includes thermogravimetric analysis (TGA) to determine the macroscopic kinetics of the thermo-catalytic process, providing critical information for understanding degradation kinetics [39–44]. The subsequent research is a testament to innovation in the field, focusing on the kinetic degradation mechanisms of PP and C-PP-PE matrices through pyrolysis. This research, utilizing the Ziegler–Natta catalyst residues as accelerators, identifies resulting J. Compos. Sci. 2024, 8, 311 3 of 16 gases, determines degradation steps through thermodynamic models, and emphasizes the influence of plastic waste composition. The necessity to comprehend degradation kinetics in pyrolysis is underscored, making this comprehensive approach highly relevant and novel. It advances the understanding and optimization of critical processes in sustainable plastic waste management, sparking curiosity and intrigue about the innovative findings it can provide. 2. Materials and Methods 2.1. Sample Collection The residues of non-additive C-PP-PE were generated during their industrial synthesis using heterogeneous Ziegler–Natta catalysis systems (W. R. Grace and Company, Columbia, MD, USA) based on TiCl4 on MgCl2, accompanied by agents for selectivity control and TEAL as a co-catalyst. Specific details of the catalyst composition are detailed in Table 1. Table 1. The composition of the catalytic system. Component Amount (%W/W) White mineral oil (petroleum) ≤75% Magnesium chloride–titanium tetrachloride complex ≤30% Organic ester <7% Diethyl phthalate <5% Isopentane <8% Titanium tetrachloride ≤0.65% Phthalic anhydride ≤0.6% Chlorobenzene ≤0.5% 2-Chloro-1-methylbenzene ≤0.04% Iron chloride ≤0.004% Aluminum chloride ≤0.005% Several samples of non-additive PP and C-PP-PE were identified; the samples were classified as W1, W2, W3, W4, and W5 according to color. All samples were cleaned many times with high-purity nitrogen gas in Agilent brand high-pressure vials with a 20 mL capacity. All samples, including pure polypropylene (PPO), were analyzed immediately. The PP and C-PP-PE were crushed and sieved to obtain an average particle size of 2 mm. A standard Prodex Henschel 115JSS mixer (Federal Equipment Company, Lodi, NJ, USA) was used at 800 rpm for 7 min at room temperature to ensure homogeneity. Subsequently, the samples were mixed by melt extrusion through a Welex-300 extruder (KD Capital Equipment, LLC, Scottsdale, AZ, USA) with process temperatures of 190–220 ◦C. The samples were prepared following the measurements specified in Table 2. Table 2. Sample composition. Moisture, Volatile Matter, Ti Al Cl Fe wt% wt% ppm ppm ppm ppm PPO 0.18 99.49 0.98 8.53 13.37 4.13 W1 0.33 99.49 0.98 320.23 201.03 99.11 W2 0.21 99.49 0.98 171.12 81.71 51.34 W3 0.18 99.49 0.98 5.15 58.75 7.03 W4 0.22 99.49 0.98 5.15 105.23 44.51 W5 0.35 99.49 0.98 410.13 205.33 100.13 2.2. Instrumental Analysis X-ray fluorescence: For the elemental analysis of metals, mainly of catalyst residues (Ti, Al, Fe, and Cl), an X-ray fluorescence Malvern Panalytical Axios FAST elemental analyzer and a Zetium Polymer Edition elemental analyzer were used. J. Compos. Sci. 2024, 8, 311 4 of 16 2.3. Thermogravimetric Analyzer A thermogravimetric analyzer (Perkin Elmer TGA7; Artisan Technology Group ®101 Mercury DriveChampaign, Champaign, IL, USA) was used for the thermal analysis. In each experiment, 10 mg of the sample was placed into an alumina melting pot and pyrolyzed under a high-purity N2 (99.999%) stream with a 60 mL/min flow rate. The heating was performed at a temperature range of 30–600 ◦C and a heating rate of 20 ◦C/min. The experimental errors were lower than 3% in three runs repeated under the same conditions. 2.4. Gas Chromatography (GC-MS) The gas stream from the thermo-oxidative pyrolysis process was collected in a properly deactivated stainless steel cylinder with a capacity of 200 mL. The valve relief was adjusted in a range of 540–600 psi and then analyzed by an Agilent technology chromatograph (Agilent Technologies; 5301 Stevens Creek Blvd Santa Clara, CA, USA) with front and back split/splitless injector ports. The GC apparatus is equipped with seven valves for gas sampling, eight columns of different lengths and polarity, three detectors, one Pulse Discharge Helium Ionization Detector (PDHID), one Universal Flame Ionization Detector (FID), and a mass spectrometer (MS), allowing for the identification of the chemical nature of oxygenates, sulfur, thiols, and permanent gases in a single operation lasting almost 40 min. The setup conditions were as follows: The run time was 37.14 min. The flow of helium carrier gas was adjusted to 2.8 mL min−1. The valve assembly transported the pyrolysis gases to the columns and the detectors. For identifying and quantifying thiols and oxygenated compounds, an MS Agilent InertPlus 5977 (Agilent Technologies; 5301 Stevens Creek Blvd Santa Clara, CA, USA) quadrupole equipped with an electronic impact ionization source, set at 230 ◦C, was used to identify and quantify the thiols and oxygenated compounds. The FID was used for the hydrocarbon family, and the permanent gases were analyzed with the PDHID. The analysis began with the transfer of gases to the chromatograph. At 0.10 min, the gases were directed to the helium carrier and the initial columns for preliminary separation. The first column retained the heavier compounds, allowing CO2 and other lighter components to pass to the next column, which separated the CO2. The subsequent column was used to separate oxygenated compounds, which were then identified using the mass spectrometer. At 0.16 min, most of the sample was directed to a split vent system, while a fraction was sent to a column for heavier hydrocarbons and another for lighter hydrocarbons. At 1.40 min, the sample was moved to a column that retains CO2 and allows CO and other lighter compounds to flow to a final column for separation before detection. The elution order is CO2, H2, argon/O2, methane, and CO. Finally, after the elution of 1-pentene, the heavier components were directed to a final column for removal in the chromatograph’s programmable oven. 2.5. Pyrolysis Setup The pyrolysis and thermo-oxidative degradation of the five industrial residues (ap- proximately 20 g in each run) were carried out in a quartz reactor placed in a horizontal tube furnace. The residue was characterized before pyrolysis and thermo-oxidative degradation, to determine its chemical composition. Pyrolysis was carried out in a N2 atmosphere fol- lowed by thermo-oxidative degradation. To ensure that the environment was inert during the experiments, a flow of N2 of 100 mL min−1 was continuously passed through the reactor. The pyrolysis and thermo-oxidative degradation temperature was 550 ◦C, at a constant heat- ing rate of 10 ◦C/min. The gases obtained were collected in metal cylinders with sulfinert alloy, to prevent sulfur compounds from being absorbed, thereby impeding their quantifi- cation and being reported as pyrolysis and thermo-oxidative degradation impurities. 2.6. Thermodynamical Analysis The models of Coats–Redfern [45] and Horowitz–Metzger [46] were used for the thermodynamic calculations. Both models have a linear approach in which several ther- J. Compos. Sci. 2024, 8, 311 5 of 16 modynamic parameters, such as activation energy and collision factor, can be determined. Indeed, these mathematical methods have been extensively used in the kinetic analysis of the thermal decomposition of many solid materials. The different models plot the mass loss rate as a function of temperature or the reciprocal of temperature. 2.7. Kinetic Modeling Isoconversional methods study how pure plastics or mixtures of plastic waste decom- pose over time. This approach makes it possible to calculate three critical factors in the decomposition rate, assuming that the conversion rate is related to the amount of reactive substances present. This allows us to describe the decomposition rate using Equation (1), which considers how the conversion rate changes during the heating process. dα dα = β = k(T) f (α) (1) dt dT In this equation, β represents the heating rate (in degrees Celsius per minute), α is the conversion, f (x) is a function that describes the kinetics with the conversion, and k(T) is a constant function that depends on temperature. The conversion is defined by Equation (2). mi − mα = (2) mi − m f In this equation, mi represents the initial mass, m indicates the mass at a specific point during the degradation process, and mf is the final mass. The application of the Arrhenius equation involves the following: dα Ae(− Eaβ = /RT) f (α) (3) dT In Equation (3), Ea represents the activation energy in kJ mol−1, A represents the pre-exponential factor (s−1), and R is the gas constant. This equation describes how the conversion rate varies with temperature, depending on the rate at which it is heated. This is crucial for understanding the isoconversional kinetic models that will be explained later. 2.7.1. Method 1 and 2: Coats–Redfern and Horowitz–Metzger This study used approaches that did not involve constant temperature conditions, such as the Arrhenius equation and various methods like Horowitz–Metzger, Coats–Redfern, and Flynn–Wall–Ozawa. These methods were employed to obtain information on the kinetic properties of PP resins with residues from different metals, such as their activation energy and frequency factor, from data obtained through TG/DTG. In the Coats–Redfern method, the functions f (α) can be used to determine the kinetic parameters. Their representation is giv[en by(Equation)(4]): f (α) AR − 2RT − Ealn 2 = ln 1 (4)T βEa Ea RT A represents the pre-exponential part. The values of activation energy and pre- exponential parameters for each f (α) function can be determined using a least squares linear regression approach, using the slopes and intercepts of the ln(f (α)/T2) graphs as a function of 1/T. The Horowitz–Metzge[r model is fo]rmulated as follows: W f θEaln ln − = − log2.303 (5)W f W 2.303RT2 In the equation, Wf refers to the amount of mass lost at the end of the first decompo- sition process, while W is the mass loss up to a certain temperature (T). If we plot ln[ln J. Compos. Sci. 2024, 8, 311 6 of 16 Wf/(Wf − W)] as a function of θ, we will obtain a straight line. The slope of this line provides us with the value of Ea (activation energy). 2.7.2. Method 3: Flynn–Wall–Ozawa (FWO) The calculation of Doyle’s temperature integral forms the basis for the Flynn–Wall– Ozawa (FWO) approach, which uses a specific mathematical expression, p(x) = exp(−1.052.x − 5.331). This expression is presented differently in Equation (6). To determine activation energies, the FWO technique was employed, which is based on the slope of a fitted linear function that relates lnβ to 1/T.( ) Ea Ea ln P = −5.331 − 1.052 (6) RT RT ln (1 − (1 − α)1/2 AR − − Ea) = ln ln β 5.331 − 1.052 Ea RT 2.7.3. Method 4: Kissinger–Akahira–Sunose (KAS) The KAS method is an integral isoconversion technique that relies on the Coats– Redfern approximation (4) a(nd us)es a fit of Equation (3). This standard Formula (7) can beexpressed as follows: Ea e((− Ea/)RT) R2T2e(− Ea/RT)P = = (7)RT ( E)a 2 Ea2 RTm 1 − (1 − α)1/2 AR Ea ln 2 = ln − ln β − (8)Tm Ea RT To calculate the activation energy (Ea) and the pre-exponential factor (A), a linear regression of ln [1 − (1 − α)(1/2)] against 1/T 2m is performed. 3. Results 3.1. Kinetic Parameters The determination of the overall activation energy of the degradation process is a chemical kinetic parameter that provides a comprehensive understanding of the catalytic effect compared to a non-catalytic process [47–50]. Tables 3 and 4 display the results obtained for the activation energy for each isoconversion model, ranging from 0.09 to 885.41 kJ/mol, along with their respective equations, by applying the R2 contraction cylinder mechanism, as recommended by Dubdub et al. [51]. This approach proved to be suitable for this type of mixture. Table 3. Kinetic parameters obtained by Horowitz and Metz and Coats and Redfern methods. Sample Stages Name Mechanism Ho(rowit)z and Metz (HM) Ea/kJ Coats and Redfern (CR) Ea/kJ A 1 ln(ln( 11−α ) = 0.1994θ + 4.6222 412.73 ln [−ln(1−α)] =−301002 T + 31.462 250.26 4.22 × 1017T PPO 2 ln(ln( 11−α ) = 0.0422θ − 1.1644 173.48 ln [−ln(1−α)] =−15304 + 7.1851 127.24 6.01 × 106T2 T 3 ln(ln ( 1 )= 0.0667θ − 1.0588 274.19 ln [ −ln(1−α)] =−29053− 2 T + 27.39 241.56 6.76 × 10 15 1 α T 1 ln(ln( 1 [−ln(1−α)]1−α) = 0.0002θ + 1.056 0.82 ln =−3257.8 − 9.9442 27.092 T 1.90 × 107T W 2 ln(ln ( 11 1−α )= 0.0007θ + 1.1483 2.88 ln [−ln(1−α)] −7175,4T2 = T − 3.7459 59.66 9.40 × 104 3 ln(ln( 11−α ) = 0.0171 1.882 70.30 ln [ −ln(1−α)] θ + =−18731 + 13.498 155.742 T 4.00 × 10 9 T 1 ln(ln( 1 65.361−α) = 0.0159θ − 2.693 ln [−ln(1−α)] =−3859.8 − 9.9783 32.092 T 2.49 × 107T W2 2 ln [−ln(1−α)] (ln( 1 155.39 −8522.1 70.86 1.85 × 1041−α ) = 0.0378θ − 1.3818 ln T2 = T − 1.9798 3 ln(ln 11−α = 0.0755θ − 1.4893 310.37 ln [−ln(1−α)] =−34837 + 37.033 289.652 T 1.20 × 10 20 T J. Compos. Sci. 2024, 8, 311 7 of 16 Table 3. Cont. Sample Stages Name Mechanism Ho(rowit)z and Metz (HM) Ea/kJ Coats and Redfern (CR) Ea/kJ A 1 ln(ln( 11−α( ) = 0.0546θ − 0.3011 224.45 ln [−ln(1−α)] =−172282 T + 10.837 143.68 2.48 × 10 8 T W 2 ln [−ln(1−α)](ln 1 ) = 0.0425θ − 1.6025 174.71 ln =−26804 + 25.08 222.86 6.25 × 10143 1−α T2 T 3 ln(ln ( 1 )= 0.0663θ − 1.2822 272.55 ln [ −ln(1−α)] =−41516 + 45.98 345.18− 2 T 1.16 × 10 24 1 α T 1 ln(ln( 1 ) = 0.036θ − 2.7017 147.99 ln [−ln(1−α)] =−5153.7 − 6.9419 42.84− 2 T 1.50 × 1061 α T W 2 ln ln ( 1 ) 0.0146 − 2.3436 60.02 ln [−ln(1−α)]4 ( = θ =−10399 + 1.4298 86.46 1.24 × 1041−α T2 T 3 ln(ln( 11−α) = 0.035 − 0.9313 143.88 ln [ −ln(1−α)] θ =−32138 + 33.239 267.21 2.47 × 1018T2 T 1 ln ln ( 1 ) 0.0259 − 2.1057 106.47 ln [−ln(1−α)]( = θ =−3174.7 − 9.6004 26.40− 2 T 1.37 × 1071 α T W5 2 ln(ln( 1− ) = 0.0139 − 1.379 57.14 ln [−ln(1−α)]θ =−84772 T − 0.6612 70.48 5.00 × 1031 α T 3 ln(ln 1 = 0.0313θ − 0.3835 128.67 ln [−ln(1−α)] =−30100− 2 T + 24.342 212.09 2.67 × 10 14 1 α T Table 4. Kinetic parameters obtained by Flynn–Wall–Ozawa and Kissinger–Akahira–Sunose methods. Sample Stages Flynn–Wall–Ozawa (FWO) Kissinger–Akahira–Sunose (KAS) Name Mechanism ( Equ)ation Ea/kJ A ( Eq)uation Ea/kJ A 1 ln(1 − (1 − α)1/2) = −1357.23 + 0.5694 10.73 1.38×105 ln( 1−(1−α) 1/2 ) = −357.23 − 12.542 2.97 2.92 × 107T T 2m T 2 ln( 1 − (1 − α)1/2) = −1299.20 + 1.9797 10.27 5.66×105 ln( 1−(1−α) 1/2 ) = −1299.2 − 11.131 10.80PPO 7.14 × 106T T 2m T 3 ln 1 − (1 − α)1/2 = −7808.80 + 17.1200 61.72 2.13×1012 ln 1−(1−α) 1/2 = −106490 + 135.43 885.41 6.66 × 1060 ( ) T ( T 2m ) T 1 ln( 1 − (1 − α)1/2) = −147.18 + 0.3854 1.16 1.15×105 ln ( 1−(1−α) 1/2 −147.18 T 2 )= T − 13.497 1.22 7.63 × 107Tm W 2 ln (1 − (1 − α)1/2 )= −2762.90 + 3.6557 21.83 3.04×106 ( 1−(1−α) 1/2 ln ) = −3411.70 − 8.506 28.37 5.14 × 1051 T T 2m T 3 ln 1 − (1 − α)1/2 = −3306.80 + 4.47 26.14 6.83×106 ln 1−(1−α) 1/2 = −4103.80 − 7.521 34.12 1.89 × 105 ( ) T ( T 2m ) T 1 1/2ln (1 − (1 − α)1/2 )= −385.40 + 0.4659 3.05 6.83×106 ln( 1−(1−α) ) = −385.40 − 12.619 3.20 3.10 × 107T T 2m T 2 ln( 1 − (1 − α)1/2) = −346.59 + 0.403 2.74 1.17×105 ln (1−(1−α) 1/2 )= −344.02 7W2 T 2 T − 12.712 2.86 3.43 × 10Tm 3 1/2 −335.79 2.65 1.15×105 1−(1−α)1/2ln 1 − (1 − α) = + 0.3876 7ln = −338.00 − 12.72 2.81 3.43 × 10 ( ) T ( T 2m ) T 1 ln( 1 − (1 − α)1/2) = −11.52 − 0.672 0.09 1.53×105 ln( 1−(1−α) 1/2 = −19.32T − 8 13.770 0.16 1.03 × 10 T 2m ) T 2 ln( 1 − (1 − α)1/2) = −167.40W + 1.8677 13.23 5.07×105 ln( 1−(1−α) 1/2 ) = −2745.00 − 9.671 22.82 1.71 × 1063 T T 2m T 3 ln 1 − (1 − α)1/2 = −6423.20 + 8.6611 50.77 4.69×108 ln 1−(1−α) 1/2 = −6312.60 − 4.591 52.49 1.04 × 104 ( ) T ( T 2m ) T 1 ln( 1 − (1 − α)1/2) = −59.38 + 0.5747 0.47 1.39×105 ( 1−(1−α) 1/2 −59.38 0.49 8.44 × 107 T ln T 2 ) = T − 13.686m 1/2 −2011.40 W 2 ln (1 − (1 − α) )= + 2.4262 15.90 8.88×105 ( 1−(1−α) 1/2 ln ) = −2801.304 T 2 T − 9.526 23.29 1.40 × 106Tm 3 1/2ln 1 − (1 − α)1/2 = −3781.90 29.89 1.28×107 1−(1−α) −52237.20 43.54 4.67 × 104 ( ) T + 5.098 ln ( 2 )= T − 6.057Tm 1 ln( 1 − (1 − α)1/2) = −158.58 − 0.3758 1.25 1.14×105 ln( 1−(1−α) 1/2 ) = −158.58 − 13487 1.32 7.63 × 107T T 2m T 2 ln (1 − (1 − α)1/2 )= −2445.90W + 3.1623 19.33 1.85×106 1/2 7 5 T ln( 1−(1−α) ) = −3079.80 − 9.020 25.61 7.48 × 10T 2m T 3 ln 1 − (1 − α)1/2 = −5338.30 + 7.186 42.19 1.03×108 ln 1−(1−α) 1/2 = −4207.20 − 7.415 34.98 1.71 × 105T T 2m T Mechanism of Pyrolysis Understanding the mechanism of a chemical reaction is fundamental in industry and science, as it provides a step-by-step understanding of the transformation process of reactants, allowing researchers to predict product outcomes, optimize reaction condi- tions, and devise strategies to synthesize new compounds more efficiently. In this sense, a thermodynamic and mechanistic analysis of the pyrolysis of pure polypropylene (PPO) and PP matrices contaminated with Ziegler–Natta-type metal catalyst residues in an inert N2 atmosphere is presented below. The pyrolytic process was recorded using TGA, and pyrolysis effluent gases were analyzed using GC-MS to identify the identities of the emerg- ing gases and propose a decomposition mechanism. Catalyst residues are predicted to J. Compos. Sci. 2024, 8, 311 8 of 16 catalyze the process, decreasing the activation energy of the polymer matrix decomposition. Naturally, the physicochemical processes are related to multiple discrete numbers, both in the quantities of the substances consumed and in the products formed (Law of definite proportions); similarly, in a thermogravimetric run, an intrinsic relationship is recorded, in which the mass decreases by evaporation depending on the boiling temperature and chemical properties of the substances formed. This dynamic allows us to obtain an almost fingerprint thermodynamic record of the processes, allowing us to determine the velocity counters and the energy barriers associated with the discrete mass losses, which change from one particular process to another. In the pyrolysis process of polypropylene, three J. Compos. Sci. 2024, 8, x FOR PEER REdViIsEtWin ct linear trends in mass change were identified, allowing us to propose three m9a orfk e1d7 stages or steps during the process. These stages were observed in the temperature ranges of 370–610 ◦C, 620–660 ◦C, and 670–750 ◦C, with some variations (see Figure 1). FFiigguurree 11.. A TThheerrmaall ddeeccaayyiinngg mooddeella accccoordrdininggt ototh tehefo flolollwowinign:g(:a ()aC) oCaotsatasn adnRde Rdfeedrfne;r(nb; )(Hb)o Hroowroit-z wanitzd aMnedt zM; (ectz) K; (ics)s iKnigsesirn–gAekra–hAikr a–hSiuran–oSsuen(oKsAe S(K);AanSd); (adn)dF (ldy)n Fnl–yWnnal–lW–Oazlla–wOaza(FwWa O(F)W. O). Table O5.n Etlehmeeontthael rchhaarnacdte, rtihzaetiporno apnods eadctisvtaatgioens eanreergsiueps pofo PrtPeOd abnydt PhPe mstaatbriiclietsy caontdamcoinacteend - wtriathti oZnN ocafttahlyestssu. b* sHtaornocwesitzf oaundn dMientzgthere mgeatsheoodu. s**e Cfflouatesn atnsdo Rfepdyferronl ymseisth, oadls. o***b aFslyendn–oWnatlhl–e Othzeaowrae. t*i*c*a*l Kgiussiidnegleirn–eAskeashtiarba–liSsuhneodseb. y organic chemistry “summarizing, from the most re- duced to the most oxidized substances”. In detail, after melting the solid PPO matrix Sample Name Activation Energies Elemental Composition of Catalyst Residues * Ea/kJ ** Ea/kJ *** Ea/kJ **** Ea/kJ Ti/ppm Al/ppm Cl/ppm Fe/ppm 412.73 250.26 10.73 2.97 PPO 173.48 127.24 10.27 10.80 0.98 8.53 13.37 4.13 274.19 241.56 61.72 885.41 0.82 27.09 1.16 1.22 W1 2.88 59.66 21.83 28.37 0.98 320.23 201.03 99.11 70.3 155.74 26.14 34.12 65.36 32.09 3.05 3.20 W2 155.39 70.86 2.74 2.86 0.98 171.12 81.71 51.34 310.37 289.65 2.65 2.81 W3 224.45 143.68 0.09 0.16 0.98 5.15 58.75 7.03 J. Compos. Sci. 2024, 8, 311 9 of 16 (approx. 300–350 ◦C), no variation in mass percentage is observed. It is expected that the initial stage corresponds to a process of the decomposition or de-polymerization of the linear chains to form reactive hydrocarbon structures of smaller size, free radical type; this process is quite complex and dynamic due to the number of free radicals formed. Although TEAL and TiCl4 residues may influence the process, their exact catalytic role requires further investigation (see Table 5). Table 5. Elemental characterization and activation energies of PPO and PP matrices contaminated with ZN catalysts. * Horowitz and Metzger method. ** Coats and Redfern method. *** Flynn–Wall– Ozawa. **** Kissinger–Akahira–Sunose. Sample Activation Energies Elemental Composition of Catalyst Residues Name * Ea/kJ ** Ea/kJ *** Ea/kJ **** Ea/kJ Ti/ppm Al/ppm Cl/ppm Fe/ppm 412.73 250.26 10.73 2.97 PPO 173.48 127.24 10.27 10.80 0.98 8.53 13.37 4.13 274.19 241.56 61.72 885.41 0.82 27.09 1.16 1.22 W1 2.88 59.66 21.83 28.37 0.98 320.23 201.03 99.11 70.3 155.74 26.14 34.12 65.36 32.09 3.05 3.20 W2 155.39 70.86 2.74 2.86 0.98 171.12 81.71 51.34 310.37 289.65 2.65 2.81 224.45 143.68 0.09 0.16 W3 174.71 222.86 13.23 22.82 0.98 5.15 58.75 7.03 272.55 345.18 50.77 52.49 147.99 42.84 0.47 0.49 W4 60.02 86.46 15.90 23.29 0.98 5.15 105.23 44.51 143.88 267.21 29.89 43.54 106.47 26.4 1.25 1.32 W5 57.14 70.48 19.33 25.61 0.98 410.13 205.33 100.13 128.67 212.09 42.19 34.98 In this study, the magnitude of changes in activation energy is presented sequentially using the three methods (see Tables 3 and 4). It has been observed that the activation energies calculated using the Coats–Redfern method are lower than those obtained with the other two methods. Conversely, the Ea values computed using the Chan et al. [52] method are lower than those obtained by the Horowitz and Metzger method but higher than those from the Coats and Redfern method. These variations in activation energies calculated with the three method may be attributed to different approximations of the temperature integral [3]. It is important to note that while these values may not be the most precise, they provide an approximate range of parameters. Activation energy data obtained by each specific method can be conveniently used to compare the relative thermal stability of different polymers. The complexity of the process is reflected in the wide range of temperatures involved; it can be proposed that this is an extensive and dynamic process, as initially, the long PPO chains must be decomposed to give rise to the formation of lower-molecular weight hydrocarbons, such as propylene, ethylene, etc. In PPO or PP without catalyst residues, bond breaking is purely thermal. There are two methods to break a bond: using pure thermal energy or through the intervention of a catalyst, which lowers the energy barrier and increases the effectiveness of interactions (making collisions more effective). TEAL and TiCl4 residues reduced the activation energy by approximately 50–90% (Table 5). In the subsequent phase, the most probable and concentrated secondary by-products found in the pyrolysis exhaust gases are more stable alkanes, alkenes, and alkynes, such as methane, ethane, isopentane, and propylene. These compounds are formed from the most likely J. Compos. Sci. 2024, 8, 311 10 of 16 radicals: methyl, ethyl, and propyl. These hydrocarbons were found in concentrations of approximately 6–57%. This process is faster due to the high reactivity of the precursor radicals. Additionally, it is associated with a shorter temperature range and reduced process time; this is also due to the high reactivity of the precursors and the less condensed phase in which they are found, which accelerates and facilitates more effective collisions, leading to the final products reported here (Schemes 1 and 2). Finally, the oxidation of hydrocarbons (alkanes and alkenes) consumes all the oxygen, nitrogen, sulfur, and part of the hydrogen from the oxygenated structures and the remaining water vapor, leading to the formation of alcohols, ketones, carboxylic acids, and combustion gases such as CO2, H2S, etc. (Table 6). The oxidized substances were found in low concentrations (below 1%) due to the low availability of oxidizing species. The second phase occurs rapidly and over a shorter temperature range due to the higher reactivity of the formed species (ordinary molecular weight alkyl radicals). In summary, once the polymeric matrix is molten, it decomposes thermally or catalytically; the reactive species lead to the formation of stable hydrocarbons, which are then oxidized to form alcohols, ketones, and other oxidized species. After analyzing the physicochemical process of the anaerobic decomposition of PP and the intermediate by-products, it is possible to design a catalytic protocol to J. Compos. Sci. 2024, 8, x FOR PEER REVIE de Wco mpose polymeric matrices into hydrocarbons that can later be used in the energy an1d1 of 17 J. Compos. Sci. 2024, 8, x FOR PEER RpEeVtIrEoWch emical industries. 11 of 17 SchSSeccmhheem 1ee. 1A1.. Apr porrpoopoosoesseded m meeeccchhaanniissm ffoorr t ththheee dd deececocomomppoopssoiittsiioiotnnioo onff p opofo lplyypoprlroyoppyryloleepnnyee.l.e ne. HOHO OOH OO O O OH OH CHCH [ [OO]] CH3 + 3 3+ + CH3 + [ H C OH C H C3 H3C H C ] [ H C 3 O 3 3 H C 3 ](<1%) (<1%) 3 (<1%) H3(