On the Method of Pulse-Heated Analysis of Solid Reactions (PHASR) for Polyolefin Pyrolysis

Insight into pyrolysis mechanism of plastic waste with C-O/C-N bonds in the backbone

Pyrolysis is an important method for efficiently recovering plastic monomers, fuels and chemicals from plastic waste. The depolymerization of the backbone structure of plastic waste is a key step of the pyrolysis process. Currently, researches on the pyrolysis mechanism of plastics with C-O/C-N bonds in the backbone are still not sufficiently in-depth and also lack systematic and comprehensive investigation. Therefore, this study for the first time comprehensively investigated both macroscopic and microscopic pyrolysis processes of plastics with C-O/C-N bonds in the backbone, and evaluated the difficulty of breaking different backbone linkages via bond dissociation energy (BDE) obtained by density functional theory (DFT) calculations to deeply reveal the pyrolysis mechanism. The results indicated that polyethylene terephthalate (PET) had a higher initial pyrolysis temperature and its thermal stability was slightly stronger than nylon 6. The backbone of PET was mainly decomposed via the cleavage of Cα-O on the alkyl side, while the degradation of nylon 6 backbone began with NH2 groups at the end of the backbone. The pyrolysis products of PET were mainly derived from the small molecular fragments, which were generated by the degradation of the backbone through the cleavage of CO bonds or CC bonds, while the pyrolysis products of nylon 6 were always dominated by caprolactam. In addition, based on the results of DFT calculations, it could be inferred that the cleavage of CC bond in PET backbone and the cleavage of its adjacent Cα-O were most likely to occur, which followed a competitive reaction mechanism. However, in pyrolysis of nylon 6, the conversion to caprolactam was mainly via the concerted reaction of amide CN bonds. Compared with the concerted cleavage of amide CN bond, the cleavage of CC bond in the backbone of nylon 6 was not predominant.

Production of diesel-range oil through pyrolysis of polyolefins recovered from municipal solid waste

Pyrolysis is an effective method to valorize plastic waste and obtain value-added fuels. This study adopted the ANN-GA (artificial neural network-genetic algorithm) coupled with a central composition factorial design to optimize the oil production from the pyrolysis of waste polyolefins (WP). The interactive effects of PE mass fraction (20-80 wt%), residence time (20-60 min), and carrier gas flow rate (0-100 mL/min) on the yields of WP pyrolysis products were investigated extensively by ANN. Moreover, the highest WP pyrolysis oil production of 78.87 wt%, optimized by GA, was obtained under 80 wt% PE, 60 min, and 0 mL/min. It was found that the different conditions of PE mass fraction, residence time, and carrier gas flow rate did not change the types of oil's main functional groups (-CH2-, -C=C-, -C=CH2, -CH3, and =C-H). The conditions affected the WP pyrolysis oil fractions significantly. The highest diesel selectivity of 91.42% was obtained under 20 wt% PE, 20 min, and 0 mL/min. Additionally, according to the interactive effects of different conditions on the productions of WP pyrolysis products, the pyrolysis pathways were proposed to understand the pyrolysis mechanism of WP better.

Machine Learning Predictions of Oil Yields Obtained by Plastic Pyrolysis and Application to Thermodynamic Analysis

Chemical recycling via thermal processes such as pyrolysis is a potentially viable way to convert mixed streams of waste plastics into usable fuels and chemicals. Unfortunately, experimentally measuring product yields for real waste streams can be time- and cost-prohibitive, and the yields are very sensitive to feed composition, especially for certain types of plastics like poly(ethylene terephthalate) (PET) and polyvinyl chloride (PVC). Models capable of predicting yields and conversion from feed composition and reaction conditions have potential as tools to prioritize resources to the most promising plastic streams and to evaluate potential preseparation strategies to improve yields. In this study, a data set consisting of 325 data points for pyrolysis of plastic feeds was collected from the open literature. The data set was divided into training and test sub data sets; the training data were used to optimize the seven different machine learning regression methods, and the testing data were used to evaluate the accuracy of the resulting models. Of the seven types of models, eXtreme Gradient Boosting (XGBoost) predicted the oil yield of the test set with the highest accuracy, corresponding to a mean absolute error (MAE) value of 9.1%. The optimized XGBoost model was then used to predict the oil yields from real waste compositions found in Municipal Recycling Facilities (MRFs) and the Rhine River. The dependence of oil yields on composition was evaluated, and strategies for removing PET and PVC were assessed as examples of how to use the model. Thermodynamic analysis of a pyrolysis system capable of achieving oil yields predicted using the machine-learned model showed that pyrolysis of Rhine River plastics should be net exergy producing under most reasonable conditions.

Depolymerization of plastics by means of electrified spatiotemporal heating

Depolymerization is a promising strategy for recycling waste plastic into constituent monomers for subsequent repolymerization1. However, many commodity plastics cannot be selectively depolymerized using conventional thermochemical approaches, as it is difficult to control the reaction progress and pathway. Although catalysts can improve the selectivity, they are susceptible to performance degradation2. Here we present a catalyst-free, far-from-equilibrium thermochemical depolymerization method that can generate monomers from commodity plastics (polypropylene (PP) and poly(ethylene terephthalate) (PET)) by means of pyrolysis. This selective depolymerization process is realized by two features: (1) a spatial temperature gradient and (2) a temporal heating profile. The spatial temperature gradient is achieved using a bilayer structure of porous carbon felt, in which the top electrically heated layer generates and conducts heat down to the underlying reactor layer and plastic. The resulting temperature gradient promotes continuous melting, wicking, vaporization and reaction of the plastic as it encounters the increasing temperature traversing the bilayer, enabling a high degree of depolymerization. Meanwhile, pulsing the electrical current through the top heater layer generates a temporal heating profile that features periodic high peak temperatures (for example, about 600 °C) to enable depolymerization, yet the transient heating duration (for example, 0.11 s) can suppress unwanted side reactions. Using this approach, we depolymerized PP and PET to their monomers with yields of about 36% and about 43%, respectively. Overall, this electrified spatiotemporal heating (STH) approach potentially offers a solution to the global plastic waste problem.

Hydrogenolysis of Polyethylene and Polypropylene into Propane over Cobalt-Based Catalysts

The development of technologies to recycle polyethylene (PE) and polypropylene (PP), globally the two most produced polymers, is critical to increase plastic circularity. Here, we show that 5 wt % cobalt supported on ZSM-5 zeolite catalyzes the solvent-free hydrogenolysis of PE and PP into propane with weight-based selectivity in the gas phase over 80 wt % after 20 h at 523 K and 40 bar H2. This catalyst significantly reduces the formation of undesired CH4 (≤5 wt %), a product which is favored when using bulk cobalt oxide or cobalt nanoparticles supported on other carriers (selectivity ≤95 wt %). The superior performance of Co/ZSM-5 is attributed to the stabilization of dispersed oxidic cobalt nanoparticles by the zeolite support, preventing further reduction to metallic species that appear to catalyze CH4 generation. While ZSM-5 is also active for propane formation at 523 K, the presence of Co promotes stability and selectivity. After optimizing the metal loading, it was demonstrated that 10 wt % Co/ZSM-5 can selectively catalyze the hydrogenolysis of low-density PE (LDPE), mixtures of LDPE and PP, as well as postconsumer PE, showcasing the effectiveness of this technology to upcycle realistic plastic waste. Cobalt supported on zeolites FAU, MOR, and BEA were also effective catalysts for C2-C4 hydrocarbon formation and revealed that the framework topology provides a handle to tune gas-phase selectivity.

Multi-Scale Modeling of Plastic Waste Gasification: Opportunities and Challenges

Among the different thermo-chemical recycling routes for plastic waste valorization, gasification is one of the most promising, converting plastic waste into syngas (H₂+CO) and energy in the presence of an oxygen-rich gas. Plastic waste gasification is associated with many different complexities due to the multi-scale nature of the process, the feedstock complexity (mixed polyolefins with different contaminations), intricate reaction mechanisms, plastic properties (melting behavior and molecular weight distribution), and complex transport phenomena in a multi-phase flow system. Hence, creating a reliable model calls for an extensive understanding of the phenomena at all scales, and more advanced modeling approaches than those applied today are required. Indeed, modeling of plastic waste gasification (PWG) is still in its infancy today. Our review paper shows that the thermophysical properties are rarely properly defined. Challenges in this regard together with possible methodologies to decently define these properties have been elaborated. The complexities regarding the kinetic modeling of gasification are numerous, compared to, e.g., plastic waste pyrolysis, or coal and biomass gasification, which are elaborated in this work along with the possible solutions to overcome them. Moreover, transport limitations and phase transformations, which affect the apparent kinetics of the process, are not usually considered, while it is demonstrated in this review that they are crucial in the robust prediction of the outcome. Hence, possible approaches in implementing available models to consider these limitations are suggested. Finally, the reactor-scale phenomena of PWG, which are more intricate than the similar processes-due to the presence of molten plastic-are usually simplified to the gas-solid systems, which can result in unreliable modeling frameworks. In this regard, an opportunity lies in the increased computational power that helps improve the model's precision and allows us to include those complexities within the multi-scale PWG modeling. Using the more accurate modeling methodologies in combination with multi-scale modeling approaches will, in a decade, allow us to perform a rigorous optimization of the PWG process, improve existing and develop new gasifiers, and avoid fouling issues caused by tar.

Study of the Viscosity and Thermal Characteristics of Polyolefins/Solvent Mixtures: Applications for Plastic Pyrolysis

Plastic pollution is one of the biggest environmental problems that the world is currently facing. Pyrolysis is a frontier technique aimed at converting plastic waste back into virgin-quality resin. However, the transfer of the waste plastic feed into the pyrolysis reactor must be optimized before the process can be upscaled to a continuous process. In this study, a new solvent that reduces the viscosity of molten plastic was introduced and characterized. The results revealed that the polymers are soluble in the ratio of up to 75 wt % plastic and 25 wt % solvent at 240 °C. The viscosity of pure low-density polyethylene (LDPE), high-density polyethylene (HDPE), and polypropylene (PP) in the solvent was measured in different weight percentages of polymer in solvent (30-80 wt %) and at 160, 180, 200, 220, 240, and 260 °C. The viscosity decreased with the decreasing polymer-weight percentage and with increasing temperature. The viscosity of LDPE/solvent and PP_s(isotactic)/solvent is much lower than for HDPE/solvent and PP_p(polypropylene impact copolymer)/solvent. Differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA) were applied to characterize the thermal behavior of LDPE, HDPE, and PP in the solvent in three different weight percentages (25, 50, and 75 wt %). The DSC results indicate that in the mixture of PP_s/solvent and LDPE/solvent the melting point of PP and LDPE decreases as the amount of solvent increases. Overall, these results indicate that the selected solvent is an effective agent to prepare waste plastics for pyrolysis.