Modeling the kinetics of hydrogen abstraction reactions in nitrogen-containing compounds via group additivity.

New group additivity values are presented to enable the modeling of a broad range of intermolecular hydrogen abstraction reactions involving nitrogen-containing compounds. From a dataset of 316 reaction rate coefficients calculated at the CBS-QB3 level of theory in the high-pressure limit, 76 group additivity values and 14 resonance corrections have been estimated. The influence of substituents on both the attacked hydrogen and attacking radical, being a carbon or nitrogen atom, has been investigated systematically. The new group additivity models can be applied to approximate the Arrhenius parameters of hydrogen abstraction reactions of nitrogen-containing compounds by hydrogen atoms, carbon-centered and nitrogen-centered radicals in the 300-1800 K temperature range. Complementary to the group additivity model, correlations for the tunneling coefficients, which depend on both the temperature and the activation energy of the reaction in the exothermic direction, have been generated. The good performance of the new group additivity schemes has been demonstrated using a test set of reactions. At 1000 K, the rate coefficients for all test set reactions are approximated on average within a factor of 1.45, 1.47 and 1.34, for the hydrogen abstractions with a reactive center of the type H-H-N, N-H-N and C-H-N respectively.

Modeling the thermochemistry of nitrogen-containing compounds via group additivity.

First-principles based kinetic modeling is essential to gain insight into the governing chemistry of nitrogen-containing compounds over a wide range of technologically important processes, e.g. pyrolysis, oxidation and combustion. It also enables the development of predictive, fundamental models key to improving understanding of the influence of nitrogen-containing compounds present as impurities or process additives, considering safety, operability and quality of the product streams. A prerequisite for the generation of detailed fundamental kinetic models is the availability of accurate thermodynamic properties. To address the scarcity of thermodynamic properties for nitrogen-containing compounds, a consistent set of 91 group additive values and three non-nearest-neighbor interactions has been determined from a dataset of CBS-QB3 calculations for 300 species, including 104 radicals. This dataset contains a wide range of nitrogen-containing functionalities, i.e. imine, nitrile, nitro, nitroso, nitrite, nitrate and azo functional groups. The group additivity model enables the approximation of the standard enthalpy of formation and standard entropy at 298 K as well as the standard heat capacities over a large temperature range, i.e. 300-1500 K. For a test set of 27 nitrogen-containing compounds, the group additivity model succeeds in approximating the ab initio calculated values for the standard enthalpy of formation with a MAD of 2.3 kJ mol-1. The MAD for the standard entropy and heat capacity is lower than 4 and 2 J mol-1 K-1, respectively. For a test set of 11 nitrogen-containing compounds, the MAD between experimental and group additivity approximated values for the standard enthalpy of formation amounts to 2.8 kJ mol-1.

Valorizing the Steel Industry Off-Gases: Proof of Concept and Plantwide Design of an Electrified and Catalyst-Free Reverse Water-Gas-Shift-Based Route to Methanol.

Conversion of steel industry off-gases to value-added chemicals enabled by renewable electricity can significantly reduce the environmental burden of the steelmaking process. Herein, we demonstrate that CO2 reduction by H2, both contained in steel mill off-gases, to form syngas via the reverse water-gas-shift reaction is effectively performed by nanosecond pulsed discharges at atmospheric pressure. The experimental results suggest the following: (i) An optimum interelectrode distance exists, maximizing CO2 conversion. (ii) CO2 conversion at constant SEI follows a nonmonotonic trend with H2 excess. CO2 conversion increases with H2 excess up to H2:CO2 = 3:1 upon shifting the chemical equilibrium. At larger H2:CO2, both gas cooling, promoted by the high H2 content, and hindered CO2 collisions in a highly diluted stream hamper CO2 conversion. (iii) SEI enhances CO2 conversion, but the effect decreases with increasing SEI due to equilibrium limitations. A stoichiometric H2:CO2 feed ratio in the plasma reactor is recommended for higher energy efficiency. Intensifying MeOH productivity via SEI elevation is not advised as a 2-fold SEI increase results only in 17% higher MeOH throughput.

Enhanced Sensitivity in Comprehensive Liquid Chromatography: Overcoming the Dilution Problem in LC × LC via Temperature-Responsive Liquid Chromatography.

In comprehensive two-dimensional liquid chromatography (LC × LC), solvents of high eluotropic strength are frequently used in the first dimension (1D), which lead to peak broadening in the second dimension (2D). In the majority of the current LC × LC column combinations, analytes are less than optimally refocused upon transfer to the second column, which negatively affects sensitivity. Furthermore, the typical combination of 1 or 2.1 mm columns in the 1D paired with a 3 mm (or broader) column in the 2D leads to at least a 9- or 4-fold dilution and a corresponding loss of sensitivity when using concentration-sensitive detectors. This occurs due to the enhanced radial dilution of the analytes in a broader column, while the sensitivity problem is further exacerbated in LC × LC due to the high flow operated 2D. In this paper, we introduce a solution to neutralize and inverse this dilution problem through a reconcentrating solution using temperature-responsive liquid chromatography (TRLC) in the 1D, which is a purely aqueous separation mode. Full solute refocusing at the 2D column head is thereby obtained when TRLC is combined with reversed-phase liquid chromatography (RPLC). This is shown for the combination of a 2.1 mm I.D. TRLC column with decreasing RPLC column diameters (3-2.1-1 mm) operated at the same linear velocities, hence a resulting decrease in dilution, respectively. Ultraviolet (UV) and electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS) detection were used to determine the experimental detection limits. Sensitivity improvements with UV detection were somewhat lower than expected, but represent ∼1.5- and 3-fold sensitivity enhancement when using a 1 mm I.D. column compared to 2.1 or 3 mm I.D. columns in the 2D, respectively. This is attributed to extra-column dispersion and the poorer performance of 1 mm I.D. columns. A major benefit of the use of 1 mm I.D. columns in the 2D is that it allows split-free coupling of 2D effluent with ESI-MS (at 450 µL/min), making the coupling robust and simple. When using ESI-MS even better, albeit more variable, sensitivity enhancements were obtained on the narrower columns. The benefits of the methodology are demonstrated for paraben test solutes and for phenolic compounds in a blueberry extract by TRLC × RPLC-UV-ESI-TOF-MS.

The merit of pressure dependent kinetic modelling in steam cracking.

Renewable cracking feedstocks from plastic waste and the need for novel reactor designs related to electrification of steam crackers drives the development of accurate and fundamental kinetic models for this process, despite its large scale implementation for more than half a century. Pressure dependent kinetics have mostly been omitted in fundamental steam cracking models, while they are crucial in combustion models. Therefore, we have assessed the importance of pressure dependent kinetics for steam cracking via in-depth modelling and experimental studies. In particular we have studied the influence of considering fall-off on the product yields for ethane and propane steam cracking. A high-pressure limit fundamental kinetic model is generated, based on quantum chemical data and group additive values, and supplemented with literature values for pressure dependent kinetic parameters for ß-scission reactions and homolytic bond scissions of C2 and C3 species. Model simulations with high-pressure limit rate coefficients and pressure dependent kinetics are compared to new experimental measurements. Steam cracking experiments for pure ethane and propane feeds are performed on a tubular bench-scale reactor at 0.17 MPa and temperatures ranging from 1058 to 1178 K. All important product species are identified using a comprehensive GC × GC-FID/q-MS. For homolytic bond scissions, the inclusion of pressure dependent kinetics has a significant effect on the conversion profile for ethane steam cracking. On the other hand, pressure dependence of C2 ß-scissions significantly influences conversion and product species profiles for both ethane and propane steam cracking. The C3 ß-scissions pressure dependence has a negligible effect in ethane steam cracking, while for propane steam cracking the effect is non-negligible on the product species profiles.

Learning Molecular Representations for Thermochemistry Prediction of Cyclic Hydrocarbons and Oxygenates.

Accurate thermochemistry estimation of polycyclic molecules is crucial for kinetic modeling of chemical processes that use renewable and alternative feedstocks. In kinetic model generators, molecular properties are estimated rapidly with group additivity, but this method is known to have limitations for polycyclic structures. This issue has been resolved in our work by combining a geometry-based molecular representation with a deep neural network trained on ab initio data. Each molecule is transformed into a probabilistic vector from its interatomic distances, bond angles, and dihedral angles. The model is tested on a small experimental dataset (200 molecules) from the literature, a new medium-sized set (4000 molecules) with both open-shell and closed-shell species, calculated at the CBS-QB3 level with empirical corrections, and a large G4MP2-level QM9-based dataset (40 000 molecules). Heat capacities between 298.15 and 2500 K are calculated in the medium set with an average deviation of about 1.5 J mol-1 K-1 and the standard entropy at 298.15 K is predicted with an average error below 4 J mol-1 K-1. The standard enthalpy of formation at 298.15 K has an average out-of-sample error below 4 kJ mol-1 on a QM9 training set size of around 15 000 molecules. By fitting NASA polynomials, the enthalpy of formation at higher temperatures can be calculated with the same accuracy as the standard enthalpy of formation. Uncertainty quantification by means of the ensemble standard deviation is included to indicate when molecules that are on the edge or outside of the application range of the model are evaluated.

Endocrine disrupting potency and toxicity of novel sophorolipid quaternary ammonium salts.

A new class of biosurfactants, namely quaternary ammonium sophorolipids (SQAS), suitable for pharmaceutical applications, was tested for the evaluation of their (anti)estrogenic and (anti)androgenic potency with the help of YES/YAS assays. Also their toxicity towards yeasts (Saccharomyces cerevisiae) and bacteria (Escherichia coli) was checked. The results achieved for SQAS, which can be regarded as potential micropollutants, were compared with those obtained for two well-known micropollutants diclofenac and 17α-ethinylestradiol subjected to the same testing procedures. This work demonstrated that acetylation of the hydroxyl group of the carbohydrate head of SQAS decreased the toxicity of this class of biosurfactants towards Saccharomyces cerevisiae. Furthermore, it contributed to the decrease of their endocrine disrupting potency. None of the SQAS studied showed clear agonist activity for female or male hormones. SQAS1 and SQAS2 revealed weak antiestrogenic and antiandrogenic potency. All of these properties were weaker, not only to the potency of the appropriate positive control in the antagonists bioassays, but also compared to the potency of other tested compounds, i.e. DCF and EE2. SQAS3 possessed most probably inhibitory activity towards male hormones. Moreover, cytotoxicity of two out of four studied SQAS at the highest concentrations towards the strains of Saccharomyces cerevisiae interfered with the endocrine disruption activity. It would be also worth studying it with the use of another endocrine activity test.

Detailed Analysis of the Composition of Selected Plastic Packaging Waste Products and Its Implications for Mechanical and Thermochemical Recycling.

Plastic packaging typically consists of a mixture of polymers and contains a whole range of components, such as paper, organic residue, halogens, and metals, which pose problems during recycling. Nevertheless, until today, limited detailed data are available on the full polymer composition of plastic packaging waste taking into account the separable packaging parts present in a certain waste stream, nor on their quantitative levels of (elemental) impurities. This paper therefore presents an unprecedented in-depth analysis of the polymer and elemental composition, including C, H, N, S, O, metals, and halogens, of commonly generated plastic packaging waste streams in European sorting facilities. Various analytical techniques are applied, including Fourier transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), polarized optical microscopy, ion chromatography, and inductively coupled plasma optical emission spectrometry (ICP-OES), on more than 100 different plastic packaging products, which are all separated into their different packaging subcomponents (e.g., a bottle into the bottle itself, the cap, and the label). Our results show that certain waste streams consist of mixtures of up to nine different polymers and contain various elements of the periodic table, in particular metals such as Ca, Al, Na, Zn, and Fe and halogens like Cl and F, occurring in concentrations between 1 and 3000 ppm. As discussed in the paper, both polymer and elemental impurities impede in many cases closed-loop recycling and require advanced pretreatment steps, increasing the overall recycling cost.

Ab initio derived group additivity model for intramolecular hydrogen abstraction reactions.

A set of group additivity values for intramolecular hydrogen abstraction reactions of alkanes, alkenes and alkynes is reported. Calculating 448 reaction rate coefficients at the CBS-QB3 level of theory for 1-2 up to 1-7 hydrogen shift reactions allowed the estimation of ΔGAV° values for 270 groups. The influence of substituents on (1) the attacking radical, (2) the attacked carbon atom, and (3) the carbon chain between the attacking and attacked reactive atom has been systematically studied. Substituents have been varied between hydrogen atoms and sp3, sp2 and sp hybridized carbon atoms. It has been assumed that substituents further away from the reactive atoms or their connecting carbon chain have negligible influences on the kinetics. This group additivity model is applicable to a wide variety of reactions in the 300-1800 K temperature range. Correlations for tunneling coefficients have been generated which are complementary to the ΔGAV°'s to obtain accurate rate coefficients without the need for imaginary frequencies or electronic energies of activation. These correlations depend on the temperature and activation energy of the exothermic step. The group additivity model has been successfully applied to a test set of reactions also calculated at the CBS-QB3 level of theory. A mean absolute deviation of 1.18 to 1.71 has been achieved showing a good overall accuracy of the model.

Symmetry calculation for molecules and transition states.

The symmetry of molecules and transition states of elementary reactions is an essential property with important implications for computational chemistry. The automated identification of symmetry by computers is a very useful tool for many applications, but often relies on the availability of three-dimensional coordinates of the atoms in the molecule and hence becomes less useful when these coordinates are a priori unavailable. This article presents a new algorithm that identifies symmetry of molecules and transition states based on an augmented graph representation of the corresponding structures, in which both topology and the presence of stereocenters are accounted for. The automorphism group order of the graph associated with the molecule or transition state is used as a starting point. A novel concept of label-stereoisomers, that is, stereoisomers that arise after labeling homomorph substituents in the original molecule so that they become distinguishable, is introduced and used to obtain the symmetry number. The algorithm is characterized by its generic nature and avoids the use of heuristic rules that would limit the applicability. The calculated symmetry numbers are in agreement with expected values for a large and diverse set of structures, ranging from asymmetric, small molecules such as fluorochlorobromomethane to highly symmetric structures found in drug discovery assays. The new algorithm opens up new possibilities for the fast screening of the degree of symmetry of large sets of molecules.

Enhancing sustainable waste management: Hydrothermal carbonization of polyethylene terephthalate and polystyrene plastics for energy recovery.

Hydrothermal carbonization (HTC) of single plastic polymers such as polyethylene terephthalate (PET) and polystyrene (PS) has not yet been explored on a large scale, particularly their thermal behavior, chemical transformations under subcritical conditions, and the energy properties of the resultant hydrochar. This study investigated these aspects by employing techniques, such as thermogravimetric analysis (TGA), Fourier transformed infrared spectroscopy (FTIR), elemental and calorific analysis. The results show that PET hydrochar has a superior energy densification (1.37) and energy yield (89 %) compared to PS hydrochar (1.13, 54 %). Hydrothermal carbonization modifies the chemical structure of the polymers by increasing the number of carbonyl groups (CO) in PET and forming new ones in PS, and by enhancing hydroxyl groups (OH) in PET while retaining them in PS. Both materials preserve their aromatic and aliphatic structures, with the introduction of alkenes groups (CC) in the PET hydrochar. PET hydrochar begins to decompose at lower temperatures (150-270 °C) than PS hydrochar (242-283 °C) but reaches higher peak temperatures (420-585 °C vs. 390-470 °C), with both types achieving similar burnout temperatures (650-800 °C). PET hydrochar recorded a higher activation energy (121-126 kJ/mol) than PS hydrochar (67-74 kJ/mol) with the Mampel first-order reaction model as the best fit.

Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices.

The challenge of devising pathways for organic synthesis remains a central issue in the field of medicinal chemistry. Over the span of six decades, computer-aided synthesis planning has given rise to a plethora of potent tools for formulating synthetic routes. Nevertheless, a significant expert task still looms: determining the appropriate solvent, catalyst, and reagents when provided with a set of reactants to achieve and optimize the desired product for a specific step in the synthesis process. Typically, chemists identify key functional groups and rings that exert crucial influences at the reaction center, classify reactions into categories, and may assign them names. This research introduces Rxn-INSIGHT, an open-source algorithm based on the bond-electron matrix approach, with the purpose of automating this endeavor. Rxn-INSIGHT not only streamlines the process but also facilitates extensive querying of reaction databases, effectively replicating the thought processes of an organic chemist. The core functions of the algorithm encompass the classification and naming of reactions, extraction of functional groups, rings, and scaffolds from the involved chemical entities. The provision of reaction condition recommendations based on the similarity and prevalence of reactions eventually arises as a side application. The performance of our rule-based model has been rigorously assessed against a carefully curated benchmark dataset, exhibiting an accuracy rate exceeding 90% in reaction classification and surpassing 95% in reaction naming. Notably, it has been discerned that a pivotal factor in selecting analogous reactions lies in the analysis of ring structures participating in the reactions. An examination of ring structures within the USPTO chemical reaction database reveals that with just 35 unique rings, a remarkable 75% of all rings found in nearly 1 million products can be encompassed. Furthermore, Rxn-INSIGHT is proficient in suggesting appropriate choices for solvents, catalysts, and reagents in entirely novel reactions, all within the span of a second, utilizing nothing more than an everyday laptop.

Application of chemometric tools in the QSAR development of VOC removal in plastic waste recycling.

Deodorization and, in a broader sense, the removal of volatile organic compounds (VOCs) from plastic waste have become increasingly important in the field of plastic recycling, and various new decontamination techniques have been developed. Both in research and industrial practice, the selection of VOCs has been random or unsubstantiated, making it difficult to compare studies and assess decontamination processes objectively. Thus, this study proposes the use of Statistical Molecular Design (SMD) and Quantitative Structure - Activity Relationship (QSAR) as chemometric tools for the selection of representative VOCs, based on physicochemical properties. Various algorithms are used for SMD; hence, several frequently used D-Optimal Onion Design (DOOD) and Space-Filling (SF) algorithms were assessed. Hereby, it was validated that DOOD, by dividing the layers based on the equal-distance approach without so-called 'Adjacent Layer Bias', results in the most representative selection of VOCs. QSAR models that describe VOC removal by water-based washing of plastic waste as a function of molecular weight, polarizability, dipole moment and Hansen Solubility Parameters Distance were successfully established. An adjusted-R2 value of 0.77 ± 0.09 and a mean absolute error of 24.5 ± 4 % was obtained. Consequently, by measuring a representative selection of VOCs compiled using SMD, the removal of other unanalyzed VOCs was predicted on the basis of the QSAR. Another advantage of the proposed chemometric selection procedure is its flexibility. SMD allows to extend or modify the considered dataset according to the available analytical techniques, and to adjust the considered physicochemical properties according to the intended process.

Plastic waste recycling is gaining momentum.

Production of detergents and aldehydes could help tackle plastic pollution.

Efficient mapping of lignin depolymerization product pools and quantification of specific monomers through rapid GPC-HPLC-UV/VIS analysis.

BACKGROUND: Growing research on lignin depolymerization to functionalized bio-aromatics has necessitated dedicated analysis techniques. However, immense variability in molecular weight and functional groups of the depolymerization products impedes fast analysis of a large number of samples while remaining in-depth enough for catalyst screening or reaction condition optimization. While GPC-HPLC-UV/VIS has been a promising technique, up until now, the information it provides is largely qualitative. By enabling quantification of key monomeric products and through further reduction of overall analysis time, this study aims to increase the potential of GPC-HPLC-UV/VIS for fast and in-depth characterization of lignin depolymerization product pools. RESULTS: Analysis of selected samples, isolated from GPC-HPLC-UV/VIS analyses of lignin depolymerization product pools, with gas chromatography (GC) equipped with an Orbitrap high-resolution accurate mass spectrometer (Orbitrap-HR/AM-MS) is successful in identifying the main low monomeric products. Moreover, these identifications are further substantiated through GPC-HPLC-UV/VIS analysis of standards. Furthermore, straight forward quantification of these products directly within GPC-HPLC-UV/VIS is successfully developed with limits of detection ≤0.05 mmol/L, which is at least on par with more complex analysis techniques. Additionally, several different reversed phase columns are assessed to reduce 2nd dimension (2D) time and, hence, overall analysis time while maintaining the possibility for quantification. A reduction in overall analysis time of about 30% as compared to the state-of-the-art is achieved by using a YMC Triart BIO C4 column as 2D. SIGNIFICANCE: Through the enhancements introduced in this study, GPC-HPLC-UV/VIS emerges as a unique technique for the analysis of lignin depolymerization product pools, which is capable of fast yet sufficiently in-depth analysis of a large volume of samples. This capability is indispensable for catalyst screening and fine-tuning reaction conditions.

Understanding the complexity of deinking plastic waste: An assessment of the efficiency of different treatments to remove ink resins from printed plastic film.

Plastic packaging is usually heavily printed with inks to provide functional benefits. However, the presence of inks strongly impedes the closed-loop recycling of plastic films. Various media have already been studied for the deinking of plastic films, but there is little scientific insight into the effectiveness of different deinking techniques. Therefore, this study aims to obtain a systematic understanding by measuring the liquefaction and maximum solubility of 14 chemically different polymer resins in seven different media typically used in plastic deinking, such as acetone, ethyl acetate, sodium hydroxide solution, cetyltrimethylammonium bromide solution, formic acid, sulfuric acid, and N,N-dimethylcyclohexylamine. Our findings show that acid-based media are able to remove a broader range of polymer resins. Organic solvents are particularly effective against acrylics and related polymer resins. The deinking efficiency tests on pure resins are also confirmed by deinking four printed plastic films containing different classes of polymer resins. A basic cost and environmental impact analysis is given to evaluate scale-up potential of the deinking medium.

Thermal pyrolysis of waste versus virgin polyolefin feedstocks: The role of pressure, temperature and waste composition.

Due to the complexity and diversity of polyolefinic plastic waste streams and the inherent non-selective nature of the pyrolysis chemistry, the chemical decomposition of plastic waste is still not fully understood. Accurate data of feedstock and products that also consider impurities is, in this context, quite scarce. Therefore this work focuses on the thermochemical recycling via pyrolysis of different virgin and contaminated waste-derived polyolefin feedstocks (i.e., low-density polyethylene (LDPE), polypropylene (PP) as main components), along with an investigation of the decomposition mechanisms based on the detailed composition of the pyrolysis oils. Crucial in this work is the detailed chemical analysis of the resulting pyrolysis oils by comprehensive two-dimensional gas chromatography (GC × GC) and ICP-OES, among others. Different feedstocks were pyrolyzed at a temperature range of 430-490 °C and at pressures between 0.1 and 2 bar in a continuous pilot-scale pyrolysis unit. At the lowest pressure, the pyrolysis oil yield of the studied polyolefins reached up to 95 wt%. The pyrolysis oil consists of primarily α-olefins (37-42 %) and n-paraffins (32-35 %) for LDPE pyrolysis, while isoolefins (mostly C9 and C15) and diolefins accounted for 84-91 % of the PP-based pyrolysis oils. The post-consumer waste feedstocks led to significantly less pyrolysis oil yields and more char formation compared to their virgin equivalents. It was found that plastic aging, polyvinyl chloride (PVC) (3 wt%), and metal contamination were the main causes of char formation during the pyrolysis of polyolefin waste (4.9 wt%).

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.

Quality evaluation and economic assessment of an improved mechanical recycling process for post-consumer flexible plastics.

Packaging represents the largest fraction of plastic waste in Europe. Currently, mechanical recycling schemes are mainly focused on the recovery of rigid packaging (like bottles), while for flexible packaging, also called films, recycling rates remain very low. Existing mechanical recycling technologies for these films are quite basic, especially in the case of complicated post-consumer flexible plastics (PCFP) waste, leading to regranulate qualities that are often subpar for renewed use in demanding film applications. In this study, the technical and economic value of an improved mechanical recycling process (additional sorting, hot washing, and improved extrusion) of PCFPs is investigated. The quality of the four types of resulting regranulates is evaluated for film and injection molding applications. The obtained Polyethylene-rich regranulates in blown films offer more flexibility (45-60%), higher ductility (27-55%), and enhanced tensile strength (5-51%), compared to the conventional mechanical recycling process. Likewise, for injection molded samples, they exhibit more flexibility (19-49%), enhanced ductility (7 to 20 times), and higher impact strength (1.8 to 3.8 times). An economic assessment is made between the obtained increased market value and the capital investment required. It is shown that the economic value can be increased by 5-38% through this improved recycling process. Overall, the study shows that it is possible to increase the mechanical recycling quality of PCFP in an economically viable way, thus opening the way for new application routes and overall increased recycling rates.

Maximizing olefin production via steam cracking of distilled pyrolysis oils from difficult-to-recycle municipal plastic waste and marine litter.

Plastic waste is steadily polluting oceans and environments. Even if collected, most waste is still predominantly incinerated for energy recovery at the cost of CO2. Chemical recycling can contribute to the transition towards a circular economy with pyrolysis combined with steam cracking being the favored recycling option for the time being. However, today, the high variety and contamination of real waste remains the biggest challenge. This is especially relevant for waste fractions which are difficult or even impossible to recycle mechanically such as highly mixed municipal plastic waste or marine litter. In this work, we studied the detailed composition and the steam cracking performance of distilled pyrolysis oil fractions in the naphtha-range of two highly relevant waste fractions: mixed municipal plastic waste (MPW) considered unsuitable for mechanical recycling and marine litter (ML) collected from the sea bottom. Advanced analytical techniques including comprehensive two-dimensional gas chromatography (GC × GC) coupled with various detectors and inductively coupled plasma - mass spectrometry (ICP-MS) were applied to characterize the feedstocks and to understand how their properties affect the steam cracking performance. Both waste-derived naphtha fractions were rich in olefins and aromatics (~70% in MPW naphtha and ~51% in ML naphtha) next to traces of nitrogen, oxygen, chlorine and metals. ICP-MS analyses showed that sodium, potassium, silicon and iron were the most crucial metals that should be removed in further upgrading steps. Steam cracking of the waste-derived naphtha fractions resulted in lower light olefin yields compared to fossil naphtha used as benchmark, due to secondary reactions of aromatics and olefins. Coke formation of ML naphtha was slightly increased compared to fossil naphtha (+ ~50%), while that of MPW naphtha was more than ~180% higher. It was concluded that mild upgrading of the waste-derived naphtha fractions or dilution with fossil feedstocks is sufficient to provide feedstocks suitable for industrial steam cracking.