Is full recyclability of polyolefins via chemical recycling a dream, or can it become reality? The main problem in plastic waste is that its composition highly heterogeneous while sorting and purifying solutions to obtain mono-streams are complex require large investments, thereby hampering the economy scale. Ideally, novel processes designed have mixed wastes as input higher value products produced such C2–C4 olefins aromatics instead low oil. In this review we show directions how realize...

Polyethylene (PE) and polypropylene (PP) are among the most recycled polymers. However, these polymers present similar physicochemical characteristics cross-contamination between them is commonly observed, affecting quality of recyclates. With increasing demand for plastics, understanding composition materials crucial. Numerous techniques have been introduced in literature to determine plastics. An ideal technique should be accessible, cost-efficient, fast, accurate. Differential Scanning...

Machine learning has proven effective for predicting properties of pure compounds from molecular structures, but mixtures, in particular oil fractions, are rarely dealt with. At best, the bulk estimated based on compound properties, linear mixing rules, and a reconstructed composition feedstock. As detailed such mixtures is well determined often approximated by lumps, accuracy can be improved. In this work, we demonstrate naphtha case study our property estimation method. First, PIONA...

Increasing recycling rates of plastic waste is necessary to achieve a sustainable and climate-neutral chemical industry. For polyolefin waste, corresponding 60% via thermal pyrolysis the most promising process. However, hydrocarbon composition these oils differs from conventional fossil-based feedstocks as they are heavier more unsaturated. GC × GC-FID prevalent characterization method for analysis complex mixtures but fails discern heavy unsaturated, aromatic compounds. An up-and-coming...

Formation of coke poses a considerable challenge in steam cracking reactors utilized for olefin production, exerting detrimental effects on the reactor performance and productivity. To tackle this challenge, more profound understanding fouling phenomena their intricate connections with feedstock composition process conditions is imperative. While conventional wisdom suggests that all aromatics contribute to increased formation, our research challenges assumption. evaluate assumption, an...

Genesys-Cat facilitates automated microkinetic model development for catalytic reactions based on a rule-based reaction network generator and enhanced Bayesian optimization.

By combining machine learning with the design of experiments, thereby achieving so-called active learning, more efficient and cheaper research can be conducted. Machine algorithms are flexible better than traditional experiment at investigating processes spanning all length scales chemical engineering. While maturing, their applications falling behind. In this article, three types challenges presented by learning—namely, convincing experimental researcher, flexibility data creation,...

The linear plastic lifecycle is unsustainable. Mechanical recycling of mixed waste remains challenging, making chemical necessary. Polyolefins, the largest share waste, can be chemically recycled through thermal pyrolysis. However, impact feedstock type on pyrolysis oil composition unclear. Only very advanced analytical techniques allow to assess detailed these oils, which crucial evaluate their economic potential. Therefore, in this work, hydrocarbon and oxygenate contents three oils...

Carbenium ions are important intermediates in both zeolite and plasma chemistry. The construction of kinetic models for chemistry requires the incorporation thermodynamic properties these carbenium ions. In this way, equilibrium is incorporated resulting more accurate general models, which facilitate rational design process development. work, a consistent set 46 group additive values (GAVs) non-nearest neighbor interactions (NNIs) determined standard enthalpy formation, molar entropy, heat...

Increasing recycling rates of plastic waste is necessary to achieve a sustainable and climate-neutral chemical industry. For polyolefin waste, corresponding 60% via thermal pyrolysis the most promising process. However, hydrocarbon composition these oils differs from conventional fossil-based feedstocks as they are heavier more unsaturated. To unravel this complexity, comprehensive two-dimensional gas chromatography (GC × GC) powerful method. Nevertheless, even when using reversed-phase GC...

Designing an active, selective, and stable catalyst for catalytic polyolefin pyrolysis is crucial enhancing energy efficiency economic viability in chemical processes. In this study, two synthesis methods—NaOH NaOH/CTAB treatments—were employed to modify the physicochemical properties of CBV23, CBV55, CBV80 zeolites. The performance both parent modified zeolites was evaluated polypropylene using a two-stage micro-pyrolyzer coupled with two-dimensional GC-FID/MS. treatment preserved enhanced...

Developing improved zeolites is essential in novel sustainable processes such as the catalytic pyrolysis of plastic waste. This study used density functional theory to investigate how alkyl chain length, unsaturated bonds, and branching affect β-scission kinetics four zeolite frameworks, a key reaction hydrocarbon cracking. The activation enthalpy was evaluated for wide variety 23 hydrocarbons, with 6 12 carbon atoms, FAU, MFI, MOR, TON. consideration both branched linear olefin diolefin...

By combining machine learning with design of experiments, so-called active learning, more efficient and cheaper research can be conducted. Machine algorithms are flexible, better at investigating the processes spanning all length scales chemical engineering. While maturing, its applications lacking behind. Three types challenges faced by identified ways to overcome them discussed: convincing experimental researcher, flexibility data creation, robustness algorithms. A bright future lies ahead...