The chemistry of chemical recycling of solid plastic waste via pyrolysis and gasification: State-of-the-art, challenges, and future directions
Chemical recycling of solid plastic waste (SPW) is a paramount opportunity to reduce marine
and land pollution and to enable the incorporation of the circular economy principle in …
and land pollution and to enable the incorporation of the circular economy principle in …
Precision polymer synthesis by controlled radical polymerization: Fusing the progress from polymer chemistry and reaction engineering
During the first 100 years of polymer science, controlled radical polymerization (also
recommended as reversible deactivation radical polymerization) is undoubtedly a …
recommended as reversible deactivation radical polymerization) is undoubtedly a …
Role of external field in polymerization: mechanism and kinetics
The past decades have witnessed an increasing interest in developing advanced
polymerization techniques subjected to external fields. Various physical modulations, such …
polymerization techniques subjected to external fields. Various physical modulations, such …
Reinforcement learning based optimal control of batch processes using Monte-Carlo deep deterministic policy gradient with phase segmentation
Batch process control represents a challenge given its dynamic operation over a large
operating envelope. Nonlinear model predictive control (NMPC) is the current standard for …
operating envelope. Nonlinear model predictive control (NMPC) is the current standard for …
Radical polymerization of acrylates, methacrylates, and styrene: Biobased approaches, mechanism, kinetics, secondary reactions, and modeling
Biobased polymer molecules are a goal for the future. Here, the different intermediate
pathways toward renewable structural constituents, which can substitute petrochemically …
pathways toward renewable structural constituents, which can substitute petrochemically …
Gillespie-driven kinetic Monte Carlo algorithms to model events for bulk or solution (bio) chemical systems containing elemental and distributed species
AD Trigilio, YW Marien… - Industrial & …, 2020 - ACS Publications
Stochastic modeling techniques have emerged as a powerful tool to study the time evolution
of processes in many research fields including (bio) chemical engineering and biology. One …
of processes in many research fields including (bio) chemical engineering and biology. One …
Computational modeling toward full chain of polypropylene production: From molecular to industrial scale
Since polypropylene was synthesized in 1954, tremendous breakthroughs have been
achieved in transferring polypropylene from a discovery in the laboratory to an …
achieved in transferring polypropylene from a discovery in the laboratory to an …
[HTML][HTML] Multi-scale modeling of plastic waste gasification: opportunities and challenges
S Madanikashani, LA Vandewalle, S De Meester… - Materials, 2022 - mdpi.com
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 …
gasification is one of the most promising, converting plastic waste into syngas (H2+ CO) and …
Model-based design of the polymer microstructure: bridging the gap between polymer chemistry and engineering
DR D'hooge, PHM Van Steenberge, P Derboven… - Polymer …, 2015 - pubs.rsc.org
The performance of polymeric materials depends strongly on the control over the polymer
microstructure during the synthesis step. In this review, attention is paid to the potential of …
microstructure during the synthesis step. In this review, attention is paid to the potential of …
Quantitative structure–property relationship model for predicting the propagation rate coefficient in free-radical polymerization
Y Shi, M Yu, J Liu, F Yan, ZH Luo, YN Zhou - Macromolecules, 2022 - ACS Publications
In this work, a generalized quantitative structure–property relationship (QSPR) model is
developed for predicting kp by using norm index (NI)-based descriptors, which is the so …
developed for predicting kp by using norm index (NI)-based descriptors, which is the so …