Macromolecular Reaction Engineering最新文献

Polybutylene succinate (PBS) and other succinic (co)polyesters are biodegradable polymers with favorable mechanical and thermal properties that find use in many applications. Due to environmental concerns, polymers based on succinic acid (SA) have been gaining attention, as SA can be produced through biotechnological processes. Thus, this review aims to highlight the synthesis and characteristics of PBS and other succinic copolyesters, with emphasis in the works employing metallic catalysts and enzymes. In addition, the modification of the macromolecular structure by copolymerization or postpolymerization is also discussed. Currently, metallic catalysts are normally used in the synthesis of these materials, under conditions of high temperatures, which can favor the occurrence of thermal degradation, increasing the dispersion of chain length distributions. Moreover, the incrustation of metallic catalysts in polymeric materials makes their application in biomedical products difficult, due to toxicity requirements. In this context, enzymatic catalysis is gaining ground, offering milder synthesis temperatures, high selectivity, and uniformity of synthesized products. This biotechnological route can substitute oligomerization processes with metallic catalysis in future industrial processes, producing materials free from metallic contamination. In addition to production by catalytic routes, trends for future applications of succinic (co)polyesters are presented, with emphasis on the value-added materials sectors.

This work presents the development and validation of two virtual analyzers (density and Melt Index (MI)) for quality monitoring and control of the final product in an industrial unit of Linear Polyethylene (LPE). Both models are based on Feedforward Neural Networks which are improved through a strategy involving the initial estimation of weights and a constructive algorithm to define the number of hidden units. The initialization strategy is based on linearization of the neural model with only one hidden unit (nonlinear model) and subsequent optimization of this model by maximizing its similarity to the standard linear regression model whose solution is obtained analytically. The Initial Neural Model (INM) is then used as a starting point for a gradual increase in the number of hidden units. In a validation test involving MI and density values collected over 2 years of operation, the neural model is able to predict these properties with mean percentage errors equal to 0.81% (MI) and 0.04% (density) and determination coefficients equal to 0.970 (MI) and 0.983 (density). The population coefficient estimated in all tests involving grade transitions (0.96) shows a strong linear correlation between the proposed model and laboratory measurements.

Front Cover: Kinetic study of multi-step bulk-/gas-phase polymerization for synthesis of heterophasic polypropylene copolymers. Power compensation calorimetry is used for studying kinetics of bulkphase polymerization, while for gas-phase polymerization, kinetic data is obtained from semi-batch operation at constant conditions. The combination of both methods allows to precisely control the heterophasic copolymers formed. This is reported by Sina Valaei and Michael Bartke in article number 2200018.

I am pleased to celebrate the 60^th birthday of our colleague and friend, Tim McKenna, in this special issue of Macromolecular Reaction Engineering (MRE). I am also thrilled that I am not the only one to reach this milestone, even though I preceded him by a couple of years. Welcome to the club, old man.

The number and scope of articles submitted to this special MRE issue reflect Tim's many accomplishments in polymer reaction engineering. Tim is the Director of Research of CP2M/CNRS and a Professor at CPE-Lyon in Villeurbanne, France. Tim's research program applies chemical engineering tools to understand, quantify, and control polymerization reactors, focusing on polyolefins and specialized latex products. He has published 269 peer-reviewed articles, 12 book chapters, 1 authored book, and is listed as an inventor in 6 patents. Tim has also given many keynote lectures and invited presentations in international conferences, and supervised a multitude of graduate students who are currently contributing to different areas of polymer science and engineering. He has also organized several international conferences, most notably Incorep (International Conference on the Reaction Engineering of Polyolefins), previously known as Ecorep (European Conference on the Reaction Engineering of Polyolefins), which will become the Blue Sky-Incorep conference in 2023, combining by the first time aspects of polyolefin chemistry, catalysis, and reaction engineering. Tim is also highly sought after as a consultant and as an expert witness for the polymer industry.

I was lucky to meet Tim when we were still at the beginning of our academic careers. If memory doesn't fail me—as it's prone to do after one's 60^th birthday—we first met in 1997, in Palm Coast, Florida, while attending Polymer Reaction Engineering III. Tim was interested on improving single particle models for olefin polymerization, focusing on intraparticle transport phenomena, particle morphology development, and thermodynamic equilibrium, while I was integrating polymerization kinetics and microstructural characterization methods to better understand olefin polymerization with coordination catalysts. Luckily for us, our research interests superimposed just enough to foster collaboration but not to trigger the shadow of competition that haunts young academics. This first meeting led to a lifelong collaboration—including our book, Polyolefin Reaction Engineering, and a series of open and in-house industrial short courses—allowing us to visit most major polyolefin manufacturing companies and travel the world together.

But I suspect that work alone would not be enough to maintain our friendship over the years. Research interests aside, Tim and I are both liberal humanists who share a love for single malts, good wines, long dinners capped with perhaps a few too many poires, and an irreverent se

Controlled polymerization techniques like the reversible-addition fragmentation chain transfer polymerization (RAFT) are sensitive to impurities such as oxygen. This work explores the application of re-initiation as a tool to enhance monomer conversion. A kinetic model for the oxygen inhibited RAFT dispersion polymerization for the synthesis of poly(4-vinylpyridine)-b-polystyrene (P4VP-b-PS) is developed. Thus, using the kinetic model, the re-initiation of the inhibited RAFT polymerization is partially (monomer conversion ≤10%) predicted. By implementing the re-initiation as a solution, the synthesis of P4VP-b-PS copolymers with the high conversion (>96%) and a good dispersity (≤1.2) is enabled.

Hybrid non-isocyanate poly(urethanes) (HNIPUs) are designed from a precursor whose carbonate functionality is derived from epoxy-functional statistical copolymers. Specifically, a bio-based diene (β-myrcene) is copolymerized via conventional free radical polymerization with glycidyl methacrylate (GMA) at different molar ratios, producing flexible copolymers with epoxy pendant groups, which are then reacted with carbon dioxide to yield the precursors with cyclic carbonate functionality. Subsequent addition of an amine-terminated telechelic poly(propylene glycol) (PPG) forms urethane linkages in the side chains, whose concentration is tuned by varying the GMA initial molar fraction. The NIPUs are end-capped with silanes to enable moisture curing, resulting in HNIPUs with elongations at break up to 150%, and relatively low elastic moduli varying from 32 kPa to 50 kPa as the number of urethane side linkages increases from 6 to 22. The swelling ratio of the NIPUs is also measured in tetrahydrofuran (THF). As the number of urethane side chains increases, the swelling ratio of the NIPUs decreases (710% to 620%), indicating a higher crosslinking density. All samples have gel contents higher than 50% in THF, indicating non-crosslinked species in the hybrid samples which confirms the relatively low reported tensile moduli.

A thermodynamic simulation package is developed for the catalytic polymerization of olefins in autoclave slurry, loop slurry, gas-phase, and autoclave solution reactors. The number of components in the reactors may vary from two to six. The simulator uses the Sanchez–Lacombe theory, one of the major thermodynamic models in the polymer industry. Step-by-step instructions on how to specify the system, derive and solve the resulting nonlinear equations, and estimate the required thermodynamic properties are given. The software is used to describe ethylene/1-hexene copolymerizations with hydrogen in different reactors under industrial conditions. These simulations demonstrate why thermodynamic effects must be included in olefin polymerization models.

A polymer distribution is usually represented by its moments. Thus, to calculate transport in a polymer system, a formulation for the transport of moments of the polymer is needed. This is only possible if the moments close or if there is a suitable closing condition. To archive this, two simplifications of the Stefan–Maxwell diffusion are derived, which convert the transport equation of polymeric species to a closed set of transport equations for the polymer moments. The first approach corresponds to an infinitely diluted polymer system, whereas the second one describes a highly concentrated polymer system. Both formulations are compared with the full Stefan-Maxwell model of a ternary mixture of a solvent and two polymer species of different chain length.

A systematic study of the impact of gas phase composition on the estimation of the reactivity ratios of a Ziegler–Natta catalyst during the gas phase copolymerization of ethylene with 1-butene and 1-hexene has been carried out. The results of the study show that if one uses a realistic equation of state to estimate the co- and anti-solubility effects of multiple species in the gas phase, one can obtain a unique value of the reactivity ratio pair from any number of experiments. However, it is found that using only binary solubility data and ignoring the impact of chemically inert species on solubility will lead to the estimate of composition-dependent reactivity ratio pairs.