Macromolecular Reaction Engineering最新文献

Development of accurate and robust dynamic models for the description of emulsion copolymerization processes is fundamental for the implementation of monitoring, advanced control, and optimization strategies. There are several studies on the dynamic modeling of styrene/1,3-butadiene rubber (SBR) emulsion copolymerization, but most of them focus on hot conditions or only one semi-batch reactor, as in the case of cold conditions. For this reason, the present study focuses on the dynamic modeling of SBR cold emulsion copolymerization processes considering a train of 15 continuous stirred tank reactors, as in many real industrial sites. The developed dynamic model is implemented by using the digital twin (DT) concept, which involves the online reading of process variables and an adaptive strategy for online tuning of some of the model parameters, being also sensitive to the effect of real-time changes on the number of reactors in the train, a subject that has been overlooked previously, but which is important at the plant site. The practical application of the DT for monitoring a real industrial process illustrates the robustness and accuracy of the developed tool, making it useful for opportune detection of process anomalies and opening the way for future advanced control strategies.

Anionic polyelectrolytes can be used for a variety of applications, including flocculation and enhanced oil recovery. While it is widely recognized that polyelectrolyte synthesis is impacted by the pre-polymer formulation and polymerization conditions, the specific relationships between these factors and the subsequent polymer properties are not well understood. Therefore, the current work intends to improve understanding of ionic strength (IS) effects during the copolymerization of 2-acrylamido-2-methylpropane sulfonic acid (AMPS) and acrylamide (AAm). The aims of the study are i) to use in situ H¹ NMR to study copolymerization kinetics, and ii) to determine how increasing IS impacts copolymerization kinetics (and, by extension copolymer microstructure). It is found that altering IS prior to copolymerization has significant impacts on the reactivity ratios, and therefore impacts the microstructure through multiple mechanisms. Increasing IS causes a crowding effect, where the propagating chain develops a random coil conformation and causes steric hindrance of the large AMPS monomer, decreasing the likelihood of AMPS propagation. When the IS is increased further, the ionic shielding effect is more impactful, increasing the likelihood of AMPS propagation. Ultimately, this work will make it possible to manipulate IS to synthesize AMPS/AAm copolymers with specific desirable properties for target applications.

The deposition process during emulsion polymerization can be classified as both particulate and reaction fouling, but a deeper understanding of the deposition mechanism, especially in combination with the polymerization process, is lacking. Here, a more in-depth understanding of the deposition mechanism is sought by investigating the fouling formation of a Vinyl acetate and Versa 10 copolymer on a heated stainless steel surface during emulsion polymerization. Its deposition behavior is also compared with the behavior of an already reacted polymer. All possible influencing factors are investigated separately, and the fouling is quantified by the mass based fouling resistance and the fouling layer composition. The fouling rates of both experimental approaches (ongoing reaction versus already reacted polymer) are used to determine the fraction of reaction fouling along the reaction pathway. The solids content and the driving temperature difference are identified as the main factors influencing fouling formation. The deposited material is composed of latex particles and emulsifier with particle size and number depending on the respective equilibrium composition of the fluid phase. The reaction fouling rate is correlated with the proportion of free initiator radicals and the amount of dissolved monomer in the aqueous phase.

Heat seal and mechanical properties of 1-octene grafted low density polyethylene films containing various concentrations of Dicumyl peroxide as the initiator and 1-octene grafting agent is investigated through using experimental measurements. The results of differential scanning calorimeter (DSC) measurements revealed that the melting temperature shifts to higher values and the peak of the DSC curve becomes wider with the increase of 1-octene concentrations. Thermogravimetric analysis (TGA) revealed a higher thermal stability up to 20 °C for 1-octene grafted PE compared with neat LDPE alloy. The results of stress–strain measurements revealed that the 1-octene grafted PE alloys has higher tensile strength in comparison with neat PE alloy and samples containing only DCP initiator. The results of heat seal analysis indicated that both DCP initiator and 1-octene tended to offer a moderate increase peel strength of PE alloy. DMTA measurements for various grafted PE alloys show a higher damping factor in comparison with neat LDPE alloy. Rheological measurements indicated a higher storage modulus up to 25% and higher complex viscosity for grafted PE samples containing 1-octene comonomer.

Online near-infrared spectroscopy technique is employed to investigate the kinetics of the anionic polymerization of butadiene with n-butyllithium initiator in the presence of the microstructure modifier 1,2-diethoxypropane (DEP) in cyclohexane solvent. A phenomenological kinetic model is developed to describe the anionic polymerization process in the presence of DEP, and its influence on the microstructure of polybutadiene under different conditions is determined.

The information available in daily plant operation data is not fully exploited by polymer reaction engineers: what do the catalytic olefin polymerization plants tell? In this article, a method is proposed to increase catalyst and process know-how, based on experimentally acquired production rate results, coming from a continuous tandem reactor polymerization process. The polymer reaction engineering methodology is also discussed in detail for connecting the catalyst reaction performance to the expected activity profile and yield for batch operation, together with the residence time distribution effect for continuous operation. The potential of the proposed methodology is highlighted with a theoretical example and the effectiveness of the method is demonstrated with an applied example, accurately estimating deactivation parameter values for two catalysts based on plant information and, validated based on small-scale polymerization experiments.

This study addresses the challenges of time-delay and low accuracy in online gas-phase composition monitoring during olefin copolymerization processes. Three flowmeters based on different mechanisms are installed in series to measure the real-time exhaust gas flow rate from the reactor. For the same gas flow, the three flowmeters display different readings, which vary with the properties and composition of the gas mixture. Consequently, the composition of the mixed gas can be determined by analyzing the reading of the three flowmeters. Fitting equations and three machine learning models, namely decision trees, random forests, and extreme gradient boosting, are employed to calculate the gas composition. The results from cold-model experimental data demonstrate that the XGBoost model outperforms others in terms of accuracy and generalization capabilities. For the concentration of ethylene, propylene, and hydrogen, the determination coefficients (R²) were 0.9852, 0.9882, and 0.9518, respectively, with corresponding normalized root mean square error (NRMSE) values of 0.0352, 0.0312, and 0.0706. The effectiveness of the online monitoring device is further validated through gas phase copolymerization experiments involving ethylene and propylene. The yield and composition of the ethylene and propylene copolymers are successfully predicted using the online measurement data.