Copolymerization of Ethylene with 1,9‐Decadiene: Part II—Prediction of Molecular Weight Distributions

Brandão, Amanda L. T.; Alberton, André L.; Pinto, José Carlos; Soares, João B. P.

doi:10.1002/mats.201700040

Cited by 11 publications

(17 citation statements)

References 38 publications

(49 reference statements)

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“…Following the Gillespie algorithm for dynamic Monte Carlo simulations,63 the MWDs were simulated for the three proposed models. For the interested reader, detailed information about the proposed MC method is described in previous publications 9,64. The LCB frequencies and MWD simulated for each model were compared and analyzed, in order to check whether these values could be discriminated during the sequential procedure.…”

Section: Methodsmentioning

confidence: 99%

“…All kinetic reaction rate constants for homopolymerization in the mechanisms shown in Table 2 were estimated in an earlier work of the group9 and their estimated values at 120 °C are shown in Table 3 .…”

Section: Models Developmentmentioning

confidence: 99%

“…Kinetic mechanisms that lead to formation of long‐chain branches usually involve incorporation of chains with terminal double bonds, for example terminal vinyl groups,3–8 or with pendant unsaturations,1,9 known as macromonomers or macromers. This process can be regarded as analogous to some copolymerizations performed with very long α‐olefins 4.…”

Section: Introductionmentioning

confidence: 99%

“…In order to investigate the proposed model discrimination problem, two case studies were investigated: The first case study concerns the discrimination among three rival kinetic models used to describe diene polymerizations performed with the constrained geometry catalyst (CGC)‐catalyst. One model leads to LCB formation via reincorporation of macromers through one of its pendant unsaturations;1,9 a second model generates LCB through chain transfer to polymer;43–45 and the third model considers the formation of linear chains 46–48. The complete simulation study includes the design of model discrimination experiments, simulation of laboratory experimental data and analyses of the resulting data.…”

Section: Introductionmentioning

confidence: 99%

“…The values of the parameters of the model selected to generate the experimental data, used during the discrimination process, were varied along the characteristic directions of model parameter uncertainties, in order to make the obtained conclusions independent of the analyzed parameters. Therefore, it became possible to map the parameter space regions where model discrimination could be achieved, also allowing for preliminary quantification of the LCB content. The second case study investigates the discrimination of three different models that describe the copolymerization of ethylene and 1,9‐decadiene with a CGC catalyst in a semi‐batch reactor, using experimental data reported in a previous work 9 …”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Discrimination of Chain Branching Models in Addition Diene Polymerizations

Brandão

Alberton

Pinto

2020

Macro Theory & Simulations

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The present work analyzes whether discrimination of chain branching models is possible in addition diene polymerizations, based solely on average molecular weights and monomer conversions monitored during the reaction course, as usually performed in most quality control labs of industrial plants. In addition, it is verified whether the analyzed models present enough flexibility to fit data generated with the other rival models. Three kinetic models are considered, and kinetic parameters are varied in order to represent average molecular weights and monomer conversions that are typically found in addition diene polymerizations. The results show that model discrimination is indeed feasible with few experiments, even when only average molecular weights measured through GPC analyses are available, which can be of significant practical importance at plant site for critical characterization of product properties and process performance.

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Section: Methodsmentioning

confidence: 99%

Section: Models Developmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Discrimination of Chain Branching Models in Addition Diene Polymerizations

Brandão

Alberton

Pinto

2020

Macro Theory & Simulations

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Monte Carlo simulation of terpolymerization: Optimizing the simulation and post‐processing times

2023

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Monte Carlo simulations are a useful and easy way to understand a polymerization reaction process properly. However, achieving reliable results with Monte Carlo simulations can also lead to prohibitive computational times and a considerable amount of data to be processed afterward. The present study analyses the Monte Carlo simulation of a steady‐state terpolymerization process to reduce the overall computational time of the simulation and the post‐processing of its results. Different sorting algorithms (Bubble, Insertion, Selection, and Tim) and Python libraries (Joblib and Numba) were used. The chain composition distribution and the micro‐structures resultant of different scenarios were assessed by processing the simulated mechanism results. The simulation time results indicate the Tim sorting algorithm as the best to use in the post‐processing step and the Numba library as the best suited for both the simulation and the post‐processing step.

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Molecular Weight Distribution in Ring‐Opening Polymerization of Propylene Oxide Catalyzed by Double Metal Complex: A Model Simulation

Zhao

Fan

2021

Macro Theory & Simulations

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easy to calculate. Even though this method cannot show out the full MWD curves, it gathers the most important information such as monomer conversion (x), molecular weight (MW), and polydispersity index (PDI). [28] PDI quantifies the width of MWD.The ring-opening polymerization (ROP) of propylene oxide (PO) catalyzed by double metal complex (DMC) is generally considered to have the characteristics of living polymerization. For example, the MW increases with x, and block copolymers with ethylene oxide can be prepared. However, our recent experimental study shows that the MWD of products is not easy to keep very narrow even if the polymerization is carried out in batch or plug flow reactor. [34] According to the polymerization mechanism proposed by Huang et al., [35][36][37] it is generally believed that the chain transfer reaction between active chains and dormant chains is the key to narrow MWD. However, up to now, no one has quantitatively investigated the effect of this chain transfer reaction on the MWD.In this work, a kinetic model involving chain propagation and chain transfer is established; the method of moments is used to simulate PDI as well as x and number-average polymerization degree (Xn) under various reaction conditions. We hope that this work can facilitate the understanding of the polymerization mechanism behind various complex phenomena in the ROP catalyzed by DMC. Modeling Section Polymerization MechanismAs Huang et al. [35][36][37] and Kim et al. [38,39] have reported, ROP of PO catalyzed by DMC consists of induction, chain propagation, and transfer reaction. Herein, only the chain propagation and transfer reaction are considered since they are the main reactions that affect MWD. As shown in Scheme 1, chains with active center can be propagated; meanwhile, the active center can be transferred to dormant chains so that they are activated and propagated. It is the chain transfer between the active chain and dormant chain that results in the more uniform chain growth. Obviously, it can be thought that the instant rate In the present work, method of moments is used to model the molecular weight distribution (MWD) of polypropylene glycol (PPG) produced with ring-opening polymerization of propylene oxide catalyzed by double metal complex (DMC), and an explicit expression about the polydispersity index (PDI) of PPG is obtained. The simulated results indicate that decreasing the initial concentration ratio of monomer to total chains (K 1 ) or increasing the rate constant ratio of chain transfer to propagation (K 2 ) leads to smaller PDI. Reducing the concentration of DMC can induce larger PDI. When the PPG's initial PDI (i.e., PDI of initiator) increases, PDI of the final PPG grows up linearly. However, with the increase of monomer conversion, PDI increases first and then decreases, that is, there is a critical conversion. The possible lack of chain transfer at the beginning of polymerization and the insufficient chain transfer caused by increased K 1 , decreased concentration of catalyst, and decreased...

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Copolymerization of Ethylene with 1,9‐Decadiene: Part II—Prediction of Molecular Weight Distributions

Cited by 11 publications

References 38 publications

Discrimination of Chain Branching Models in Addition Diene Polymerizations

Discrimination of Chain Branching Models in Addition Diene Polymerizations

Monte Carlo simulation of terpolymerization: Optimizing the simulation and post‐processing times

Molecular Weight Distribution in Ring‐Opening Polymerization of Propylene Oxide Catalyzed by Double Metal Complex: A Model Simulation

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