Monte Carlo Simulation of Olefin Block Copolymers: Bivariate Distribution of Molecular Weight and Chemical Composition

Buakrong, Poramet; Anantawaraskul, Siripon; Soares, João B. P.

doi:10.1002/masy.201700060

Cited by 5 publications

(11 citation statements)

References 27 publications

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“…The results are in good agreement with previous investigations using Monte Carlo simulation. 46,47 Interestingly, while the effect of P t on MWD and CCD is the opposite of the effect of P p on these distributions, the effect of P t on NBD differs. When we discussed the effect of P p above, we kept the ratio between P s and P t constant.…”

Section: Effect Of the Probability Of Chainmentioning

confidence: 97%

Using Probability Models to Design the Microstructure of Linear Olefin Block Copolymers

Chayrattanaroj,

Anantawaraskul,

Soares

2024

Macromolecules

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Olefin block copolymers (OBCs)�a new type of linear thermoplastic ethylene/1-olefin elastomer�are made via chainshuttling polymerization using two catalysts with different reactivity ratios and a chain-shuttling agent. The microstructure of the OBCs has been analyzed using standard characterization techniques, but these methods cannot reveal the details of their molecular architectures, such as the distribution of the number of blocks in the polymer population; these finer microstructural features fall in the realm of mathematical models. In this article, we developed probability model equations to describe the microstructure of the OBCs and validated our solutions with Monte Carlo simulations. These new equations describe the distributions of molecular weight, chemical composition, number and length of blocks in OBCs made in a continuous stirred-tank reactor operated at steady-state conditions. We also developed a new method to predict the multimodality of the chemical composition distribution of OBCs (which can be experimentally measured) to assist in the design of new OBC materials.

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Section: Effect Of the Probability Of Chainmentioning

confidence: 97%

Using Probability Models to Design the Microstructure of Linear Olefin Block Copolymers

Chayrattanaroj,

Anantawaraskul,

Soares

2024

Macromolecules

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“…Another Monte Carlo simulation depicting bivariate (molecular weight and chemical composition) distribution of olefin block copolymers during CSP was also evolved . The results were found to be different from those of a statistical copolymer of similar molecular weight and composition.…”

Section: Coordinative Chain Transfer Polymerizationmentioning

confidence: 99%

“…Another Monte Carlo simulation depicting bivariate (molecular weight and chemical composition) distribution of olefin block copolymers during CSP was also evolved. 166 The results were found to be different from those of a statistical copolymer of similar molecular weight and composition. Among the chemical input parameters, the chain shuttling probability was found to influence the chemical composition distribution only, while the catalyst ratio does affect both.…”

Section: Cctp For End Functionalization Usingmentioning

confidence: 99%

Coordinative Chain Transfer and Chain Shuttling Polymerization

Mundil,

Bravo,

Merle

et al. 2023

Chem. Rev.

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Coordinative chain transfer polymerization, CCTP, is a degenerative chain transfer polymerization process that has a wide range of applications. It allows a highly controlled synthesis of polyolefins, stereoregular polydienes, and stereoregular polystyrene, including (stereo)block as well as statistical copolymers thereof. It also shows a green character by allowing catalyst economy during the synthesis of such polymers. CCTP notably allows the end functionalization of both the commodity and stereoregular specialty polymers aforementionned, control of the composition of statistical copolymers without adjusting the feed, and quantitative formation of 1-alkenes from ethene. A one-pot one-step synthesis of the original multiblock microstructures and architectures by chain shuttling polymerization (CSP) is also an asset of CCTP. This methodology takes advantage of the simultaneous presence of two catalysts of different selectivity toward comonomers that produce blocks of different composition/microstructure, while still allowing the chain transfer. This affords the production of highly performant functional polymers, such as thermoplastic elastomers and adhesives, among others. This approach has been extended to cyclic esters' and ethers' ring-opening polymerization, providing new types of multiblock microstructure. The present Review provides the state of the art in the field with a focus on the last 10 years.

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“…Several mathematical models have been developed to provide useful insights on how polymerization conditions affect the microstructure of OBCs based on the polymerization mechanism, kinetic parameters, and reaction conditions reported by Zhang et al…”

Section: Introductionmentioning

confidence: 99%

“…Steady‐state Monte Carlo (MC) models were developed later to predict these distributions for OBCs made in CSTRs . Unfortunately, this approach cannot describe dynamic responses, such as those happening in CSTRs during grade transitions and/or nonsteady‐state operation nor in semi‐batch polymerizations.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Monte Carlo Simulation of Olefin Block Copolymers (OBCs) Produced via Chain‐Shuttling Polymerization: Effect of Kinetic Rate Constants on Chain Microstructure

Tongtummachat

Anantawaraskul

Soares

2018

Macro Reaction Engineering

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The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/mren.201800021. PolyolefinsOlefin block copolymers (OBCs) are thermoplastic elastomers with unique statistical multiblock structures produced by chain-shuttling polymerization. In this study, a dynamic Monte Carlo model is used to simulate the effect of changing chain-shuttling (k CS ), catalyst deactivation (k d ), and chain transfer (k tr ) rate constants on the microstructure of OBCs made in a semi-batch reactor. The simulations show how each rate constant governs different aspects of the OBC chains and provide guidelines on how to fine-tune OBC microstructure to achieve precisely designed multiblock structures.

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Monte Carlo Simulation of Olefin Block Copolymers: Bivariate Distribution of Molecular Weight and Chemical Composition

Cited by 5 publications

References 27 publications

Using Probability Models to Design the Microstructure of Linear Olefin Block Copolymers

Using Probability Models to Design the Microstructure of Linear Olefin Block Copolymers

Coordinative Chain Transfer and Chain Shuttling Polymerization

Dynamic Monte Carlo Simulation of Olefin Block Copolymers (OBCs) Produced via Chain‐Shuttling Polymerization: Effect of Kinetic Rate Constants on Chain Microstructure

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