Modeling Vapor Solubility in Semicrystalline Polyethylene

Moebus, Joseph A.; Greenhalgh, Brian R.

doi:10.1002/mren.201700072

Cited by 26 publications

(98 citation statements)

References 29 publications

(84 reference statements)

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“…In our previous article, we discussed the importance of solubility predictions in the design and operation of chemical processes. Polymer systems are an important class of these, as they exhibit complex phase behavior, and they are not well modeled by the equations of state (EOS) typically used in process engineering.…”

Section: Introductionmentioning

confidence: 99%

“…Polymer systems are an important class of these, as they exhibit complex phase behavior, and they are not well modeled by the equations of state (EOS) typically used in process engineering. Advanced fluid equations of state such as the perturbed chain‐statistical associating fluid theory equation of state (PC‐SAFT EOS) have shown remarkable utility in predicting polymer phase behavior, but these “fluid” EOS do not in general capture an important aspect of semicrystalline polymers; tie chains, While model parameters within such equations of state can be adjusted to match solubility data in semicrystalline polymers, such “tuned” models do not extrapolate in the general sense. For example, adjusting binary interaction parameters in a fluid EOS between an absorbing substance and the polymer may allow one to match an experimental isotherm without formally accounting for the effects of crystallinity and tie chains, but this does not allow one to predict the solubility at a different temperature, nor the absorption of another substance in that same polymer.…”

Section: Introductionmentioning

confidence: 99%

“…In our previous article, we described a model to predict the solubility of vapors in semicrystalline polyethylenes. In that work we presented the basic theory (originally developed by Michaels and Hausslein, and subsequently applied by several other authors) by which one can account for the inhibition of solubility by tie chains.…”

Section: Introductionmentioning

confidence: 99%

“…In effect, Equation represents the meltpoint depression of the polymer due to absorption of other species. Further details on the background, subordinate terms and parameters and references for the above equations are provided in our previous work . Here we wish to address an error in that work, namely how amorphous phase mole fractions, which are the basis of the solubility prediction represented by Equation , are converted to mass fraction on a granule (or total) basis.…”

Section: Introductionmentioning

confidence: 99%

“…Here we wish to address an error in that work, namely how amorphous phase mole fractions, which are the basis of the solubility prediction represented by Equation , are converted to mass fraction on a granule (or total) basis. The expression we gave (as Equation ) for relating mass fraction on an amorphous and total basis was incorrect. Here we present the form that we believe to be accurate.…”

Section: Introductionmentioning

confidence: 99%

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Parameterization of Models for Vapor Solubility in Semicrystalline Polyethylene

Savatsky

Moebus

Greenhalgh

2019

Macro Reaction Engineering

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This paper extends the previous article by the authors on the solubility of hydrocarbon vapors in semicrystalline polyethylenes produced in the gas phase process. That work demonstrates a computational model for solubility based on an activity coefficient modification of the Sako-Wu-Prausnitz equation of state. In that work, by fitting a key parameter, one related to the constraint of tie chains on polymer fluid behavior, to a single isopentane solubility isotherm, accurate predictions of hydrocarbon solubility in polymer granules over a range of temperature, pressure, and composition are reported. In the present work, additional experimental solubility data are reported, an error in the authors' previous article is corrected, and a useful parameterization method that improves the predictive capabilities of the model is demonstrated. By using the model to predict much of the authors' own experimental data, as well as that published by others in the field, it is demonstrated how the proposed parameterization method allows for accurate predictions using a limited amount of experimental measurements.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Parameterization of Models for Vapor Solubility in Semicrystalline Polyethylene

Savatsky

Moebus

Greenhalgh

2019

Macro Reaction Engineering

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Impact of order of catalytic ethylene and propylene polymerization on nanometer scale isotactic polypropylene‐polyethylene blend morphology in nascent heterophasic granules revealed by low voltage scanning electron microscopy and scanning transmission electron microscopy

Brant

Brown

Narváez

2021

J of Applied Polymer Sci

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New heterophasic granules comprised of two high molecular weight semi‐crystalline components ‐ polyethylene (PE) and isotactic polypropylene (iPP) ‐ are prepared from a MgCl2 supported Zeigler‐Natta catalyst. The impact of order of monomer addition on granule morphology and extent of mixing of PE and iPP in these monomer‐to‐polymer scenarios are examined. In one polymerization propylene is followed by ethylene (iPP‐PE; 1), and in the second ethylene is followed by propylene (PE‐iPP; 2). Detailed morphological assessments were carried out on RuO4 stained sections of the nascent granules of these heterophasic products using low voltage scanning electron microscopy (LVSEM) and scanning transmission electron microscopy (STEM). In these side‐by‐side granule morphology comparisons, LVSEM, which has not been used for granule examinations, has proved to be invaluable, typically providing insights into phase morphology that STEM does not. Both polymerizations 1 and 2 result in intimate mixing of PE and iPP on the tens to hundreds of nanometer scale. However, morphological outcomes for 1 and 2 are markedly different. In the case of 1, comprising 31 wt% iPP and 69 wt% of PE (the second‐grown phase), a reticulated mesh network of PE is readily observed coursing through much of the first produced iPP globular and sub‐globular matrix. The PE fibrils that comprise this network are remarkably uniform in diameter; approximately 100–150 nm. This aspect of the morphology is consistent with a PE sheath encapsulating both iPP globules and sub‐globules commonly found in iPP homopolymer granules made with MgCl2 catalysts. This morphology is similar to that of the most extensively studied heterophasic granules, classic iPP‐ethylene‐propylene rubber (EPR) impact copolymer (ICP), where the second grown EPR fills in space between and around the iPP globules and sub‐globules. Thus, the dominant morphology of 1 is consistent with the often‐called pore‐filling model. Using the same catalyst and arriving at a similar global composition (65 wt% PE and 35 wt% iPP), sample 2 is produced through the reverse order of monomer addition. The dominant morphology for 2 cannot be explained by the pore‐filling model. Instead, LVSEM most clearly shows that the second grown iPP phase, is finely dispersed throughout the PE matrix (not outside it) as irregularly shaped inclusions that are nominally 100 to 400 nm in diameter, so the dominant morphology in 2 is consistent with the proposed but not previously observed core‐shell model. The STEM results for 2 also reveal the presence of primitive PE spherulites and organized PE lamellae in the granules; structures not found in 1 and apparently not reported before in polyethylene homopolymer granules. These structures form likely from heat released during ethylene polymerization in the first step in 2. In LVSEM, the PE and iPP phases provide different amplitude contrast (grayscale) that is useful for calibration. In the LVSEM images of both samples 1 and 2, non‐binary strong grayscale gradients are observ...

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A conceptual multilevel approach to polyolefin reaction engineering

Soares

McKenna

2022

Can J Chem Eng

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This article gives a wide overview of different types of mathematical models that can be used to describe the polymerization of linear olefins with coordination catalysts. We expanded the conventional classification of mathematical models into micro-, meso-, and macroscale, to include seven modelling levels: catalysis, polymerization kinetics, thermodynamic equilibrium, particle transport phenomena, particle interactions, reactor fluid dynamics, and reactor residence time distribution. Some of these levels may coexist at the same scale, but they are better treated separately because they make use of distinct modelling approaches. How complex the models in each level need to be, as well as how many modelling levels should be implicitly included, depends on the type of application intended for the simulations. In this paper, we will argue that the proposed levels of mathematical modelling not only bring to our attention the complexity behind the simulation of laboratory-and industrial-scale olefin polymerization reactors but are also useful conceptual tools to assist us to decide which levels to include and which ones to exclude when we develop simulation packages to describe olefin polymerization processes.

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Modeling Vapor Solubility in Semicrystalline Polyethylene

Cited by 26 publications

References 29 publications

Parameterization of Models for Vapor Solubility in Semicrystalline Polyethylene

Parameterization of Models for Vapor Solubility in Semicrystalline Polyethylene

Impact of order of catalytic ethylene and propylene polymerization on nanometer scale isotactic polypropylene‐polyethylene blend morphology in nascent heterophasic granules revealed by low voltage scanning electron microscopy and scanning transmission electron microscopy

A conceptual multilevel approach to polyolefin reaction engineering

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