Predicting the Effects of Composition, Molecular Size and Shape, Plasticization, and Swelling on the Diffusion of Aromatic Additives in Block Copolymers

Janes, Dustin W.; Chandrasekar, Vaishnavi; Woolford, Steven E.; Ludwig, Kyle B.

doi:10.1021/acs.macromol.7b00690

Cited by 15 publications

(33 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our regression analysis, we omitted the two data points representing isooctane. It is an additional goal of our research in polymer free volume to go beyond the discrete set of diffusants studied by Vrentas et al to identify diffusant structures which are not represented well by the theory, and propose rational mitigation strategies . The experimental

D

of isooctane is equal to that of cyclooctane even though our analysis of 3‐D conformer structures shows it to be 55% more asymmetric (Table ).…”

Section: Discussionmentioning

confidence: 90%

“…Analysis of the data and the ability to generate shape factors based on the relative symmetry or asymmetry of publicly available 3‐D conformer structures provided input to the diffusion model such that we could make informed predictions of

D

for arbitrary molecules of interest. While the free‐volume theory of Vrentas and Duda is already well‐known to be highly successful at predicting

D

of solvent molecules in polymer melts, its functional form may also be readily adapted to correlate

D

of larger diffusants in solid polymer forms on the basis of size and shape . We believe this approach removes a roadblock in applying free‐volume based predictions to biomaterials, which typically must remain solid at the temperature of interest, and very large additives for which a direct measurement of

D

could be especially slow and cumbersome.…”

Section: Discussionmentioning

confidence: 99%

“…The free‐volume theory of Vrentas and Duda is a diffusion model that predicts the effects of composition and temperature on the polymer/solvent binary mutual diffusion coefficient

D_{12}

. It was validated over the course of roughly two decades of development and comparison to reliable experimental data . Their formula for these effects is

D_{12} = D_{0} {normale normalx normalp ([]|, \frac{- E}{normalR normalT}) (|, 1 - ϕ_{1})}^{2} (|, 1 - 2 χ ϕ_{1}) normale normalx normalp ([]|, \frac{- ω_{1} {\overset{V}{true}}_{1}^{*} - ξ (|, 1 - ω_{1}) {\overset{V}{true}}_{2}^{*}}{{\overset{V}{true}}_{normalF normalH} γ^{- 1}}),

where

D_{0}

is the pre‐exponential factor,

E

is the energy per mole required to overcome attractive forces from neighboring molecules,

ϕ_{1}

is the volume fraction of solvent in the polymer, and

χ

is the Flory–Huggins polymer–solvent interaction parameter.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Characterizing the free volume of ultrahigh molecular weight polyethylene to predict diffusion coefficients in orthopedic liners

et al. 2017

Self Cite

View full text Add to dashboard Cite

Liners used in orthopedic devices are often made from ultrahigh molecular weight polyethylene (UHMWPE). A general predictive capability for transport coefficients of small molecules in UHMWPE does not exist, making it difficult to assess properties associated with leaching or uptake of small molecules. To address this gap, we describe here how a form of the Vrentas-Duda free volume model can be used to predict upper-bound diffusion coefficients (D) of arbitrary molecules within UHMWPE on the basis of their size and shape. Within this framework, the free-volume microstructure of UHMWPE is defined by analysis of a curated set of model diffusants. We determined an upper limit on D for vitamin E, a common antioxidant added to UHMWPE, to be 7.1 × 10 cm s . This means that a liner that contains 0.1 wt % or less Vitamin E and has <120 cm patient contacting surface area would elute <100 µg/day of vitamin E. Additionally, the model predicts that squalene and cholesterol-two pro-oxidizing biological compounds-do not penetrate over 820 µm into UHMWPE liners over the course of 5 years because their D is ≤7.1 × 10 cm s . © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 2393-2402, 2018.

show abstract

D

of isooctane is equal to that of cyclooctane even though our analysis of 3‐D conformer structures shows it to be 55% more asymmetric (Table ).…”

Section: Discussionmentioning

confidence: 90%

D

for arbitrary molecules of interest. While the free‐volume theory of Vrentas and Duda is already well‐known to be highly successful at predicting

D

of solvent molecules in polymer melts, its functional form may also be readily adapted to correlate

D

D

could be especially slow and cumbersome.…”

Section: Discussionmentioning

confidence: 99%

“…The free‐volume theory of Vrentas and Duda is a diffusion model that predicts the effects of composition and temperature on the polymer/solvent binary mutual diffusion coefficient

D_{12}

. It was validated over the course of roughly two decades of development and comparison to reliable experimental data . Their formula for these effects is

D_{12} = D_{0} {normale normalx normalp ([]|, \frac{- E}{normalR normalT}) (|, 1 - ϕ_{1})}^{2} (|, 1 - 2 χ ϕ_{1}) normale normalx normalp ([]|, \frac{- ω_{1} {\overset{V}{true}}_{1}^{*} - ξ (|, 1 - ω_{1}) {\overset{V}{true}}_{2}^{*}}{{\overset{V}{true}}_{normalF normalH} γ^{- 1}}),

where

D_{0}

is the pre‐exponential factor,

E

is the energy per mole required to overcome attractive forces from neighboring molecules,

ϕ_{1}

is the volume fraction of solvent in the polymer, and

χ

is the Flory–Huggins polymer–solvent interaction parameter.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Characterizing the free volume of ultrahigh molecular weight polyethylene to predict diffusion coefficients in orthopedic liners

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…A D value can then be estimated by fitting the time-dependent mass uptake to the appropriate solution of the diffusion equation (Crank, 1979). For low molecular weight leachables (M w < 100 g/mol), gravimetric vapour sorption techniques are very effective to continuously monitor mass uptake of the polymer sample over time (Janes, Chandrasekar, Woolford, & Ludwig, 2017). Experimental determination of transport parameters can be more challenging for larger leachables that diffuse more slowly.…”

Section: Iffus I On Coeffi Cientsmentioning

confidence: 99%

“…The polymers in each category and functional forms of D (M w ) are provided in Saylor et al (2019). For comparison, literature data for each category are also shown (open circles) (Begley et al, 2005;Chandrasekar, Janes, Forrey, et al, 2018;Chandrasekar, Janes, Forrey, et al, 2018;Janes et al, 2017;Kydonieus, 2017;Schwope et al, 1992). For measurements made at different temperatures, the 'Piringer model' (Begley et al, 2005) was used to calculate D at 310 K where S is the equilibrium solubility of the leachable in the matrix.…”

Section: Future Opp Ortunitie Smentioning

confidence: 99%

Advances in predicting patient exposure to medical device leachables

et al. 2020

Self Cite

View full text Add to dashboard Cite

Medical device materials contain chemicals that may pose toxicological concern(s) if released in sufficient quantities. Toxicological risk assessment approaches are increasingly being used in lieu of animal testing to address these concerns. Currently, these approaches rely primarily on in vitro extraction testing to estimate the potential for patients to be exposed to chemicals that may possibly leach out of device materials, but the clinical relevance of the test results is often ambiguous. Recent developments suggest physics‐based models can be used to provide more clinically relevant exposure estimates. However, the lack of data available to parameterize and validate these models presents a barrier to routine use. Herein, we provide an overview of these approaches, including considerations in developing and parameterizing exposure models, strategies that can be used to address the challenges associated with limited data, and potential future directions and improvements.

show abstract

Robust estimates of solute diffusivity in polymers for predicting patient exposure to medical device leachables

Elder

Saylor

2023

Journal of Polymer Science

View full text Add to dashboard Cite

Medical devices often include polymeric components, which contain additives or contaminants that may leach into patients and pose a health risk. Previously, we proposed a mass transport model that conservatively estimates the leaching kinetics and only requires the solute's diffusion coefficient in the polymer, , to be specified. Because determining experimentally is time‐consuming, we also parameterized empirical models to estimate worst‐case values using only the solute molecular weight, . These models were based on a modest database and were limited to 19 polymers and larger solutes ( g/mol). Here, we assemble a much larger database, which enables us to construct more accurate models using a robust statistical approach, expanding the coverage to 50 device‐relevant polymers and smaller solutes ( g/mol). Then, we demonstrate several applications of these bounds, including modeling the release kinetics. Finally, we observe an interesting phenomenon, a discontinuous drop in of up to 25,000× for solutes with g/mol in glassy polymers. Using molecular simulations and cheminformatics tools, we propose a novel definition of the effective diameter of free volume channels in polymers, and we show that solutes larger than this channel size diffuse much more slowly.

show abstract

Predicting the Effects of Composition, Molecular Size and Shape, Plasticization, and Swelling on the Diffusion of Aromatic Additives in Block Copolymers

Cited by 15 publications

References 49 publications

Characterizing the free volume of ultrahigh molecular weight polyethylene to predict diffusion coefficients in orthopedic liners

Characterizing the free volume of ultrahigh molecular weight polyethylene to predict diffusion coefficients in orthopedic liners

Advances in predicting patient exposure to medical device leachables

Robust estimates of solute diffusivity in polymers for predicting patient exposure to medical device leachables

Contact Info

Product

Resources

About