Predicting Polyelectrolyte Coacervation from a Molecularly Informed Field-Theoretic Model
Predicting Polyelectrolyte Coacervation from a Molecularly Informed Field-Theoretic Model
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从分子信息场论模型预测聚电解质凝聚
DOI:
10.1021/acs.macromol.2c01759
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发表时间:
2022
期刊:
影响因子:
5.5
通讯作者:
Shell, M. Scott
中科院分区:
文献类型:
--
作者:
Nguyen, My;Sherck, Nicholas;Shen, Kevin;Edwards, Chelsea E.;Yoo, Brian;Köhler, Stephan;Speros, Joshua C.;Helgeson, Matthew E.;Delaney, Kris T.;Shell, M. Scott
Understanding the phase behavior of polyelectrolyte coacervation is crucial for many applications, including consumer formulations, wet adhesives, processed food, and drug delivery. However, in most cases, modeling coacervation is not easily accessed by molecular simulation methods due to the long-range nature of electrostatic forces and the typically high molecular weights of the species involved. We present a modeling strategy to study complex coacervation leveraging the strengths of both particle simulations and polymer field theory. Field theory is uniquely suited to capture larger-length scales that are inaccessible to particle simulations, but its predictive capability is limited by the need to specify emergent parameters. Using model coacervate-forming systems consisting of poly(acrylic acid) and poly(allylamine hydrochloride), we show an original way to use small-scale, all-atom simulations to parameterize field-theoretic models via the relative entropy coarse-graining approach. The dependence of coacervation on the salt concentration, molecular weight, and charge stoichiometry is predicted without fitting to experimental data and is consistent with experimental trends including asymmetric phase behavior from non-stoichiometric mixtures of polyelectrolytes. This demonstrates a unique simulation approach to study phase behavior in coacervate-forming systems, which is particularly useful when chemical specificity is of interest.
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DOI:
10.1073/pnas.2201804119
发表时间:
2022-05-03
影响因子:
11.1
作者:
通讯作者:
--
影响因子:
10.7
作者:
V. Tolstoguzov
通讯作者:
V. Tolstoguzov
影响因子:
4.6
作者:
Shao, Hui;Bachus, Kent N.;Stewart, Russell J.
通讯作者:
Stewart, Russell J.
影响因子:
5.5
作者:
Neitzel AE;Fang YN;Yu B;Rumyantsev AM;de Pablo JJ;Tirrell MV
通讯作者:
Tirrell MV
影响因子:
5.5
作者:
U. Suter
通讯作者:
U. Suter