Solubility of selected polymers in cyclohexane: comparison between Flory–Huggins interaction parameters calculated using three different molecular dynamics simulation approaches

IF 2.9 3区 化学 Q3 CHEMISTRY, PHYSICAL Physical Chemistry Chemical Physics Pub Date : 2024-11-26 DOI:10.1039/d4cp03690e
Gabriel P. Costa, Stanislav R. Stoyanov, Qi Liu, Phillip Choi
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Abstract

Accurate prediction of solubility of polymers in solvents a priori is highly desirable in practice. To this end, the Flory–Huggins interaction parameter χ is commonly used and molecular dynamics simulation, a powerful computational tool, has been used for such a purpose. To calculate χ, there exist three possible strategies using molecular dynamics simulation. One is through the calculation of Hildebrand solubility parameters of the pure components while the other two are to calculate the enthalpy of solvation and Gibbs free energy of solvation for the solution, respectively. This study evaluated these three strategies using binary solutions containing a hydrophobic or hydrophilic polymer (polyisobutylene, polystyrene, cis and trans polybutadiene, cis and trans polyisoprene, poly(ethylene oxide), and polyacrylamide) and an aliphatic solvent – cyclohexane. We found that χ determined via solubility parameters predicted the solubility trend but deviated significantly from experimental values. On the other hand, the enthalpy of solvation approach provided the most accurate χ values, compared to experiment, at a reasonable computational demand, especially for hydrocarbon polymers, while the Gibbs free energy of solvation approach, though more computationally intensive, did not significantly improve χ from the enthalpy of solvation approach. In particular, the Gibbs free energy of solvation approach overestimated χ for non-polar polymers. A conformational analysis of the solvated polymers revealed that all polymers collapsed in cyclohexane with polyethylene oxide and polyacrylamide collapsed the most as expected. For the two polar polymers used, the collapse was evidenced by abrupt changes in radius of gyration (Rg) and solvent accessible surface area (SASA) in the early stage of molecular dynamics simulation trajectories, and plateauing at much lower final values. Conversely, the hydrocarbon polymers exhibited minimal deviation from the expected Rg and barely any change in SASA with time. Our findings demonstrated that there exist differences in the accuracy and computational resources used when different molecular dynamics simulation strategies are used in the determination of χ.

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选定聚合物在环己烷中的溶解度:三种不同分子动力学模拟方法计算得出的 Flory-Huggins 相互作用参数之间的比较
在实际应用中,预先准确预测聚合物在溶剂中的溶解度是非常必要的。为此,通常使用 Flory-Huggins 相互作用参数 χ,而分子动力学模拟是一种强大的计算工具。要计算 χ,有三种可能的分子动力学模拟策略。一种是通过计算纯成分的希尔德布兰德溶解度参数,另两种是分别计算溶液的溶解焓和溶解吉布斯自由能。本研究使用含有疏水性或亲水性聚合物(聚异丁烯、聚苯乙烯、顺式和反式聚丁二烯、顺式和反式聚异戊二烯、聚环氧乙烷和聚丙烯酰胺)和脂肪族溶剂(环己烷)的二元溶液对这三种策略进行了评估。我们发现,通过溶解度参数确定的 χ 预测了溶解度趋势,但与实验值偏差很大。另一方面,与实验相比,溶解焓方法在合理的计算要求下提供了最准确的 χ 值,特别是对于碳氢化合物聚合物;而溶解的吉布斯自由能方法虽然计算量更大,但与溶解焓方法相比并没有显著改善 χ 值。特别是,对于非极性聚合物,溶解的吉布斯自由能方法高估了 χ。对溶解聚合物的构象分析表明,所有聚合物在环己烷中都会塌缩,其中聚环氧乙烷和聚丙烯酰胺的塌缩程度最高。对于所使用的两种极性聚合物,塌缩表现为分子动力学模拟轨迹早期的回旋半径(Rg)和溶剂可及表面积(SASA)突然发生变化,并在较低的最终值上趋于平稳。相反,碳氢化合物聚合物的 Rg 与预期值偏差极小,SASA 随时间几乎没有变化。我们的研究结果表明,使用不同的分子动力学模拟策略测定 χ 时,在精度和所使用的计算资源方面存在差异。
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来源期刊
Physical Chemistry Chemical Physics
Physical Chemistry Chemical Physics 化学-物理:原子、分子和化学物理
CiteScore
5.50
自引率
9.10%
发文量
2675
审稿时长
2.0 months
期刊介绍: Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.
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