Louwerse Manuel J, Maldonado Ana, Rousseau Simon, Moreau-Masselon Chloe, Roux Bernard, Rothenberg Gadi
Van't Hoff Institute for Molecular Sciences, University of Amsterdam, Postbus 94720, 1090 GS, Amsterdam, The Netherlands.
Inorganic Chemistry and Catalysis, Debye Institute for Nanomaterials Science, Utrecht University, Universteitsweg 99, 3584 CG, Utrecht, The Netherlands.
Chemphyschem. 2017 Nov 3;18(21):2999-3006. doi: 10.1002/cphc.201700408. Epub 2017 Oct 6.
The Hansen solubility parameter approach is revisited by implementing the thermodynamics of dissolution and mixing. Hansen's pragmatic approach has earned its spurs in predicting solvents for polymer solutions, but for molecular solutes improvements are needed. By going into the details of entropy and enthalpy, several corrections are suggested that make the methodology thermodynamically sound without losing its ease of use. The most important corrections include accounting for the solvent molecules' size, the destruction of the solid's crystal structure, and the specificity of hydrogen-bonding interactions, as well as opportunities to predict the solubility at extrapolated temperatures. Testing the original and the improved methods on a large industrial dataset including solvent blends, fit qualities improved from 0.89 to 0.97 and the percentage of correct predictions rose from 54 % to 78 %. Full Matlab scripts are included in the Supporting Information, allowing readers to implement these improvements on their own datasets.
通过应用溶解和混合热力学对汉森溶解度参数方法进行了重新审视。汉森的实用方法在预测聚合物溶液的溶剂方面已获得认可,但对于分子溶质而言仍需改进。通过深入研究熵和焓的细节,提出了一些修正方法,这些方法在不丧失易用性的前提下使该方法在热力学上更为合理。最重要的修正包括考虑溶剂分子的大小、固体晶体结构的破坏、氢键相互作用的特异性,以及预测外推温度下溶解度的机会。在一个包括溶剂混合物的大型工业数据集上对原始方法和改进方法进行测试,拟合质量从0.89提高到0.97,正确预测的百分比从54%上升到78%。支持信息中包含完整的Matlab脚本,使读者能够在自己的数据集中实现这些改进。