A Machine Learning Study of Polymer-Solvent Interactions

Ting-Li Liu; Lun-Yang Liu; Fang Ding; Yun-Qi Li

doi:10.1007/s10118-022-2716-2

Your Location：

Home >

Browse articles >

A Machine Learning Study of Polymer-Solvent Interactions

RESEARCH ARTICLE | Updated：2022-06-22

- A Machine Learning Study of Polymer-Solvent Interactions
- A Machine Learning Study of Polymer-Solvent Interactions
- Chinese Journal of Polymer Science 2022年40卷第7期页码：834-842
- Affiliations：
  
  a.State Key Laboratory of Polymer Physics and Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China
  b.School of Applied Chemistry and Engineering, University of Science and Technology of China, Hefei 230026, China
- Author bio：
  
  lyliu@ciac.ac.cn (L.Y.L.)
  yunqi@ciac.ac.cn (Y.Q.L.)
- Funds：
  
  The work was financially supported by the National Natural Science Foundation of China (Nos. 21774128, U1832177, 22173094, 51988102), CAS Key Research Program of Frontier Sciences (No. QYZDY-SSW-SLH027). We are grateful to Network and Computing Center, Changchun Institute of Applied Chemistry for essential support.
- DOI：10.1007/s10118-022-2716-2
  中图分类号：
Scan for full text
Ting-Li Liu, Lun-Yang Liu, Fang Ding, 等. A Machine Learning Study of Polymer-Solvent Interactions[J]. Chinese Journal of Polymer Science, 2022,40(7):834-842.

Ting-Li Liu, Lun-Yang Liu, Fang Ding, et al. A Machine Learning Study of Polymer-Solvent Interactions[J]. Chinese Journal of Polymer Science, 2022,40(7):834-842.
Ting-Li Liu, Lun-Yang Liu, Fang Ding, 等. A Machine Learning Study of Polymer-Solvent Interactions[J]. Chinese Journal of Polymer Science, 2022,40(7):834-842. DOI： 10.1007/s10118-022-2716-2.

Ting-Li Liu, Lun-Yang Liu, Fang Ding, et al. A Machine Learning Study of Polymer-Solvent Interactions[J]. Chinese Journal of Polymer Science, 2022,40(7):834-842. DOI： 10.1007/s10118-022-2716-2.

摘要

We constructed predictive models using machine learning for three polymer-solvent interaction parameters: Flory-Huggins interaction, Hildebrand solubility and the relative energy difference in Hansen solubility, and then compiled them into software (polySML-PSI). The impact of solvent properties on interaction and the applicability of commonly used empirical rules were evaluated further.

Abstract

Polymer-solvent interaction is a fundamentally important concept routinely described by the Flory-Huggins interaction (,χ,), Hildebrand solubility (Δ,δ,) and the relative energy difference (RED) determined from Hansen solubility in experimental, theoretical and simulation studies. Here we performed a machine learning study based on a comprehensive and representative dataset covering the interaction pairs from 81 polymers and 1221 solvents. The regression models provide the coefficients of determination in the range of 0.86−0.94 and the classification models deliver the area under the receiver operating characteristic curve (AUCs) better than 0.93. These models were integrated into a newly developed software polySML-PSI. Important features including Log,P, molar volume and dipole are identified, and their non-linear, non-monotonic contributions to polymer-solvent interactions are presented. The widely known “like-dissolve-like” rule and two broadly used empirical equations to estimate ,χ, as a function of temperature or Hansen solubility are also evaluated, and the polymer-specified constants are presented. This study provides a quantitative reference and a tool to understand and utilize the concept of polymer-solvent interactions.

关键词

Keywords

Flory-Huggins interactionHildebrand solubilityHansen solubilityMachine learningPrediction

references

Flory, P. J . Thermodynamics of high polymer solutions . J. Chem. Phys. , 1942 . 10 51 -61 . DOI:10.1063/1.1723621http://doi.org/10.1063/1.1723621 .

Flory, P. J . Thermodynamics of high polymer solutions . J. Chem. Phys. , 1941 . 9 660 -660. .

Huggins, M. L . Some properties of solutions of long-chain compounds . J. Phys. Chem. , 1942 . 46 151 -158 . DOI:10.1021/j150415a018http://doi.org/10.1021/j150415a018 .

Huggins, M. L. The viscosity of dilute solutions of long-chain molecules. IV . Dependence on concentration . J. Am. Chem. Soc. , 1942 . 64 2716 -2718 . DOI:10.1021/ja01263a056http://doi.org/10.1021/ja01263a056 .

Blanks, R. F.; Prausnitz, J . Thermodynamics of polymer solubility in polar and nonpolar systems . Ind. Eng. Chem. Fundam. , 1964 . 3 1 -8 . DOI:10.1021/i160009a001http://doi.org/10.1021/i160009a001 .

Bae, Y. H.; Okano, T.; Kim, S. W . Temperature dependence of swelling of crosslinked poly(N,N′-alkyl substituted acrylamides) in water . J. Polym. Sci., Part B: Polym. Phys. , 1990 . 28 923 -936. .

Schweizer, K. S.; Yethiraj, A . Polymer reference interaction site model theory: new molecular closures for phase separating fluids and alloys . J. Chem. Phys. , 1993 . 98 9053 -9079 . DOI:10.1063/1.464465http://doi.org/10.1063/1.464465 .

Zhuang, B.; Ramanauskaite, G.; Koa, Z. Y.; Wang, Z. G . Like dissolves like: a first-principles theory for predicting liquid miscibility and mixture dielectric constant . Sci. Adv. , 2021 . 7 eabe7275 DOI:10.1126/sciadv.abe7275http://doi.org/10.1126/sciadv.abe7275 .

Geoghegan, M.; Krausch, G . Wetting at polymer surfaces and interfaces . Prog. Polym. Sci. , 2003 . 28 261 -302 . DOI:10.1016/S0079-6700(02)00080-1http://doi.org/10.1016/S0079-6700(02)00080-1 .

Chen, J.; Zhuang, H.; Zhao, J.; Gardella, J. A . Solvent effects on polymer surface structure . Surf. Interface Anal. , 2001 . 31 713 -720 . DOI:10.1002/sia.1097http://doi.org/10.1002/sia.1097 .

Guillen, G. R.; Pan, Y.; Li, M.; Hoek, E. M. V . Preparation and characterization of membranes formed by nonsolvent induced phase separation: a review . Ind. Eng. Chem. Res. , 2011 . 50 3798 -3817 . DOI:10.1021/ie101928rhttp://doi.org/10.1021/ie101928r .

König-Mattern, L.; Linke, S.; Rihko-Struckmann, L.; Sundmacher, K. . Computer-aided solvent screening for the fractionation of wet microalgae biomass . Green Chem. , 2021 . 23 10014 -10029 . DOI:10.1039/D1GC03471Ehttp://doi.org/10.1039/D1GC03471E .

Xia, J.; Guo, H.; Travesset, A . On the thermodynamic stability of binary superlattices of polystyrene-functionalized nanocrystals . Macromolecules , 2020 . 53 9929 -9942 . DOI:10.1021/acs.macromol.0c01860http://doi.org/10.1021/acs.macromol.0c01860 .

Chen, J.; Zha, L.; Hu, W . Effect of solvent selectivity on crystallization-driven fibril growth kinetics of diblock copolymers . Polymer , 2018 . 138 359 -362 . DOI:10.1016/j.polymer.2018.01.074http://doi.org/10.1016/j.polymer.2018.01.074 .

Tao, Y.; Olsen, B. D.; Ganesan, V.; Segalman, R. A . Domain size control in self-assembling rod-coil block copolymer and homopolymer blends . Macromolecules , 2007 . 40 3320 -3327 . DOI:10.1021/ma062876hhttp://doi.org/10.1021/ma062876h .

Danquah, M.; Fujiwara, T.; Mahato, R. I . Self-assembling methoxypoly(ethylene glycol)-b-poly(carbonate-co-L-lactide) block copolymers for drug delivery . Biomaterials , 2010 . 31 2358 -2370 . DOI:10.1016/j.biomaterials.2009.11.081http://doi.org/10.1016/j.biomaterials.2009.11.081 .

Jimenez, J.; Ford, E . Mapping wet vs gel spinning in Hansen space . Polymer , 2021 . 230 124079 DOI:10.1016/j.polymer.2021.124079http://doi.org/10.1016/j.polymer.2021.124079 .

Robinson, J . Solvent flux through dense polymeric nanofiltration membranes . J. Membr. Sci. , 2004 . 230 29 -37 . DOI:10.1016/j.memsci.2003.10.027http://doi.org/10.1016/j.memsci.2003.10.027 .

Orwoll, R. A.; Arnold, P. A., Polymer-solvent interaction parameter χ. In Physical properties of polymers handbook, Mark, J. E., Ed. Springer: 2007; pp. 233−257.

Venkatram, S.; Kim, C.; Chandrasekaran, A.; Ramprasad, R . Critical assessment of the hildebrand and hansen solubility parameters for polymers . J. Chem. Inf. Model. , 2019 . 59 4188 -4194 . DOI:10.1021/acs.jcim.9b00656http://doi.org/10.1021/acs.jcim.9b00656 .

Hansen, C. Hansen Solubility Parameters: A User's Handbook. CRC Press: 2007, p. 546.

Khansary, M. A . Vapor pressure and Flory-Huggins interaction parameters in binary polymeric solutions . Korean J. Chem. Eng. , 2016 . 33 1402 -1407 . DOI:10.1007/s11814-015-0277-6http://doi.org/10.1007/s11814-015-0277-6 .

Schwahn, D.; Willner, L . Phase Behavior and Flory- Huggins interaction parameter of binary polybutadiene copolymer mixtures with different vinyl content and molar volume . Macromolecules , 2002 . 35 239 -247 . DOI:10.1021/ma010379phttp://doi.org/10.1021/ma010379p .

Sun, Z.; Wang, C. H . Determination of Flory-Huggins interaction parameter and self-diffusion coefficients in ternary polymer solutions by quasielastic light scattering . J. Chem. Phys. , 1995 . 103 3762 -3766 . DOI:10.1063/1.470055http://doi.org/10.1063/1.470055 .

DiPaola-Baranyi, G.; Guillet, J . Estimation of polymer solubility parameters by gas chromatography . Macromolecules , 1978 . 11 228 -235 . DOI:10.1021/ma60061a043http://doi.org/10.1021/ma60061a043 .

Deshpande, D.; Tyagi, O . Gas chromatographic behavior of poly(vinyl acetate) at temperatures encompassing Tg: determination of Tg and η . Macromolecules , 1978 . 11 746 -751 . DOI:10.1021/ma60064a026http://doi.org/10.1021/ma60064a026 .

Emerson, J. A.; Toolan, D. T. W.; Howse, J. R.; Furst, E. M.; Epps, T. H . Determination of solvent-polymer and polymer-polymer Flory-Huggins interaction parameters for poly(3-hexylthiophene) via solvent vapor swelling . Macromolecules , 2013 . 46 6533 -6540 . DOI:10.1021/ma400597jhttp://doi.org/10.1021/ma400597j .

Errede, L. Polymer swelling. 5 . Correlation of relative swelling of poly(styrene-co-divinylbenzene) with the Hildebrand solubility parameter of the swelling liquid . Macromolecules , 1986 . 19 1522 -1525 . DOI:10.1021/ma00160a006http://doi.org/10.1021/ma00160a006 .

Sweere, A. J.; Fraaije, J. G . Prediction of polymer-solvent miscibility properties using the force field based quasi-chemical method PAC-MAC . Polymer , 2016 . 107 147 -153 . DOI:10.1016/j.polymer.2016.11.024http://doi.org/10.1016/j.polymer.2016.11.024 .

Cui, F.; Chen, W.; Kong, X.; Liu, L.; Shi, C.; Li, Y . Anomalous dynamics of water in polyamide matrix . J. Phys. Chem. B , 2019 . 123 3086 -3095 . DOI:10.1021/acs.jpcb.9b01491http://doi.org/10.1021/acs.jpcb.9b01491 .

Chen, W.; Cui, F.; Liu, L.; Li, Y . Assembled structures of perfluorosulfonic acid ionomers investigated by anisotropic modeling and simulations . J. Phys. Chem. B , 2017 . 121 9718 -9724 . DOI:10.1021/acs.jpcb.7b06412http://doi.org/10.1021/acs.jpcb.7b06412 .

Lei, Q.-L.; Ciamarra, M. P.; Ni, R . Nonequilibrium strongly hyperuniform fluids of circle active particles with large local density fluctuations . Sci. Adv. , 2019 . 5 eaau7423 DOI:10.1126/sciadv.aau7423http://doi.org/10.1126/sciadv.aau7423 .

Li, Y.; Liu, L.; Chen, W.; An, L . Materials genome: research progress, challenges and outlook . Sci. Sin. Chim. , 2018 . 48 243 -255 . DOI:10.1360/N032017-00182http://doi.org/10.1360/N032017-00182 .

Liu, L.; Ding, F.; Li, Y . Big data approach on polymer materials: fundamental, progress and challenge . Acta Polymerica Sinica (in Chinese) , 2022 . 52 1 -17. .

Chandrasekaran, A.; Kim, C.; Venkatram, S.; Ramprasad, R . A deep learning solvent-selection paradigm powered by a massive solvent/nonsolvent database for polymers . Macromolecules , 2020 . 53 4764 -4769 . DOI:10.1021/acs.macromol.0c00251http://doi.org/10.1021/acs.macromol.0c00251 .

Greaves, T. L.; Drummond, C. J . Solvent nanostructure, the solvophobic effect and amphiphile self-assembly in ionic liquids . Chem. Soc. Rev. , 2013 . 42 1096 -1120 . DOI:10.1039/C2CS35339Chttp://doi.org/10.1039/C2CS35339C .

Postel, S.; Schneider, C.; Wessling, M . Solvent dependent solute solubility governs retention in silicone based organic solvent nanofiltration . J. Membr. Sci. , 2016 . 497 47 -54 . DOI:10.1016/j.memsci.2015.09.014http://doi.org/10.1016/j.memsci.2015.09.014 .

Sanchez-Lengeling, B.; Roch, L. M.; Perea, J. D.; Langner, S.; Brabec, C. J.; Aspuru-Guzik, A . A Bayesian approach to predict solubility parameters . Adv. Theory Simul. , 2018 . 2 1800069 .

Mark, J. E. Physical properties of polymer handbook. Springer: 2007, Vol. 1076.

Potter, C. B.; Davis, M. T.; Albadarin, A. B.; Walker, G. M . Investigation of the dependence of the Flory-Huggins interaction parameter on temperature and composition in a drug-polymer system . Mol. Pharm. , 2018 . 15 5327 -5335 . DOI:10.1021/acs.molpharmaceut.8b00797http://doi.org/10.1021/acs.molpharmaceut.8b00797 .

Van Dijk, M.; Wakker, A . Some observations on the behaviour of the thermodynamic interaction parameter in dilute polymer solutions . Polymer , 1993 . 34 132 -137 . DOI:10.1016/0032-3861(93)90295-Lhttp://doi.org/10.1016/0032-3861(93)90295-L .

Lindvig, T.; Michelsen, M. L.; Kontogeorgis, G. M . A Flory-Huggins model based on the Hansen solubility parameters . Fluid Phase Equilib. , 2002 . 203 247 -260 . DOI:10.1016/S0378-3812(02)00184-Xhttp://doi.org/10.1016/S0378-3812(02)00184-X .

Bicerano, J. Prediction of Polymer Properties. CRC Press: 2002.

Barton, A. F. M. CRC handbook of solubility parameters and other cohesion parameters, second edition. CRC Press Taylor and Francis: 2017 p. 1−739.

Zade, S. S.; Zamoshchik, N.; Bendikov, M . From short conjugated oligomers to conjugated polymers. Lessons from studies on long conjugated oligomers . Acc. Chem. Res. , 2011 . 44 14 -24 . DOI:10.1021/ar1000555http://doi.org/10.1021/ar1000555 .

RDKit: open-source cheminformatics. http://www.rdkit.org/. (accessed 23 Nov).

Rappé, A. K.; Casewit, C. J.; Colwell, K.; Goddard III, W. A.; Skiff, W. M . UFF, a full periodic table force field for molecular mechanics and molecular dynamics simulations . J. Am. Chem. Soc. , 1992 . 114 10024 -10035 . DOI:10.1021/ja00051a040http://doi.org/10.1021/ja00051a040 .

Stewart, J. J. P. MOPAC2016. http://OpenMOPAC.net (accessed 29 Nov).

Bajusz, D.; Rácz, A.; Héberger, K . Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations . J. Cheminform. , 2015 . 7 1 -13 . DOI:10.1186/s13321-014-0049-zhttp://doi.org/10.1186/s13321-014-0049-z .

Liu, L.; Chen, W.; Liu, T.; Kong, X.; Zheng, J.; Li, Y . Rational design of hydrocarbon-based sulfonated copolymers for proton exchange membranes . J. Mater. Chem. A , 2019 . 7 11847 -11857 . DOI:10.1039/C9TA00688Ehttp://doi.org/10.1039/C9TA00688E .

Ke, G.; Meng, Q.; Finley, T.; Wang, T.; Chen, W.; Ma, W.; Ye, Q.; Liu, T.-Y . Lightgbm: a highly efficient gradient boosting decision tree . Adv. Neural Inf. Process. Syst. , 2017 . 30 3146 -3154. .

Liu, T.; Liu, L.; Cui, F.; Ding, F.; Zhang, Q.; Li, Y . Predicting the performance of polyvinylidene fluoride, polyethersulfone and polysulfone filtration membranes using machine learning . J. Mater. Chem. A , 2020 . 8 21862 -21871 . DOI:10.1039/D0TA07607Dhttp://doi.org/10.1039/D0TA07607D .

Spowage, B. M.; Bruce, C. L.; Hirst, J. D . Interpretable correlation descriptors for quantitative structure-activity relationships . J. Cheminform. , 2009 . 1 1 -13 . DOI:10.1186/1758-2946-1-1http://doi.org/10.1186/1758-2946-1-1 .

Shang, B. Z.; Wang, Z.; Larson, R. G . Effect of headgroup size, charge, and solvent structure on polymer—Micelle interactions, studied by molecular dynamics simulations . J. Phys. Chem. B , 2009 . 113 15170 -15180 . DOI:10.1021/jp9057737http://doi.org/10.1021/jp9057737 .

Ivanova, A.; Madjarova, G.; Tadjer, A.; Gospodinova, N . Effect of solvation and intermolecular interactions on the structure and optical properties of PANI oligomers . Int. J. Quantum Chem. , 2006 . 106 1383 -1395 . DOI:10.1002/qua.20896http://doi.org/10.1002/qua.20896 .

Box, K.; Comer, J . Using measured pKa, LogP and solubility to investigate supersaturation and predict BCS class . Curr. Drug Metab. , 2008 . 9 869 -878 . DOI:10.2174/138920008786485155http://doi.org/10.2174/138920008786485155 .

Papanu, J.; Hess, D.; Soane, D.; Bell, A . Dissolution of thin poly(methyl methacrylate) films in ketones, binary ketone/alcohol mixtures, and hydroxy ketones . J. Electrochem. Soc. , 1989 . 136 3077 DOI:10.1149/1.2096404http://doi.org/10.1149/1.2096404 .

Zhao, Y.; Liu, W.; Pei, X.; Yao, D . Refinement of the theoretical solubility model and prediction of solute solubility in mixed solvent systems . Fluid Phase Equilib. , 2017 . 437 43 -55 . DOI:10.1016/j.fluid.2017.01.006http://doi.org/10.1016/j.fluid.2017.01.006 .

Song, Z.; Chiang, S . W.; Chu, X.; Du, H.; Li, J.; Gan, L.; Xu, C.; Yao, Y.; He, Y.; Li, B. Effects of solvent on structures and properties of electrospun poly(ethylene oxide) nanofibers . J. Appl. Polym. Sci. , 2018 . 135 45787 DOI:10.1002/app.45787http://doi.org/10.1002/app.45787 .

Etxabarren, C.; Iriarte, M.; Uriarte, C.; Etxeberrıa, A.; Iruin, J . Polymer-solvent interaction parameters in polymer solutions at high polymer concentrations . J. Chromatogr. A , 2002 . 969 245 -254 . DOI:10.1016/S0021-9673(02)00886-5http://doi.org/10.1016/S0021-9673(02)00886-5 .

Chang, T . Polymer characterization by interaction chromatography . J. Polym. Sci., Part B: Polym. Phys. , 2005 . 43 1591 -1607 . DOI:10.1002/polb.20440http://doi.org/10.1002/polb.20440 .

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

Data and Machine Learning in Polymer Science

Inferring the Physics of Structural Evolution of Multicomponent Polymers via Machine-Learning-Accelerated Method

Predicting the Mechanical Properties of Polyurethane Elastomers Using Machine Learning