Elastomer swelling and Hansen solubility parameters

Nielsen, Tenna Brandt; Hansen, Claus Thorp

doi:10.1016/j.polymertesting.2005.05.007

Cited by 58 publications

(29 citation statements)

References 2 publications

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“…[17] and already mentioned by Hansen, [19] the enthalpy of mixingr elates to the square of the parameter distance:the interaction parameter, b,i s[ Eq. (8)…”

Section: #3 Using the Squared Distancementioning

confidence: 99%

Revisiting Hansen Solubility Parameters by Including Thermodynamics

et al. 2017

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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.

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“…[17] and already mentioned by Hansen, [19] the enthalpy of mixingr elates to the square of the parameter distance:the interaction parameter, b,i s[ Eq. (8)…”

Section: #3 Using the Squared Distancementioning

confidence: 99%

Revisiting Hansen Solubility Parameters by Including Thermodynamics

et al. 2017

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“…For the last 50 years, different methods for evaluating experimental parameters of polymers have been reported. Measurable properties, such as intrinsic viscosity,17 turbidimetry,18 weight gain,19 or swelling20 of a polymer film, were reported. Verheyen et al21 also reported a correlation between the experimental solubility and solubility parameters.…”

Section: Theoretical Of Solubility Predictionsmentioning

confidence: 99%

Solubility of polyhydroxyalkanoates by experiment and thermodynamic correlations

Jacquel

et al. 2007

AIChE Journal

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This article presents and develops the thermodynamic correlation model to obtain the solubility of polyhydroxyalkanoates (PHAs) in solvents. This model offers a new way to evaluate the polymer solubility parameters and regressions between experimental solubility and solubility parameters. Important parameters influencing solubility such as temperature, polymer molecular weight, crystallinity, and the kind of PHAs were studied. Experiments were carried out on PHB-co-Hx copolymers of different contents. Finally, a model which takes into account these parameters were established and tested on 232 experimental points. The method developed could be used for the selection of a solvent with high efficiency, low price, and low toxicity.

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“…By calculating the Euclidean distance between two points in the Hansen space, one can evaluate the miscibility of two substances according to the commonly known rule "similia similibus solvuntur." ere are many scientific and industrial fields of Hansen solubility parameters application, including polymer materials, paints, and coatings (e.g., miscibility and solubility [5][6][7][8][9], environmental stress cracking [10,11], adhesion [12], plasticizers compatibility [13], swelling, solvent diffusion, and permeation [14,15], and polymer sensors designing [16], pigments and nanomaterials dispersibility [3,[17][18][19][20]), membrane filtration techniques [21], and pharmaceutics and pharmaceutical technology (e.g., solubility [22][23][24][25][26][27], cocrystal screening [28,29], drug-DNA interaction [30], drug's absorption site prediction [31], skin permeation [32], drug-nail affinity [33], drug-polymer miscibility, and hot-melt extrusion technology [34][35][36][37]).…”

Section: Introductionmentioning

confidence: 99%

Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String

Przybyłek

Jeliński

Cysewski

2019

Journal of Chemistry

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A new method of Hansen solubility parameters (HSPs) prediction was developed by combining the multivariate adaptive regression splines (MARSplines) methodology with a simple multivariable regression involving 1D and 2D PaDEL molecular descriptors. In order to adopt the MARSplines approach to QSPR/QSAR problems, several optimization procedures were proposed and tested. e effectiveness of the obtained models was checked via standard QSPR/QSAR internal validation procedures provided by the QSARINS software and by predicting the solubility classification of polymers and drug-like solid solutes in collections of solvents. By utilizing information derived only from SMILES strings, the obtained models allow for computing all of the three Hansen solubility parameters including dispersion, polarization, and hydrogen bonding. Although several descriptors are required for proper parameters estimation, the proposed procedure is simple and straightforward and does not require a molecular geometry optimization. e obtained HSP values are highly correlated with experimental data, and their application for solving solubility problems leads to essentially the same quality as for the original parameters. Based on provided models, it is possible to characterize any solvent and liquid solute for which HSP data are unavailable.

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Elastomer swelling and Hansen solubility parameters

Cited by 58 publications

References 2 publications

Revisiting Hansen Solubility Parameters by Including Thermodynamics

Revisiting Hansen Solubility Parameters by Including Thermodynamics

Solubility of polyhydroxyalkanoates by experiment and thermodynamic correlations

Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String

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