Redefining solubility parameters: Bulk and surface properties from unified molecular descriptors

Panayiotou, Costas; Mastrogeorgopoulos, Spyros; Aslanidou, Dimitra; Avgidou, Mary; Hatzimanikatis, Vassily

doi:10.1016/j.jct.2017.03.035

Cited by 19 publications

(57 citation statements)

References 32 publications

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“…We recognize that there are several methods to perform quantitative structure property relationship (QSPR) modeling in terms of Abraham's LSER descriptors based on inter‐relationships between the LSER molecular descriptors and partial solvation parameters (PSPs), and HSPs, wherein COSMO‐RS calculations provide the bridge that unifies the LSER, PSP, and HSP methods. The successful application of these predictive theories to a multitude of problems is well‐documented in the literature, but rather than adapting these methods to handle our P3HT‐solvent gradient systems, which is beyond the scope of this study, we chose to use experimentally measured LSER parameters to perform our analysis.…”

Section: Resultsmentioning

confidence: 99%

Impact of Varying Binary Solvent Gradients on the Solubility Parameters of Poly(3‐hexylthiophene)

Sharp

Taylor

Andrews

et al. 2018

Macro Chemistry & Physics

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Current methods for estimating the solubility parameters (SPs) of a solute, particularly conjugated polymers and organic semiconductor moieties, suffer from theoretical and computational deficiencies that have led to many questions and investigations that seek improvement in solubility parameter theory. This investigation focuses on the variation of SPs of a protype conjugated polymer, poly(3‐hexylthiophene), using (1) different set of solvents and binary solvent mixtures having a broad range of chemical characteristics, and (2) multiple computational methodologies, for example, functional solubility parameter and Hansen solubility parameter approaches. The results reveal that the choice of solvents and the fitting methodology impact the empirical SPs when using the binary gradient method. The validity of the observed SPs and the relative contributions of the dispersion, polar, and hydrogen‐bonding interactions are further rationalized using linear solvation energy relationship modeling of the solubility data.

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Section: Resultsmentioning

confidence: 99%

Impact of Varying Binary Solvent Gradients on the Solubility Parameters of Poly(3‐hexylthiophene)

Sharp

Taylor

Andrews

et al. 2018

Macro Chemistry & Physics

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“…The final analysis of the PCL solvent affinities utilized the LSER molecular descriptor methodology developed by Panayiotou et al . Within this formalism, the polymer–‐solvent affinities can be defined in terms of Flory–Huggins interaction parameters, χ 12,FH , which are defined in terms of tabulated LSER descriptors V x , A , B , E , and S ,

\begin{matrix} lefttrue \\ {italicφ}_{italic2}^{sans-serif2} {italicχ}_{12, FH} = \frac{10, 000 {italicφ}_{italic2}^{sans-serif2} {italicV}_{x, 1}}{italicRT} [{((), \sqrt{sans-serif3.1 + \frac{{italicE}_{italic1}}{{italicV}_{x, 1}}} + \sqrt{sans-serif3.1 + \frac{{italicE}_{italic2}}{{italicV}_{x, 2}}})}^{sans-serif2} + {((), \sqrt{\frac{S_{1}}{V_{italicx, italic1}}} + \sqrt{\frac{S_{2}}{V_{italicx, italic2}}})}^{sans-serif2}] \\ + {([], r_{1} ν_{H} - sans-serifln ((), \frac{x_{1}}{ν_{10}}) - sans-serifln ((), \frac{x_{1}}{ν_{01}}))}_{italicmixture} - {([], r_{1} ν_{11} + sans-serif2 sans-serifln ((), sans-serif1 ‐ r_{1} ν_{11}))}_{pure 1} \end{matrix}

where the solvent and polymer are denote 1 and 2, respectively, and φ 2 is the volume fraction of the PCL polymer. The LSER parameters of the solvents and PCL taken used in this working equation from the literature are given in Table .…”

Section: Resultsmentioning

confidence: 99%

“…where x i is the mole fraction of the i th compound, and r i is the number of identical segments with a hard core volume

V_{i}^{*}

in the i th molecule. For each solvent (1) r 1 can be approximated quite well by the equation r 1 = –0.070 + 4.778 V x , where V x is the McGowan volume . For polymers (2), r 2 is evaluated using the relation V x , i / r i = 0.21, and r in the polymer–solvent mixture is given r = X 1 r 1 + X 2 r 2 .…”

Section: Resultsmentioning

confidence: 99%

“…For each solvent (1) r 1 can be approximated quite well by the equation r 1 = –0.070 + 4.778 V x , where V x is the McGowan volume . For polymers (2), r 2 is evaluated using the relation V x , i / r i = 0.21, and r in the polymer–solvent mixture is given r = X 1 r 1 + X 2 r 2 . Finally, ν 12 is the reduced number of hydrogen bonds between a solvent donor ( d 1 ) and polymer acceptor ( a 2 ).…”

Section: Resultsmentioning

confidence: 99%

“…Additionally, the second virial coefficients obtained from static light scattering (SLS) measurements were used as a complementary evaluation of the polymer‐solvent affinity. Finally, we compare the relative solvent affinities for PCL reflected by the experimental [ η ] PCL values to the affinities predicted by (1) COSMO‐RS calculations, (2) partial solvation parameters (PSPs), and (3) a recent QSPR/LSER thermodynamic framework based on quantitative structure–property relationships (QSPR) and linear solvation energy relationship (LSER) molecular descriptors …”

Section: Introductionmentioning

confidence: 99%

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Solubility parameters and solvent affinities for polycaprolactone: A comparison of methods

Boucher

2020

J of Applied Polymer Sci

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Intrinsic viscosity measurements were used in combination with the functional solubility parameter (FSP) and Hansen solubility parameter (HSP) fitting methods to determine the solubility parameters (SPs) of polycaprolactone (PCL). Despite using only eight solvents, a simple similarity criteria approach showed that the HSPs and FSPs were good predictors of the relative solvent-PCL affinity compared to HSPs available in the literature and SPs calculated using additive group contribution methods. Three complementary computational methodologies-Conductor-like Screening MOdel for Real Solvents (COSMO-RS), partial solvation parameters (PSPs), and a thermodynamic quantitative structure-property relationship (QSPR) approach-were used to substantiate the relative solvent-PCL affinities revealed by the intrinsic viscosity measurements. The solvent affinities predicted by all three techniques were in good agreement with the trend observed in the experimental intrinsic viscosity data, but the COSMO-RS activity coefficients, ln(γ PCL ), were slightly superior to the PSP and thermodynamic QSPR methods, particularly when incorporating the Elbro free-volume combinatorial correction in the COSMO-RS calculations. As part of this study, the FSP fitting algorithm was modified to obtain the PSPs for PCL in terms of the intrinsic viscosity data, thereby, presenting a promising new way to calculate the PSPs of polymers from empirical solubility and solvent affinity data.

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Mitigating Complexity: Cohesion Parameters and Related Topics. I: The Hildebrand Solubility Parameter

Wilhelm

2018

J Solution Chem

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Redefining solubility parameters: Bulk and surface properties from unified molecular descriptors

Cited by 19 publications

References 32 publications

Impact of Varying Binary Solvent Gradients on the Solubility Parameters of Poly(3‐hexylthiophene)

Impact of Varying Binary Solvent Gradients on the Solubility Parameters of Poly(3‐hexylthiophene)

Solubility parameters and solvent affinities for polycaprolactone: A comparison of methods

Mitigating Complexity: Cohesion Parameters and Related Topics. I: The Hildebrand Solubility Parameter

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