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The solubility parameter for biomedical polymers—Application of inverse gas chromatography
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The solubility parameter for biomedical polymers—Application of inverse gas chromatography ´ K. Adamska ∗ , A. Voelkel, A. Berlinska Pozna´ n University of Technology, Institute of Chemical Technology and Engineering, ul. Berdychowo 4, 60-965 Pozna´ n, Poland
a r t i c l e
i n f o
Article history: Received 4 December 2015 Received in revised form 26 February 2016 Accepted 14 April 2016 Available online xxx Keywords: Solubility parameters Inverse gas chromatography Biomedical polymers
a b s t r a c t The solubility parameter seems to be a useful tool for thermodynamic characterisation of different materials. The solubility parameter concept can be used to predict sufficient miscibility or solubility between a solvent and a polymer, as well as components of co-polymer matrix in composite biomaterials. The values of solubility parameter were determined for polycaprolactone (PCL), polylactic acid (PLA) and polyethylene glycol (PEG) by using different procedures and experimental data, collected by means of inverse gas chromatography. © 2016 Elsevier B.V. All rights reserved.
1. Introduction In the design and preparation of various compositions or formulations, consisting of different components, the characteristics of these components, described by various physicochemical parameters, are important. The application of the solubility parameter in the description of the behaviour of materials in real systems is presented including such phenomena as: miscibility, adhesion and wetting. Hence, the suitable knowledge about mutual miscibility, solubility or compatibility between different materials is desirable. Understanding and quantification of interactions between the components of the system is very often a key problem. This allows to assess the suitability of compounds for established applications. One potential solution is to set the cohesive energy of the components, or more precisely, solubility parameter. This parameter is used for the estimation of the properties of an unknown material and the assessment of the interaction between different materials. The solubility parameter found an application for the prediction and correlation the cohesive and adhesive properties between different materials. It can be used in coatings industry for proper solvent selection in polymer/additives system [1,2] for characterisation of different additives (plasticisers, antistatic agents) used in polymers [3] matching a binder to pigment [4] in printing industry for selection of the best cleaning agent for binders [5].
∗ Corresponding author. E-mail address: [email protected] (K. Adamska).
Different polymers are currently investigated and used in biomedical field. Due to the unique properties of some polymers, such as e.g. biocompatibility or biofuncionality, their importance is constantly increasing.The solubility parameter concept can be used in all aspects of pharmaceutical dosage form design [6], for proper excipients selection [7,8] to predict the effectiveness of adhesives in dentine bonding systems and the ability of the resin to soften or solubilise the dentine surface [9–11], i.e. in characterisation of the materials applied in biological or biomedical systems. Moreover, the solubility parameter is one of the factors, which might be used to describe the penetration and absorption of various blood components into polymers, used as biomaterials [12]. It can be also applied to predict sufficient miscibility/solubility between solvent and polymer or components of co-polymer matrix in composite biomaterials. The aim of this work was to estimate the solubility parameter data for polymers used as biomaterials: polycaprolactone, polylactic acid and polyethylene glycol. Polycaprolactone (PCL) is a semicrystalline, biocompatible, resorbable polymer, which found an application in biomedical field [13]. It is used as a component of composites in tissue engineering as a polymer for blood vessel and cartilage scaffolds [14], bone tissue regeneration [13–16], drug delivery systems [17] and others. Polylactic acid (PLA), due to its unique features of biodegradability, biocompatibility, thermoplastic processability and eco-friendliness, is the most common synthetic polymer used in medical applications, for scaffold preparation [18], in drug delivery systems [19], vascular grafts [20], implants for a bone fixation [21] etc. Poly(ethylene glycol) (PEG) is a commonly applied nonionic, hydrophilic polymer. The attach-
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Please cite this article in press as: K. Adamska, et al., The solubility parameter for biomedical polymers—Application of inverse gas chromatography, J. Pharm. Biomed. Anal. (2016), http://dx.doi.org/10.1016/j.jpba.2016.04.014
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ment of PEG chains has been employed as an effective method of choice in the development of biocompatible materials for many biological and biomedical applications [22]. The solubility parameter term is related to the cohesive energy density (CED), which indicates the energy of vaporisation per unit volume.
ı = (CED)1/2 = H − RT/Vm
1/2
= E/Vm
1/2
(1)
where: ı- solubility parameter, R − gas constant, T − temperature, H − enthalpy of vaporisation, Vm − molar volume, E − free energy of vaporisation. The concept of the solubility parameter was proposed by Scatchard, Hildebrand and Scott and initially applied to systems, cohesion of which arises only from the dispersion forces. The solubility parameter, defined by Eq. (1) is called Hildebrand solubility parameter or Hildebrand parameter [23]. Its extension to system, where the cohesive energy can be considered as a sum of contributions from the dispersive (Ed ), the polar (Ep ) and the hydrogen bonding (Eh ) was introduced by Hansen [2,3]: −Ecoh = −Ed − Ep − Eh
(2)
The so-called Hansen solubility parameter (HSP) is expressed as: ı2T = ı2d + ı2p + ı2h
(3)
where: ıT ,ıd , ıp , ıh denotes the total, the dispersive, the polar and the hydrogen bonding contribution, respectively. The solubility parameter for volatile substances can be calculated from the energy of evaporation [24], by using Eq. (1), but this method gives only a total solubility parameter not Hansen solubility parameters. For low- or non-volatile compounds different methods were drawn up, e.g. solubility of a material in different solvents or a polymer swelling in different solvents, with known solubility parameters value. It is assumed, that the solubility parameter of the investigated material is approximately the same as the solubility parameter of the solvent, which dissolves this material or mixes with it at all proportions, without a change of volume and enthalpy [25]. A similar method is the measurement of the polymer swelling in solvents with known solubility parameter value, taken from literature [26]. Different group contribution methods, e.g. the Hoftyzer and Van Krevelen method can be applied to calculate the solubility parameter, knowing the chemical structure of a material [26–29]. It is assumed, that two materials, having close values of the solubility parameter are likely to be compatible and should be miscible, when mixed together. In this work, inverse gas chromatography was applied for the determination of the solubility parameter for polymers used in biomedical applications. Inverse gas chromatography (IGC) is known as an effective technique to measure different physicochemical parameters and it allows to calculate the solubility parameter, for a wide range of low- or non-volatile materials in a large range of temperatures. In the IGC technique, an investigated material (a stationary phase) is placed in the chromatographic column, and its properties are deduced from behaviour of injected, volatile probes (test solutes), transported by a mobile phase. As a result of an interaction between the test solutes and the stationary phase, the retention data obtained are used to calculate the Flory) and furtherly the solubility Huggins interaction parameter (∞ 1,2 parameter (␦2 ) [30]. The interaction parameter is considered as the Gibbs free energy parameter and such assumption allows dividing the interaction into the enthalpy∞ and the entropy ∞ compoparameter ∞ H 1,2, S nents [31,32]: ∞ ∞ ∞ 1,2 = H + s
(4)
and is related with the solubility parameter by [31]: ∞ ∞ 1,2 = (V1 /RT )(ı1 − ı2 ) + s 2
(5)
where ı1 and ı2 are the solubility parameter of the test solvent and the investigated material, respectively and V1 is the solvent molar volume. The injected test solute is absorbed in the stationary phase (the investigated material). The knowledge of the retention of the test solute, expressed as the specific retention volume, allows to calculate the interaction parameter [32]:
∞ = ln 273.15R/po1 Vg M1 − po1 /RT B11 − V1o − 1 (1,2)i
(6)
where 1 denotes the solute and 2 denotes the examined material, M1 , p01 , B11 , Vg ,V10 are the molecular mass, the saturated vapour pressure of the test solute, the second virial coefficient of the test solute, the specific retention volume of the test solute and the molar volume of the test solute, respectively. Smidsrod and Guillet were the first to apply the inverse gas chromatography to research the interactions between a solvent and a polymer as a stationary phase. The method of determination is based on the rule, that the Flory-Huggins parameter, obtained from the retention data, can be related to the solubility parameter by the Eq. (5). Ito and Guillet [32] proposed to estimate the solubility parameter of polymers, having a set of ∞ and ı1i values for the (1,2)i respective test solutes, by using the equation:
ı21i /RT − ∞ /V1o = (2ı2 /RT )ı1i − ı22 /RT + ∞ s /Vi (1,2)i
(7)
The slope of linear relationship 2ı2 /RT versus ı1i is proportional to the solubility parameter of the examined material, i.e. ı2 [32–37]. The value of ı2 can also be calculated from:
intercept = ı22 /RT + ∞ s /Vi
(8)
assuming ∞ s = 0.2; 0.3 or 0.4 and taking for Vi the smallest molar volume of the test solute. The Guillet procedure was used by Price [38] to determine the solubility parameter for the compounds with small molecular mass. He described the solubility parameter as a sum of two factors arising from the dispersive and the polar interactions between the investigated material and the test solute: ı2T = ı2d + ı2p
(9)
Voelkel and Janas [34] extended the test solute group in order to estimate the three-parameter Hansen equation. The division of the test solutes into groups, corresponding to different types of intermolecular interactions, enables the dispersiveıd , the polar ıp and the hydrogen bonding ıh components of the total solubility parameter value to be obtained, according to the relations: ıd =
mn−alkanes × RT 2
ıp =
(m1 − mn−alkanes ) × RT 2
b) (10)
ıh =
(m2 − mn−alkanes ) × RT 2
c)
a)
where mn−alkanes − the value of the slope for n-alkanes; m1 − the value of the slope for aromatic hydrocarbons, ketones, 1nitropropane; m2 − the value of the slope for alcohols and pyridine. The alternative procedure for estimation the polymers solubility parameter is linked to the assumption, presented by Lindvig et al. [39]. They proposed using the modified Hansen relationship, correlating the experimentally determined values of the Flory-Huggins
Please cite this article in press as: K. Adamska, et al., The solubility parameter for biomedical polymers—Application of inverse gas chromatography, J. Pharm. Biomed. Anal. (2016), http://dx.doi.org/10.1016/j.jpba.2016.04.014
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O O H
n
OH
3
O O
O H
OH CH3
n
n
Fig. 1. The chemical structure of: a) poly(-caprolactone) (PCL), b) polylactide (PLA), c) poly(ethylene glycol) (PEG).
interaction parameter ∞ and the differences, between the HSPs (1,2)i values of the examined material and respective test solutes: 2
2
2
= ␣VRT1 ((␦1,d − ␦2,d ) + 0.25(␦1,p − ␦2,p ) + 0.25(␦1,hb − ␦2,hb ) )(11) where: R − the gas constant; T − temperature of experiment; 1 and 2–the test solute and the examined substance, respectively; ␣ − Lindvig’s coefficient (␣ = 0-1). According to the Lindvig’s assumption, by the finding of the minimum of the function: G2 =
RT 4∞ (1,2)i ˛V1
ε1,d − ε2,d
2
2
+ (␦1,p − ␦2,p ) + (␦1,p − ␦2,p )
2
(12)
and using ∞ data for the test solutes/polymers system, the HSPs (1,2)i parameters of the examined materials can be calculated [40] in Eq. (12) ε1,d = 2ı1,d and it was assumed, that the optimum value of the correction constant ␣ was equal 0.6, which was suggested in Ref. [39]. The solubility parameter data obtained for different polymers can be applied for suitable selection of a solvent or polymers/additives, for polymer or co-polymer matrix in composite biomaterials. 2. Materials and methods The examined polymers were polycaprolactone (Mw = 70.00090.000, PCL), polyethylene glycol (Mw = 10000, PEG), polylactide (PLA). The chemical structure of the examined materials was presented in Fig. 1. The measurements were carried out on iGC SMS (Surface Measurements Systems, London, UK) gas chromatograph, equipped with a flame ionization detector (FID). Methane was used as a noninteracting marker to correct for dead time retention. To prepare the filling of the column (the stationary phase), each polymer was dissolved in a suitable solvent, mixed with the solid support − Chromosorb P AW-DMDCS 100/120 mesh (Supelco) and then the support was covered with polymer by slow evaporation of the solvent. The loading of the stationary phase in a chromatographic column was 20% (w/w). A glass col-
Table 1 The solubility parameter data of the test solutes used [23]. Test solute
Solubility parameter [MPa] 1/2
hexane heptane octane nonane acetonitrile toluene butanone pentan-2-one 1,2-dichloroethane 1-nitropropane ethanol propanol butanol 1,4-dioxane pyridine
14.9 15.3 15.4 15.6 24.8 18.3 19.3 18.4 20.2 21.3 26.1 24.9 28.7 20.7 21.7
umn was used (30 cm length, 2 mm i.d.). After packing, the column was ended by glass wool. The measurements were carried out above polymers melting temperature − for PEG, PCL and PLA at 75 ◦ C. The temperature of injector and detector was equal to 150 ◦ C. Helium was used as a carrier gas with the flow rate 20 ml/min. The test solvents were selected to represent the ability to different types of intermolecular interactions: dispersive − (nalkanes); polar − acetonitrile, toluene, 2-butanone, 2-pentanone, 1,2-dichloroethane,1-nitropropane; hydrogen bonding − ethanol, 1-propanol, 1-butanol, 1,4-dioxane, pyridine. Five injections of the vapour of each solvent were made for each probe and the retention time was determined from the maximum of the symmetric peak. Further calculations lead to the specific retention volume (Vg ), values of which were used in estimation of the physicochemical parameters, as the solubility parameter and its components (HSP). The calculations of the specific retention volume were performed by using SMS iGC Analysis Software v1.2. Optimisation was carried out in two ways:
2 2 OPTA takingintoaccountthedifferences Gexp − Gact
2
(13)
or OPT Btakingintoaccountthedifference
(14)
where Gexp denotes the value of the parameter calculated from the experimental data and Gact value from literature data of Hansen. The criterion of the acceptance of a given solution was the value of the F parameter (the sum of OPT A or the sum of OPT B). 2.1. Results and discussion
Fig. 2. The example of plot of the left hand side of Eq. (7) vs. the solubility parameter of test solutes for PEG.
The values of the solubility parameter differ, according to the calculation procedure (Tables 2–4). One of the methods, used for the solubility parameter estimation was a Guillet and co-workers procedure. The solubility parameter values data were calculated from the slope and the intercept of the Eqs. (7) and (8), respectively. The values of the test solutes solubility parameter ı1 , necessary to determine the polymers solubility parameter, were presented in Table 1. According to the Guillet procedure, the linear relationship with the correlation coefficient of approximately 0.98-0.99 was obtained
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Table 2 The solubility parameter data calculated, according to Guillet procedure, from the slope and the intercept for a different value of the entropy term ∞ s . Polymer
PCL PLA PEG
ı2 (MPa)1/2 from the slope
ı2 (MPa)1/2 from the intercept
∞ s = 0.2
∞ s = 0.3
15.8 ± 0.4 17.9 ± 0.3 20.5 ± 0.5
∞ s = 0.4
17.1 ± 0.2 20.7 ± 0.6 22.3 ± 0.3
16.9 ± 0.2 20.6 ± 0.4 22.2 ± 0.2
16.8 ± 0.3 20.5 ± 0.3 22.0 ± 0.4
Table 3 Hansen solubility parameters (HSP) for polymers, calculated from Eq. (10). Polymer
HSP (MPa)1/2 ıd
PCL PLA PEG
ıp
21.2 ± 0.6 20.0 ± 0.6 20.8 ± 0.6
3.4 ± 0.9 5.9 ± 0.7 8.4 ± 0.7
ıh
ıT
5.2 ± 0.8 7.6 ± 0.9 9.4 ± 0.9
22.1 ± 0.8 22.2 ± 0.7 24.3 ± 0.7
Table 4 Hansen solubility parameters (HSP) for polymers, calculated from Eq. (12). Polymer
PCL PLA PEG
HSP (MPa)1/2 ıd
ıp
ıh
ıT
15.9 19.8 20.3
1.4 4.0 9.6
2.0 6.7 6.0
16.1 22.0 24.0
for all the examined systems. The example of the left hand side of the Eq. (7) vs. the solubility parameter of the test solutes was shown in Fig. 2. ı2 data for polymers obtained from the slope and the intercept were collected in Table 2. To determine ı2 from the intercept, some assumptions were made, considering the factor xs∞ /v1 . According to the literature data, the value of the entropy term may vary in the range 0.2–0.4 [41], 0.3–0.4 or 0.34 [31,41]. In this work, Xs∞ equal to 0.2, 0.3 and 0.4 was applied. The value of Vi taken for calculation should be the smallest among all molecular volumes of the test solutes or examined materials. In this work, acetonitrile fulfills this condition, with Vi = 52.6 cm3 /mol. Comparing ı2 data calculated from the slope and the intercept, it can be found, that the former values are lower. Solubility parameter values calculated for all the materials from the intercept, decreased with an increasing Xs∞ value. The results of HSP calculated according to the Eq. (10) for PCL, PLA and PEG were reported in Table 3. Comparing the results from Table 2 with theıT values in Table 3, it can be observed that the ıT values obtained are higher than the values from the slope and the intercept. Additionally, the differences between the ı2 data for polymers are higher than the respective differences between ıT values. For PCL and PLA almost the same values of ıT were obtained (Table 3). PEG as the most hydrophilic polymer, is characterised by the highest ı2 (20.51 (MPa)1/2 ) or ıT value − (24.34 (MPa)1/2 ). The smallest disparity between ı2 from the slope and ıT was found for PEG, while the highest for PCL. Taking into consideration components of the solubility parameter (Table 3), the differences in ıd , ıp and ıh values for PCL, PLA and PEG are observed. It can be seen that poly(-caprolactone), the most hydrophobic polymer, shows the highest dispersive components value of 21.21(MPa)1/2 . This material has also the weakest tendency to form hydrogen bonding, which is expressed by the smallest ıh value from all the examined polymers. Bordes et al. [42] has published the PCL solubility parameter determined by a group contribution method, swelling experiments and turbidimetric titration. The calculated values depend on the method used. They showed that the value of ıd was in the range 16.1–17.8(MPa)1/2 , ıh in 7.7–9.1(MPa)1/2 , and for
ıp the largest difference between the values (3.3–7.7 (MPa)1/2 ), was obtained depending on the applied method of calculation. For PCL, (Table 3), only the ıp value is consistent with the value calculated by Bordes et al. The polar and the hydrogen bonding components for the hydrophilic PEG are much higher than the values obtained for PCL and PLA (Table 3). The solubility parameter is known as an indicator of hydrophilicity of a material-the higher the ı2 value it indicates, the higher hydrophilicity of the material is. Such observation is confirmed by the data for PEG, i.e. the ı2 value from the slope and from the intercept and as well as the components of HSP and ıT data (Table 3). It is assumed that, if the difference between the values of the solubility parameter of different materials is close to 2 (MPa)1/2 , such materials should interact with each other and exhibit, e.g. suitable mixing properties. Therefore, taking into consideration ıT data obtained (Table 3), it is expected that all examined materials should be miscible. The determination of the solubility parameter components gives more detailed description of the investigated system. The results in Table 3 show that the dispersive component’s values of all the materials are very close, but slight differences are observed for the polar and the hydrogen bonding components. According to this data, it can be assumed, that e.g. PEG addition to the PCL-PLA mixture should influence the hydrogen bonding ability of PCL/PLA/PEG blend and the increase of the hydrophilicity of such system. The results of HSP, obtained according to Eq. (12) (Table 4), showed different values from those presented in Table 3. Here, significantly different values of the dispersive component of HSP were found for PCl, PLA and PEG. The highest ability to the polar interactions was found for PEG, while the ability to the hydrogen bonding is similar for PLA and PEG. The value of the total solubility parameter ıT was the highest for PEG and the lowest for PCL. These values seem to be more realistic than those from Table 3. It should be noted that in the case of using Lindvig’s procedure, all ∞ experimental X(1,2)i data are taken for the calculations, thereby the diversity of the magnitude of interactions is taken into account. The examined materials used as biomaterials are in contact with an aqueous environment of the body fluids. Therefore, such envi-
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K. Adamska et al. / Journal of Pharmaceutical and Biomedical Analysis xxx (2016) xxx–xxx Table 5 |The solubility parameter of blood components [12]. Blood component
Solubility parameter (MPa)1/2
Cholesterol and esters Triglycerides Lipid-soluble vitamins Phospholipids
17.2–17.6 16.4–17.0 17.6–22.3 >32
ronment in living organism can influence the properties of polymer as a result of e.g. absorption of different components of body fluid. Some of the blood components, with their solubility parameter’s data, are presented in Table 5. Additionally, water, which is the main component of the body fluid, may cause a swelling effect for more hydrophilic polymers and, therefore, lead to some changes in their properties. 3. Conclusions The aim of this study was to calculate the solubility parameters of polymers used in biomedical systems, using the inverse gas chromatography technique and different procedures of their calculation. The ı2 data calculated from the slope, according to Guillet and co-workers, are lower than those from the intercept. The Hansen solubility parameter’s data vary depending on the procedure of calculation. They indicate the different ability of the examined polymers to interactions with e.g. components of the body fluid. References [1] C. Carr, The use of solubility parameters in the coatings industry, Eur. Polym. Paint Colour J. 181 (1991) 4278–4281. [2] C.M. Hansen, Solvents for coatings, Chemtech 2 (1972) 547–553. [3] C.M. Hansen, Polymer additives and solubility parameters, Prog. Org. Coat. 51 (2004) 109–112. [4] C.M. Hansen, The three dimensional solubility parameter -key to paint component affinities II, J. Paint Technol. 39 (1967) 505–510. [5] D. Rasmussen, E. Walmström, HSP-solubility parameters; a tool for development of new products-modelling of the solubility of binders in pure and used solvents, Surf. Coat. Int. 77 (1994) 323–333. [6] B.C. Hancock, P. York, R.C. Rowe, The use of solubility parameters in pharmaceutical dosage form design, Int. J. Pharm. 148 (1997) 1–21. [7] K. Adamska, A. Voelkel, K. Héberger, Selection of solubility parameters for characterization of pharmaceutical excipients, J. Chromatogr. A 1171 (2007) 90–97. [8] K. Adamska, R. Bellinghausen, A. Voelkel, New procedure of the determination of Hansen solubility parameters by means of inverse gas chromatography, J. Chromatogr. A 1195 (2008) 146–149. [9] E. Asmussen, E.K. Hansen, A. Peutzfeldt, Influence of the solubility parameter of intermediary resin on the effectiveness of the gluma bonding system, J. Dent Res. 70 (1991) 1290––1293. [10] E. Asmussen, S. Uno, Solubility parameters, fractional polarities, and bond strengths of some intermediary resins used in dentin bonding, J. Dent. Res. 72 (1993) 558–565. [11] R.G. Miller, C.Q. Bowles, C.C. Chappelow, J.D. Eick, Application of solubility parameter theory to dentin-bonding systems and adhesive strength correlations, J. Biomed. Mater. Res. 41 (1998) 237–243. [12] S.D. Bruck, Calcification of glutaraldehyde-treated xenografts and blood-contacting synthetic elastomers, Bioengineering: Proceedings of the Ninth Northeast Conference (1981), Pergamon Press. [13] S.A.A. Ghavimi, M.H. Ebrahimzadeh, M. Solati-Hashjin, N.A.A. Osman, Polycaprolactone/starch composite: fabrication, structure, properties, and applications, J. Biomed. Mater. Res. Part A 103 (2015) 2482––2498. [14] Q. Yao, P. Nooeaid, R. Detsch, J.A. Roether, Y. Dong, O.M. Goudouri, D.W. Schubert, A.R. Boccaccini, Bioglass® /chitosan-polycaprolactone bilayered composite scaffolds intended for osteochondral tissue engineering, J. Biomed. Mater. Res. Part A 102 (2014) 4510–4518. [15] M. Kim, W.K. Jung, G. Kim, Bio-composites composed of a solid free-form fabricated polycaprolactone and alginate-releasing bone morphogenic protein and bone formation peptide for bone tissue regeneration, Bioprocess Biosyst. Eng. 36 (2013) 1725–1734.
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[16] M.A. Jyoti, H.Y. Song, Initial in vitro biocompatibility of a bone cement composite containing a poly--caprolactone microspheres, J. Mater. Sci. Mater. Med. 22 (2011) 1333–1342. [17] Y. Zhang, R.X. Zhuo, Synthesis and in vitro drug release behavior of amphiphilic triblock copolymer nanoparticles based on poly(ethylene glycol) and polycaprolactone, Biomaterials 26 (2005) 6736–6742. [18] J.E. Park, M. Todo, Development and characterization of reinforced poly(l-lactide) scaffolds for bone tissue engineering, J. Mater. Sci. Mater. Med. 22 (2011) 1171–1182. [19] X. Li, L. Liu, P. Yang, P. Li, J. Xin, R. Su, Synthesis of collagen-modified polylactide and its application in drug delivery, J. Appl. Polym. Sci. 129 (2013) 3290–3296. [20] S. Wang, Y. Zhang, G. Yin, H. Wang, Z. Dong, Electrospun polylactide/silk fibroin–gelatin composite tubular scaffolds for small-diameter tissue engineering blood vessels, J. Appl. Polym. Sci. 113 (2009) 2675–2682. [21] M. Bezer, Y. Yildirim, B. Erol, O. Güven, Absorbable self-reinforced polylactide (SR-PLLA) rods vs rigid rods (K-wire) in spinal fusion: an experimental study in rabbits, Eur. Spine J. 14 (2005) 227–233. [22] J.K. Oh, Polylactide (PLA)-based amphiphilic block copolymers: synthesis, self-assembly, and biomedical applications, Soft Matter 7 (2011) 5096–5108. [23] A.F.M. Barton, CRC Handbook of Solubility Parameters and Other Cohesion Parameters, CRC Press, Inc, Boca Raton, Florida, 1983. [24] J.H. Hildebrand, J.M. Prausnitz, R.L. Scott, Regular and Related Solutions, Van Nostrand-Reinhold, New York, 1970. [25] V.N.S. Pendyala, S.F. Xavier, Prediction of a synergistic blend composition range based on polymer-solvent interactions, Polymer 38 (1997) 3565–3572. [26] D.W. van Krevelen, Properties of Polymers, Elsevier, Amsterdam, 1990. [27] C.V.S. Subrahmanyam, K. Prakas Ravi, P. Rao Sundu, Estimation of the solubility parameter of trimethoprim by current methods, Pharm. Acta Helv. 71 (1996) 175–183. [28] M. Terada, R.H. Marchessault, Determination of solubility parameters for poly(3-hydroxyalkanoates), Int. J. Biol. Macrom. 25 (1999) 207–215. [29] P. Sakellariou, R.C. Rowe, E.F.T. White, The solubility parameters of some cellulose derivatives and polyethylene glycols used in tablet film coating, Int. J. Pharm. 31 (1986) 175–177. [30] G. DiPaola-Baranyi, J.E. Guillet, Estimation of polymer solubility parameters by gas chromatography, Macromolecules 11 (1978) 228–235. [31] R.F. Blanks, J.M. Prausnitz, Thermodynamics of polymer solubility in polar and nonpolar systems, Ind. Eng. Chem. Fundam. 3 (1964) 1–8. [32] K. Ito, J.E. Guillet, Estimation of solubility parameters for some olefin polymers and copolymers by inverse gas chromatography, Macromolecules 12 (1979) 1163–1167. [33] A. Voelkel, Inverse gas chromatography. Solubility parameters of 1,3-bis[-hexoxy-oligo(oxyethylene)]-propan-2-ols, Acta Chromatogr. 1 (1992) 69–80. [34] A. Voelkel, J. Janas, Inverse gas chromatographic determination of solubility parameter and binary parameters of ␣,-diamino oligoethers, J. Chromatogr. A 669 (1994) 89–95. [35] W. Wasiak, A. Voelkel, I. Rykowska, Physico-chemical characterization of chemically bonded stationary phases including metal complexes by inverse gas chromatography, J. Chromatogr. A 690 (1995) 83–91. [36] P. Choi, T. Kavassalis, A. Rudin, Measurement of three-dimensional solubility parameters of nonyl phenol ethoxylates using inverse gas chromatography, J. Coll. Int. Sci. 180 (1996) 1–8. [37] K. Adamska, A. Voelkel, Inverse gas chromatographic determination of solubility parameters of excipients, Int. J. Pharm. 304 (2005) 11–17. [38] G.J. Price, Calculation of Solubility Parameters by Inverse Gas Chromatography, in: D.R. Lloyd, T.C. Ward, H.P. Schreiber (Eds.), American Chemical Society, Washington, DC, 1989, p. 48. [39] T. Lindvig, M.L. Michelsen, G.M. Kontogeorgis, A Flory–Huggins model based on the Hansen solubility parameters, Fluid Phase Equilibr. 203 (2002) 247–260. [40] K. Adamska, R. Bellinghausen, A. Voelkel, New procedure for the determination of Hansen solubility parameters by means of inverse gas chromatography, J. Chromatogr. A 1195 (2008) 146–149. [41] G.M. Bristow, W.F. Watson, Cohesive energy densities of polymers Part 1—Cohesive energy densities of rubbers by swelling measurements, Trans. Farad. Soc. 54 (1958) 1731–1741. [42] C. Bordes, V. Fréville, E. Ruffin, P. Marote, J.Y. Gauvrit, S. Brianc, P. Lantéri, Determination of poly(-caprolactone)solubility parameters: application to solvents substitution in a microencapsulation process, Int. J. Pharm. 383 (2010) 236–243.
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The solubility parameter for biomedical polymers—Application of inverse gas chromatography ´ K. Adamska ∗ , A. Voelkel, A. Berlinska Pozna´ n University of Technology, Institute of Chemical Technology and Engineering, ul. Berdychowo 4, 60-965 Pozna´ n, Poland
a r t i c l e
i n f o
Article history: Received 4 December 2015 Received in revised form 26 February 2016 Accepted 14 April 2016 Available online xxx Keywords: Solubility parameters Inverse gas chromatography Biomedical polymers
a b s t r a c t The solubility parameter seems to be a useful tool for thermodynamic characterisation of different materials. The solubility parameter concept can be used to predict sufficient miscibility or solubility between a solvent and a polymer, as well as components of co-polymer matrix in composite biomaterials. The values of solubility parameter were determined for polycaprolactone (PCL), polylactic acid (PLA) and polyethylene glycol (PEG) by using different procedures and experimental data, collected by means of inverse gas chromatography. © 2016 Elsevier B.V. All rights reserved.
1. Introduction In the design and preparation of various compositions or formulations, consisting of different components, the characteristics of these components, described by various physicochemical parameters, are important. The application of the solubility parameter in the description of the behaviour of materials in real systems is presented including such phenomena as: miscibility, adhesion and wetting. Hence, the suitable knowledge about mutual miscibility, solubility or compatibility between different materials is desirable. Understanding and quantification of interactions between the components of the system is very often a key problem. This allows to assess the suitability of compounds for established applications. One potential solution is to set the cohesive energy of the components, or more precisely, solubility parameter. This parameter is used for the estimation of the properties of an unknown material and the assessment of the interaction between different materials. The solubility parameter found an application for the prediction and correlation the cohesive and adhesive properties between different materials. It can be used in coatings industry for proper solvent selection in polymer/additives system [1,2] for characterisation of different additives (plasticisers, antistatic agents) used in polymers [3] matching a binder to pigment [4] in printing industry for selection of the best cleaning agent for binders [5].
∗ Corresponding author. E-mail address: [email protected] (K. Adamska).
Different polymers are currently investigated and used in biomedical field. Due to the unique properties of some polymers, such as e.g. biocompatibility or biofuncionality, their importance is constantly increasing.The solubility parameter concept can be used in all aspects of pharmaceutical dosage form design [6], for proper excipients selection [7,8] to predict the effectiveness of adhesives in dentine bonding systems and the ability of the resin to soften or solubilise the dentine surface [9–11], i.e. in characterisation of the materials applied in biological or biomedical systems. Moreover, the solubility parameter is one of the factors, which might be used to describe the penetration and absorption of various blood components into polymers, used as biomaterials [12]. It can be also applied to predict sufficient miscibility/solubility between solvent and polymer or components of co-polymer matrix in composite biomaterials. The aim of this work was to estimate the solubility parameter data for polymers used as biomaterials: polycaprolactone, polylactic acid and polyethylene glycol. Polycaprolactone (PCL) is a semicrystalline, biocompatible, resorbable polymer, which found an application in biomedical field [13]. It is used as a component of composites in tissue engineering as a polymer for blood vessel and cartilage scaffolds [14], bone tissue regeneration [13–16], drug delivery systems [17] and others. Polylactic acid (PLA), due to its unique features of biodegradability, biocompatibility, thermoplastic processability and eco-friendliness, is the most common synthetic polymer used in medical applications, for scaffold preparation [18], in drug delivery systems [19], vascular grafts [20], implants for a bone fixation [21] etc. Poly(ethylene glycol) (PEG) is a commonly applied nonionic, hydrophilic polymer. The attach-
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ment of PEG chains has been employed as an effective method of choice in the development of biocompatible materials for many biological and biomedical applications [22]. The solubility parameter term is related to the cohesive energy density (CED), which indicates the energy of vaporisation per unit volume.
ı = (CED)1/2 = H − RT/Vm
1/2
= E/Vm
1/2
(1)
where: ı- solubility parameter, R − gas constant, T − temperature, H − enthalpy of vaporisation, Vm − molar volume, E − free energy of vaporisation. The concept of the solubility parameter was proposed by Scatchard, Hildebrand and Scott and initially applied to systems, cohesion of which arises only from the dispersion forces. The solubility parameter, defined by Eq. (1) is called Hildebrand solubility parameter or Hildebrand parameter [23]. Its extension to system, where the cohesive energy can be considered as a sum of contributions from the dispersive (Ed ), the polar (Ep ) and the hydrogen bonding (Eh ) was introduced by Hansen [2,3]: −Ecoh = −Ed − Ep − Eh
(2)
The so-called Hansen solubility parameter (HSP) is expressed as: ı2T = ı2d + ı2p + ı2h
(3)
where: ıT ,ıd , ıp , ıh denotes the total, the dispersive, the polar and the hydrogen bonding contribution, respectively. The solubility parameter for volatile substances can be calculated from the energy of evaporation [24], by using Eq. (1), but this method gives only a total solubility parameter not Hansen solubility parameters. For low- or non-volatile compounds different methods were drawn up, e.g. solubility of a material in different solvents or a polymer swelling in different solvents, with known solubility parameters value. It is assumed, that the solubility parameter of the investigated material is approximately the same as the solubility parameter of the solvent, which dissolves this material or mixes with it at all proportions, without a change of volume and enthalpy [25]. A similar method is the measurement of the polymer swelling in solvents with known solubility parameter value, taken from literature [26]. Different group contribution methods, e.g. the Hoftyzer and Van Krevelen method can be applied to calculate the solubility parameter, knowing the chemical structure of a material [26–29]. It is assumed, that two materials, having close values of the solubility parameter are likely to be compatible and should be miscible, when mixed together. In this work, inverse gas chromatography was applied for the determination of the solubility parameter for polymers used in biomedical applications. Inverse gas chromatography (IGC) is known as an effective technique to measure different physicochemical parameters and it allows to calculate the solubility parameter, for a wide range of low- or non-volatile materials in a large range of temperatures. In the IGC technique, an investigated material (a stationary phase) is placed in the chromatographic column, and its properties are deduced from behaviour of injected, volatile probes (test solutes), transported by a mobile phase. As a result of an interaction between the test solutes and the stationary phase, the retention data obtained are used to calculate the Flory) and furtherly the solubility Huggins interaction parameter (∞ 1,2 parameter (␦2 ) [30]. The interaction parameter is considered as the Gibbs free energy parameter and such assumption allows dividing the interaction into the enthalpy∞ and the entropy ∞ compoparameter ∞ H 1,2, S nents [31,32]: ∞ ∞ ∞ 1,2 = H + s
(4)
and is related with the solubility parameter by [31]: ∞ ∞ 1,2 = (V1 /RT )(ı1 − ı2 ) + s 2
(5)
where ı1 and ı2 are the solubility parameter of the test solvent and the investigated material, respectively and V1 is the solvent molar volume. The injected test solute is absorbed in the stationary phase (the investigated material). The knowledge of the retention of the test solute, expressed as the specific retention volume, allows to calculate the interaction parameter [32]:
∞ = ln 273.15R/po1 Vg M1 − po1 /RT B11 − V1o − 1 (1,2)i
(6)
where 1 denotes the solute and 2 denotes the examined material, M1 , p01 , B11 , Vg ,V10 are the molecular mass, the saturated vapour pressure of the test solute, the second virial coefficient of the test solute, the specific retention volume of the test solute and the molar volume of the test solute, respectively. Smidsrod and Guillet were the first to apply the inverse gas chromatography to research the interactions between a solvent and a polymer as a stationary phase. The method of determination is based on the rule, that the Flory-Huggins parameter, obtained from the retention data, can be related to the solubility parameter by the Eq. (5). Ito and Guillet [32] proposed to estimate the solubility parameter of polymers, having a set of ∞ and ı1i values for the (1,2)i respective test solutes, by using the equation:
ı21i /RT − ∞ /V1o = (2ı2 /RT )ı1i − ı22 /RT + ∞ s /Vi (1,2)i
(7)
The slope of linear relationship 2ı2 /RT versus ı1i is proportional to the solubility parameter of the examined material, i.e. ı2 [32–37]. The value of ı2 can also be calculated from:
intercept = ı22 /RT + ∞ s /Vi
(8)
assuming ∞ s = 0.2; 0.3 or 0.4 and taking for Vi the smallest molar volume of the test solute. The Guillet procedure was used by Price [38] to determine the solubility parameter for the compounds with small molecular mass. He described the solubility parameter as a sum of two factors arising from the dispersive and the polar interactions between the investigated material and the test solute: ı2T = ı2d + ı2p
(9)
Voelkel and Janas [34] extended the test solute group in order to estimate the three-parameter Hansen equation. The division of the test solutes into groups, corresponding to different types of intermolecular interactions, enables the dispersiveıd , the polar ıp and the hydrogen bonding ıh components of the total solubility parameter value to be obtained, according to the relations: ıd =
mn−alkanes × RT 2
ıp =
(m1 − mn−alkanes ) × RT 2
b) (10)
ıh =
(m2 − mn−alkanes ) × RT 2
c)
a)
where mn−alkanes − the value of the slope for n-alkanes; m1 − the value of the slope for aromatic hydrocarbons, ketones, 1nitropropane; m2 − the value of the slope for alcohols and pyridine. The alternative procedure for estimation the polymers solubility parameter is linked to the assumption, presented by Lindvig et al. [39]. They proposed using the modified Hansen relationship, correlating the experimentally determined values of the Flory-Huggins
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O O H
n
OH
3
O O
O H
OH CH3
n
n
Fig. 1. The chemical structure of: a) poly(-caprolactone) (PCL), b) polylactide (PLA), c) poly(ethylene glycol) (PEG).
interaction parameter ∞ and the differences, between the HSPs (1,2)i values of the examined material and respective test solutes: 2
2
2
= ␣VRT1 ((␦1,d − ␦2,d ) + 0.25(␦1,p − ␦2,p ) + 0.25(␦1,hb − ␦2,hb ) )(11) where: R − the gas constant; T − temperature of experiment; 1 and 2–the test solute and the examined substance, respectively; ␣ − Lindvig’s coefficient (␣ = 0-1). According to the Lindvig’s assumption, by the finding of the minimum of the function: G2 =
RT 4∞ (1,2)i ˛V1
ε1,d − ε2,d
2
2
+ (␦1,p − ␦2,p ) + (␦1,p − ␦2,p )
2
(12)
and using ∞ data for the test solutes/polymers system, the HSPs (1,2)i parameters of the examined materials can be calculated [40] in Eq. (12) ε1,d = 2ı1,d and it was assumed, that the optimum value of the correction constant ␣ was equal 0.6, which was suggested in Ref. [39]. The solubility parameter data obtained for different polymers can be applied for suitable selection of a solvent or polymers/additives, for polymer or co-polymer matrix in composite biomaterials. 2. Materials and methods The examined polymers were polycaprolactone (Mw = 70.00090.000, PCL), polyethylene glycol (Mw = 10000, PEG), polylactide (PLA). The chemical structure of the examined materials was presented in Fig. 1. The measurements were carried out on iGC SMS (Surface Measurements Systems, London, UK) gas chromatograph, equipped with a flame ionization detector (FID). Methane was used as a noninteracting marker to correct for dead time retention. To prepare the filling of the column (the stationary phase), each polymer was dissolved in a suitable solvent, mixed with the solid support − Chromosorb P AW-DMDCS 100/120 mesh (Supelco) and then the support was covered with polymer by slow evaporation of the solvent. The loading of the stationary phase in a chromatographic column was 20% (w/w). A glass col-
Table 1 The solubility parameter data of the test solutes used [23]. Test solute
Solubility parameter [MPa] 1/2
hexane heptane octane nonane acetonitrile toluene butanone pentan-2-one 1,2-dichloroethane 1-nitropropane ethanol propanol butanol 1,4-dioxane pyridine
14.9 15.3 15.4 15.6 24.8 18.3 19.3 18.4 20.2 21.3 26.1 24.9 28.7 20.7 21.7
umn was used (30 cm length, 2 mm i.d.). After packing, the column was ended by glass wool. The measurements were carried out above polymers melting temperature − for PEG, PCL and PLA at 75 ◦ C. The temperature of injector and detector was equal to 150 ◦ C. Helium was used as a carrier gas with the flow rate 20 ml/min. The test solvents were selected to represent the ability to different types of intermolecular interactions: dispersive − (nalkanes); polar − acetonitrile, toluene, 2-butanone, 2-pentanone, 1,2-dichloroethane,1-nitropropane; hydrogen bonding − ethanol, 1-propanol, 1-butanol, 1,4-dioxane, pyridine. Five injections of the vapour of each solvent were made for each probe and the retention time was determined from the maximum of the symmetric peak. Further calculations lead to the specific retention volume (Vg ), values of which were used in estimation of the physicochemical parameters, as the solubility parameter and its components (HSP). The calculations of the specific retention volume were performed by using SMS iGC Analysis Software v1.2. Optimisation was carried out in two ways:
2 2 OPTA takingintoaccountthedifferences Gexp − Gact
2
(13)
or OPT Btakingintoaccountthedifference
(14)
where Gexp denotes the value of the parameter calculated from the experimental data and Gact value from literature data of Hansen. The criterion of the acceptance of a given solution was the value of the F parameter (the sum of OPT A or the sum of OPT B). 2.1. Results and discussion
Fig. 2. The example of plot of the left hand side of Eq. (7) vs. the solubility parameter of test solutes for PEG.
The values of the solubility parameter differ, according to the calculation procedure (Tables 2–4). One of the methods, used for the solubility parameter estimation was a Guillet and co-workers procedure. The solubility parameter values data were calculated from the slope and the intercept of the Eqs. (7) and (8), respectively. The values of the test solutes solubility parameter ı1 , necessary to determine the polymers solubility parameter, were presented in Table 1. According to the Guillet procedure, the linear relationship with the correlation coefficient of approximately 0.98-0.99 was obtained
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Table 2 The solubility parameter data calculated, according to Guillet procedure, from the slope and the intercept for a different value of the entropy term ∞ s . Polymer
PCL PLA PEG
ı2 (MPa)1/2 from the slope
ı2 (MPa)1/2 from the intercept
∞ s = 0.2
∞ s = 0.3
15.8 ± 0.4 17.9 ± 0.3 20.5 ± 0.5
∞ s = 0.4
17.1 ± 0.2 20.7 ± 0.6 22.3 ± 0.3
16.9 ± 0.2 20.6 ± 0.4 22.2 ± 0.2
16.8 ± 0.3 20.5 ± 0.3 22.0 ± 0.4
Table 3 Hansen solubility parameters (HSP) for polymers, calculated from Eq. (10). Polymer
HSP (MPa)1/2 ıd
PCL PLA PEG
ıp
21.2 ± 0.6 20.0 ± 0.6 20.8 ± 0.6
3.4 ± 0.9 5.9 ± 0.7 8.4 ± 0.7
ıh
ıT
5.2 ± 0.8 7.6 ± 0.9 9.4 ± 0.9
22.1 ± 0.8 22.2 ± 0.7 24.3 ± 0.7
Table 4 Hansen solubility parameters (HSP) for polymers, calculated from Eq. (12). Polymer
PCL PLA PEG
HSP (MPa)1/2 ıd
ıp
ıh
ıT
15.9 19.8 20.3
1.4 4.0 9.6
2.0 6.7 6.0
16.1 22.0 24.0
for all the examined systems. The example of the left hand side of the Eq. (7) vs. the solubility parameter of the test solutes was shown in Fig. 2. ı2 data for polymers obtained from the slope and the intercept were collected in Table 2. To determine ı2 from the intercept, some assumptions were made, considering the factor xs∞ /v1 . According to the literature data, the value of the entropy term may vary in the range 0.2–0.4 [41], 0.3–0.4 or 0.34 [31,41]. In this work, Xs∞ equal to 0.2, 0.3 and 0.4 was applied. The value of Vi taken for calculation should be the smallest among all molecular volumes of the test solutes or examined materials. In this work, acetonitrile fulfills this condition, with Vi = 52.6 cm3 /mol. Comparing ı2 data calculated from the slope and the intercept, it can be found, that the former values are lower. Solubility parameter values calculated for all the materials from the intercept, decreased with an increasing Xs∞ value. The results of HSP calculated according to the Eq. (10) for PCL, PLA and PEG were reported in Table 3. Comparing the results from Table 2 with theıT values in Table 3, it can be observed that the ıT values obtained are higher than the values from the slope and the intercept. Additionally, the differences between the ı2 data for polymers are higher than the respective differences between ıT values. For PCL and PLA almost the same values of ıT were obtained (Table 3). PEG as the most hydrophilic polymer, is characterised by the highest ı2 (20.51 (MPa)1/2 ) or ıT value − (24.34 (MPa)1/2 ). The smallest disparity between ı2 from the slope and ıT was found for PEG, while the highest for PCL. Taking into consideration components of the solubility parameter (Table 3), the differences in ıd , ıp and ıh values for PCL, PLA and PEG are observed. It can be seen that poly(-caprolactone), the most hydrophobic polymer, shows the highest dispersive components value of 21.21(MPa)1/2 . This material has also the weakest tendency to form hydrogen bonding, which is expressed by the smallest ıh value from all the examined polymers. Bordes et al. [42] has published the PCL solubility parameter determined by a group contribution method, swelling experiments and turbidimetric titration. The calculated values depend on the method used. They showed that the value of ıd was in the range 16.1–17.8(MPa)1/2 , ıh in 7.7–9.1(MPa)1/2 , and for
ıp the largest difference between the values (3.3–7.7 (MPa)1/2 ), was obtained depending on the applied method of calculation. For PCL, (Table 3), only the ıp value is consistent with the value calculated by Bordes et al. The polar and the hydrogen bonding components for the hydrophilic PEG are much higher than the values obtained for PCL and PLA (Table 3). The solubility parameter is known as an indicator of hydrophilicity of a material-the higher the ı2 value it indicates, the higher hydrophilicity of the material is. Such observation is confirmed by the data for PEG, i.e. the ı2 value from the slope and from the intercept and as well as the components of HSP and ıT data (Table 3). It is assumed that, if the difference between the values of the solubility parameter of different materials is close to 2 (MPa)1/2 , such materials should interact with each other and exhibit, e.g. suitable mixing properties. Therefore, taking into consideration ıT data obtained (Table 3), it is expected that all examined materials should be miscible. The determination of the solubility parameter components gives more detailed description of the investigated system. The results in Table 3 show that the dispersive component’s values of all the materials are very close, but slight differences are observed for the polar and the hydrogen bonding components. According to this data, it can be assumed, that e.g. PEG addition to the PCL-PLA mixture should influence the hydrogen bonding ability of PCL/PLA/PEG blend and the increase of the hydrophilicity of such system. The results of HSP, obtained according to Eq. (12) (Table 4), showed different values from those presented in Table 3. Here, significantly different values of the dispersive component of HSP were found for PCl, PLA and PEG. The highest ability to the polar interactions was found for PEG, while the ability to the hydrogen bonding is similar for PLA and PEG. The value of the total solubility parameter ıT was the highest for PEG and the lowest for PCL. These values seem to be more realistic than those from Table 3. It should be noted that in the case of using Lindvig’s procedure, all ∞ experimental X(1,2)i data are taken for the calculations, thereby the diversity of the magnitude of interactions is taken into account. The examined materials used as biomaterials are in contact with an aqueous environment of the body fluids. Therefore, such envi-
Please cite this article in press as: K. Adamska, et al., The solubility parameter for biomedical polymers—Application of inverse gas chromatography, J. Pharm. Biomed. Anal. (2016), http://dx.doi.org/10.1016/j.jpba.2016.04.014
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K. Adamska et al. / Journal of Pharmaceutical and Biomedical Analysis xxx (2016) xxx–xxx Table 5 |The solubility parameter of blood components [12]. Blood component
Solubility parameter (MPa)1/2
Cholesterol and esters Triglycerides Lipid-soluble vitamins Phospholipids
17.2–17.6 16.4–17.0 17.6–22.3 >32
ronment in living organism can influence the properties of polymer as a result of e.g. absorption of different components of body fluid. Some of the blood components, with their solubility parameter’s data, are presented in Table 5. Additionally, water, which is the main component of the body fluid, may cause a swelling effect for more hydrophilic polymers and, therefore, lead to some changes in their properties. 3. Conclusions The aim of this study was to calculate the solubility parameters of polymers used in biomedical systems, using the inverse gas chromatography technique and different procedures of their calculation. The ı2 data calculated from the slope, according to Guillet and co-workers, are lower than those from the intercept. The Hansen solubility parameter’s data vary depending on the procedure of calculation. They indicate the different ability of the examined polymers to interactions with e.g. components of the body fluid. References [1] C. Carr, The use of solubility parameters in the coatings industry, Eur. Polym. Paint Colour J. 181 (1991) 4278–4281. [2] C.M. Hansen, Solvents for coatings, Chemtech 2 (1972) 547–553. [3] C.M. Hansen, Polymer additives and solubility parameters, Prog. Org. Coat. 51 (2004) 109–112. [4] C.M. Hansen, The three dimensional solubility parameter -key to paint component affinities II, J. Paint Technol. 39 (1967) 505–510. [5] D. Rasmussen, E. Walmström, HSP-solubility parameters; a tool for development of new products-modelling of the solubility of binders in pure and used solvents, Surf. Coat. Int. 77 (1994) 323–333. [6] B.C. Hancock, P. York, R.C. Rowe, The use of solubility parameters in pharmaceutical dosage form design, Int. J. Pharm. 148 (1997) 1–21. [7] K. Adamska, A. Voelkel, K. Héberger, Selection of solubility parameters for characterization of pharmaceutical excipients, J. Chromatogr. A 1171 (2007) 90–97. [8] K. Adamska, R. Bellinghausen, A. Voelkel, New procedure of the determination of Hansen solubility parameters by means of inverse gas chromatography, J. Chromatogr. A 1195 (2008) 146–149. [9] E. Asmussen, E.K. Hansen, A. Peutzfeldt, Influence of the solubility parameter of intermediary resin on the effectiveness of the gluma bonding system, J. Dent Res. 70 (1991) 1290––1293. [10] E. Asmussen, S. Uno, Solubility parameters, fractional polarities, and bond strengths of some intermediary resins used in dentin bonding, J. Dent. Res. 72 (1993) 558–565. [11] R.G. Miller, C.Q. Bowles, C.C. Chappelow, J.D. Eick, Application of solubility parameter theory to dentin-bonding systems and adhesive strength correlations, J. Biomed. Mater. Res. 41 (1998) 237–243. [12] S.D. Bruck, Calcification of glutaraldehyde-treated xenografts and blood-contacting synthetic elastomers, Bioengineering: Proceedings of the Ninth Northeast Conference (1981), Pergamon Press. [13] S.A.A. Ghavimi, M.H. Ebrahimzadeh, M. Solati-Hashjin, N.A.A. Osman, Polycaprolactone/starch composite: fabrication, structure, properties, and applications, J. Biomed. Mater. Res. Part A 103 (2015) 2482––2498. [14] Q. Yao, P. Nooeaid, R. Detsch, J.A. Roether, Y. Dong, O.M. Goudouri, D.W. Schubert, A.R. Boccaccini, Bioglass® /chitosan-polycaprolactone bilayered composite scaffolds intended for osteochondral tissue engineering, J. Biomed. Mater. Res. Part A 102 (2014) 4510–4518. [15] M. Kim, W.K. Jung, G. Kim, Bio-composites composed of a solid free-form fabricated polycaprolactone and alginate-releasing bone morphogenic protein and bone formation peptide for bone tissue regeneration, Bioprocess Biosyst. Eng. 36 (2013) 1725–1734.
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