Influence of the Processes Parameters on the Properties of The ...

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Chapter 5. Characterization <strong>of</strong> Scaffolds for Connective Tissue Engineering Crystallization, crystallinity degree, and <strong>the</strong>rmal properties <strong>of</strong> P L LA depend on <strong>the</strong> polymer molecular weight, polymerization conditions, <strong>the</strong>rmal history, purity, and so on. As reported by Ikada et al. [1987], blending <strong>of</strong> P L LA and P D LA results in <strong>the</strong> formation <strong>of</strong> a stereo-complex with a crystalline structure different from that <strong>of</strong> each homopolymer and melting temperatures that reach 230 o C. Contradictory data are reported about P L LA melting enthalpy, ranging in <strong>the</strong> literature from 40 to 203 J/g. To calculate <strong>the</strong> degree <strong>of</strong> crystallinity, we have used <strong>the</strong> most common value adopted for <strong>the</strong> melting enthalpy <strong>of</strong> <strong>the</strong> totally crystallised P L LA, [Auras et al., 2010]. c % = 100 (ΔH m - ΔH c )/93.6 Poly(lactic acid) (PLA) is a glassy, high modulus <strong>the</strong>rmoplastic polymer with properties comparable to polystyrene (PS). The mechanical properties <strong>of</strong> <strong>the</strong> polylactides depends upon <strong>the</strong> manufacturing method, <strong>the</strong> crystalinity factor, <strong>the</strong> T g and ratio <strong>of</strong> L-lactide, D-lactide or racemic D,L-lactide contents. In case <strong>of</strong> poly(lactic -co-glycolic) acid <strong>the</strong> properties are intermediate between those <strong>of</strong> poly lactic acid and polyglycolic acid. There is increase in <strong>the</strong> mechanical properties but a decrease in <strong>the</strong> T g due to <strong>the</strong> addition <strong>of</strong> PGA structure. 2 Kinematics and Thermodynamics Experiments The aim <strong>of</strong> <strong>the</strong> sorption-desorption studies was to be able to consider <strong>the</strong> foaming phenomenon more precisely. Thus, in this part, we have realized experiments to achieve <strong>the</strong> sorption kinetics by using <strong>the</strong> desorption data. As we have mentioned earlier, <strong>the</strong> sorption behaviour <strong>of</strong> CO 2 into <strong>the</strong> polymer determines <strong>the</strong> number <strong>of</strong> nuclei generated and it deserves a proper investigation. We have also investigated <strong>the</strong> desorption phenomenon which has influence both on <strong>the</strong> pore growth and <strong>the</strong> final structure <strong>of</strong> <strong>the</strong> polymer. 2.1 Sorption-Diffusion Kinetics The aim to plot kinetic curves was to determine <strong>the</strong> time <strong>of</strong> saturation <strong>of</strong> <strong>the</strong> polymer by CO 2 . To obtain kinetic curves, experiments <strong>of</strong> 10, 20, 60, 120 and 240 minutes have been performed. As shown in Figure 5.6-(A), <strong>the</strong> sorption curve is reaching to a plateau after 60 minutes <strong>of</strong> processing which means that <strong>the</strong> polymer can be considered to be quiet saturated by CO 2 after 60 minutes at 125 bars and 36.5°C. In Figure 5.6-(B), M t denotes <strong>the</strong> weight <strong>of</strong> CO 2 inside <strong>the</strong> polymer at time t, and M ∞ is <strong>the</strong> maximum sorbed amount <strong>of</strong> CO 2 . Here, all M t values are <strong>the</strong> extrapolated data (to t = 0) <strong>of</strong> <strong>the</strong> initial linear parts <strong>of</strong> <strong>the</strong> desorption curves as presented in Chapter 3, section 4. Each M t value is analyzed after different experiments. M ∞ has been taken as <strong>the</strong> value <strong>of</strong> 240 minutes, where <strong>the</strong> equilibrium is supposed to be completely reached. The sorption behaviour is modelled using one dimensional diffusion equation from a plane sheet (Eq.2,2), chapter 2. The Minerr function <strong>of</strong> Mathcad has been used to optimize <strong>the</strong> modelling and to calculate <strong>the</strong> average sorption-diffusion coefficient. Thus, <strong>the</strong> sorption diffusion coefficient was found as 3.64 × 10 -10 m 2 s -1 for P sat = 125 bars, T sat = 36.5°C and t sat = 120 min. Indeed, <strong>the</strong> capacity <strong>of</strong> sorption <strong>of</strong> CO 2 , thus <strong>the</strong> diffusion coefficient must increase with <strong>the</strong> increasing amount <strong>of</strong> CO 2 solubilized in <strong>the</strong> polymer, but to simplify <strong>the</strong> calculations, we have considered an average sorption-diffusion coefficient all across <strong>the</strong> time interval. Mathcad programs for diffusion are presented in Annex A-2. The <strong>the</strong> model is in very good agreement with experimental data as show in Figure 5.6-(A). - 120 -
Chapter 5. Characterization <strong>of</strong> Scaffolds for Connective Tissue Engineering 0,1800 Weight variation <strong>of</strong> PLGA50:50 (g) 0,1780 0,1760 0,1740 0,1720 0,1700 0,1680 0,1660 (A) 0,1640 0,00 10,00 20,00 30,00 √t (√s) (B) Figure 5.6: (A)-Kinetics and modelling <strong>of</strong> <strong>the</strong> sorption <strong>of</strong> CO 2 in PLGA 50:50 at 125 bar and 36.5°C, (B) Desorption <strong>of</strong> CO 2 from PLGA 50:50 <strong>of</strong> CO 2 in PLGA 50:50 at 125 bars and 36.5°C. 2.2 Desorption-Diffusion Kinetics Desorption kinetics <strong>of</strong> CO 2 from PLGA 50:50 have been studied in order to analyze <strong>the</strong> amount <strong>of</strong> CO 2 sorbed, but also to provide diffusion data with different saturation times and pressures. We must remember that <strong>the</strong> M t values used in desorption studies are different from <strong>the</strong> ones in sorption kinetics. In desorption kinetics, during <strong>the</strong> decrease <strong>of</strong> CO 2 weight, M t denotes <strong>the</strong> quantity <strong>of</strong> CO 2 present in <strong>the</strong> polymer at time t, and it has been analyzed by <strong>the</strong> desorption method described previously. Only <strong>the</strong> M ∞ value is found by <strong>the</strong> extrapolation <strong>of</strong> <strong>the</strong> initial parts <strong>of</strong> desorption curve. On <strong>the</strong> o<strong>the</strong>r hand, <strong>the</strong> desorptiondiffusion coefficients are calculated using Fickian diffusion from a plane sheet. Figure 5.7 presents desorption data as M t /M ∞ which is plotted against <strong>the</strong> √t/a 2 after processed with different saturation pressures, 100 and 200 bars. Here, <strong>the</strong> factor “a” is corresponding to <strong>the</strong> semithickness <strong>of</strong> <strong>the</strong> polymer pellet and t = 0 s is <strong>the</strong> end <strong>of</strong> <strong>the</strong> saturation period. It is obvious that <strong>the</strong> desorption shows a linear behaviour until approximately 65% <strong>of</strong> <strong>the</strong> total amount <strong>of</strong> CO 2 sorbed. After that value, <strong>the</strong> experimental data diverges from <strong>the</strong> Fickian model. In <strong>the</strong> literature, this kind <strong>of</strong> behaviour is generally attributed to <strong>the</strong> vitrification <strong>of</strong> <strong>the</strong> polymer and <strong>the</strong> non-Fickian diffusion behaviour <strong>of</strong> <strong>the</strong> CO 2 from glassy polymers. This divergence is greater for <strong>the</strong> values <strong>of</strong> 100 bars than for <strong>the</strong> values <strong>of</strong> 200 bars. Additionally, <strong>the</strong> M t /M ∞ value <strong>of</strong> <strong>the</strong> desorption curve from 200 bars is smaller than <strong>of</strong> <strong>the</strong> 100 bars all across <strong>the</strong> time scale. Thus, <strong>the</strong> Fickian model <strong>of</strong> diffusion has been applied for <strong>the</strong> regions <strong>of</strong> divergence. The model plotted (cf. Figure 5.7) is in a very good agreement with <strong>the</strong> experimental data. This behaviour can be explained by <strong>the</strong> double Fickian diffusion. When <strong>the</strong> polymer changes its state from rubbery to glassy, <strong>the</strong> diffusion coefficient changes but <strong>the</strong> behaviour <strong>of</strong> diffusion is assumed Fickian. As <strong>of</strong> this moment, we consider that <strong>the</strong> intersection <strong>of</strong> <strong>the</strong> extrapolation <strong>of</strong> <strong>the</strong> second curve with <strong>the</strong> initial curve gives <strong>the</strong> vitrification point <strong>of</strong> <strong>the</strong> polymer. This point reflects <strong>the</strong> glass transition temperature <strong>of</strong> <strong>the</strong> polymer as <strong>the</strong> drop <strong>of</strong> <strong>the</strong> temperature and <strong>the</strong> desorption curve <strong>of</strong> CO 2 . At 100 bars and 200 bars, we have 0.35 and 0.19 for <strong>the</strong> M t /M ∞ , respectively. These data correspond, to <strong>the</strong> weight fraction <strong>of</strong> CO 2 in PLGA 50:50 <strong>of</strong> 0.082 and 0.057, respectively. Hence, <strong>the</strong> corresponding vitrification time is 2.72 s and 2.64 s for 100 bars and 200 bars, respectively. So, we have used <strong>the</strong> data and <strong>the</strong> model shown in Figure 5.7, to calculate <strong>the</strong> diffusion coefficients. - 121 -
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Institut National Polytechnique de
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pleased I was to work with all memb
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Publications and Conferences The wo
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Nomenclature and Abbreviations Abbr
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ρ p Pellet density Splitting (Bra
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Chapter 2 .........................
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