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Phase behavior of gelatin/maltodextrin aqueous mixtures studied from a combined experimental and theoretical approach
Fluid Phase Equilibria ( IF 2.8 ) Pub Date : 2020-12-01 , DOI: 10.1016/j.fluid.2020.112675
Fabrizio Masullo , Yoran Beldengrün , Jonathan Miras , Allan D. Mackie , Jordi Esquena , Josep Bonet Avalos

Abstract A combined experimental and theoretical study of the phase behavior of mixtures of gelatin and maltodextrin is presented. This system, at neutral pH and 50∘C, exhibits coexistence of three equilibrium phases: two liquid phases and a third, which is a solid-like precipitate that resembles a coacervate. This phase behavior completely changes at lower pH, where only two phases remain. Flory-Huggins solution theory is used to model the observed phase behavior. The optimal fits of the associated Flory-Huggins mixing parameters are obtained using a novel non-linear regression method based on neural networks. The neural network was trained using as input only the number of phases present, without knowledge of the specific compositions of the coexisting phases. The optimal Flory-Huggins parameters result in phase diagrams which are consistent with our experimental data. A comparison with the experimental results indicates that the method can produce relevant fits of the model parameters in situations where the information is limited. Moreover, the formation of the solid-like precipitate can be explained within the standard Flory-Huggins framework, despite the fact that important local and specific interactions or induced structural changes occur in the system to produce such a precipitate. In conclusion, the model obtained for this system allows a straightforward exploration, prior to the experimental validation, of the appropriate conditions for future practical applications of this system.

中文翻译:

从实验和理论相结合的方法研究明胶/麦芽糊精水性混合物的相行为

摘要 对明胶和麦芽糊精混合物的相行为进行了实验和理论联合研究。该系统在中性 pH 值和 50∘C 下表现出三个平衡相的共存:两个液相和第三个,它是类似于凝聚层的固体状沉淀物。这种相行为在较低的 pH 值下完全改变,此时只剩下两相。Flory-Huggins 解理论用于模拟观察到的相行为。使用基于神经网络的新型非线性回归方法获得相关 Flory-Huggins 混合参数的最佳拟合。神经网络仅使用存在的相数作为输入进行训练,而不知道共存相的具体组成。最佳 Flory-Huggins 参数产生与我们的实验数据一致的相图。与实验结果的比较表明,该方法可以在信息有限的情况下产生模型参数的相关拟合。此外,固体状沉淀物的形成可以在标准的 Flory-Huggins 框架内解释,尽管重要的局部和特定相互作用或诱导结构变化发生在系统中以产生这种沉淀物。总之,为该系统获得的模型允许在实验验证之前直接探索该系统未来实际应用的适当条件。与实验结果的比较表明,该方法可以在信息有限的情况下产生模型参数的相关拟合。此外,固体状沉淀物的形成可以在标准的 Flory-Huggins 框架内解释,尽管重要的局部和特定相互作用或诱导结构变化发生在系统中以产生这种沉淀物。总之,为该系统获得的模型允许在实验验证之前直接探索该系统未来实际应用的适当条件。与实验结果的比较表明,该方法可以在信息有限的情况下产生模型参数的相关拟合。此外,固体状沉淀物的形成可以在标准的 Flory-Huggins 框架内解释,尽管重要的局部和特定相互作用或诱导结构变化发生在系统中以产生这种沉淀物。总之,为该系统获得的模型允许在实验验证之前直接探索该系统未来实际应用的适当条件。尽管在系统中发生了重要的局部和特定相互作用或诱发的结构变化以产生这种沉淀物。总之,为该系统获得的模型允许在实验验证之前直接探索该系统未来实际应用的适当条件。尽管在系统中发生了重要的局部和特定相互作用或诱发的结构变化以产生这种沉淀物。总之,为该系统获得的模型允许在实验验证之前直接探索该系统未来实际应用的适当条件。
更新日期:2020-12-01
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