Wu Yan, Zhang Hang, Li Meng-Shan, Sheng Sheng, Wang Jun, Wu Fu-An
School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of China.
School of Mathematics and Computer Science, Gannan Normal University, Ganzhou Jiangxi 341000, People's Republic of China.
R Soc Open Sci. 2022 Jan 19;9(1):211419. doi: 10.1098/rsos.211419. eCollection 2022 Jan.
Solubility of gas in polymers is an important physico-chemical property of foam materials and widely used in the preparation and modification of new materials. Under the conditions of high temperature and high pressure, the dissolution process is a nonlinear, non-equilibrium and dynamic process, so it is difficult to establish an accurate solubility calculation model. Inspired by particle dynamics and evolutionary algorithm, this paper proposes a hybrid model based on chaotic self-adaptive particle dynamics evolutionary algorithm (CSA-PD-EA), which can use the iterative process of particles in evolutionary algorithms at the dynamic level to simulate the mutual diffusion process of molecules during dissolution. The predicted solubility of supercritical CO in poly(d,l-lactide--glycolide), poly(l-lactide) and poly(vinyl acetate) indicated that the comprehensive prediction performance of the CSA-PD-EA model was high. The calculation error and correlation coefficient were, respectively, 0.3842 and 0.9187. The CSA-PD-EA model showed prominent advantages in accuracy, efficiency and correlation over other computational models, and its calculation time was 4.144-15.012% of that of other dynamic models. The CSA-PD-EA model has wide application prospects in the computation of physical and chemical properties and can provide the basis for the theoretical calculation of multi-scale complex systems in chemistry, materials, biology and physics.
气体在聚合物中的溶解度是泡沫材料一项重要的物理化学性质，在新材料的制备与改性中有着广泛应用。在高温高压条件下，溶解过程是一个非线性、非平衡的动态过程，因此难以建立精确的溶解度计算模型。受粒子动力学和进化算法启发，本文提出一种基于混沌自适应粒子动力学进化算法（CSA-PD-EA）的混合模型，该模型能够在动态层面利用进化算法中粒子的迭代过程来模拟溶解过程中分子的相互扩散过程。对超临界CO在聚（d，l-丙交酯-乙交酯）、聚（l-丙交酯）和聚醋酸乙烯酯中的溶解度预测表明，CSA-PD-EA模型具有较高的综合预测性能。计算误差和相关系数分别为0.3842和0.9187。与其他计算模型相比，CSA-PD-EA模型在准确性、效率和相关性方面表现出突出优势，其计算时间为其他动态模型的4.144%-15.012%。CSA-PD-EA模型在物理化学性质计算方面具有广阔的应用前景，可为化学、材料、生物和物理等领域多尺度复杂系统的理论计算提供依据。
