A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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The Royal Society
2022-01-01
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| Series: | Royal Society Open Science |
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| Online Access: | https://royalsocietypublishing.org/doi/10.1098/rsos.211419 |
| _version_ | 1797837678384775168 |
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| author | Yan Wu Hang Zhang Meng-shan Li Sheng Sheng Jun Wang Fu-an Wu |
| author_facet | Yan Wu Hang Zhang Meng-shan Li Sheng Sheng Jun Wang Fu-an Wu |
| author_sort | Yan Wu |
| collection | DOAJ |
| description | 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 CO2 in poly(d,l-lactide-co-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. |
| first_indexed | 2024-04-09T15:28:34Z |
| format | Article |
| id | doaj.art-f262b74386934057b9811375504adbb2 |
| institution | Directory Open Access Journal |
| issn | 2054-5703 |
| language | English |
| last_indexed | 2024-04-09T15:28:34Z |
| publishDate | 2022-01-01 |
| publisher | The Royal Society |
| record_format | Article |
| series | Royal Society Open Science |
| spelling | doaj.art-f262b74386934057b9811375504adbb22023-04-28T11:04:05ZengThe Royal SocietyRoyal Society Open Science2054-57032022-01-019110.1098/rsos.211419A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymersYan Wu0Hang Zhang1Meng-shan Li2Sheng Sheng3Jun Wang4Fu-an Wu5School of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of ChinaCollege of Physics and Electronic Information, Gannan Normal University, Ganzhou Jiangxi 341000, People's Republic of ChinaCollege of Physics and Electronic Information, Gannan Normal University, Ganzhou Jiangxi 341000, People's Republic of ChinaSchool of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of ChinaSchool of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of ChinaSchool of Biotechnology, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212018, People's Republic of ChinaSolubility 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 CO2 in poly(d,l-lactide-co-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.https://royalsocietypublishing.org/doi/10.1098/rsos.211419dissolution behaviourevolutionary computationparticle dynamicscomputational model |
| spellingShingle | Yan Wu Hang Zhang Meng-shan Li Sheng Sheng Jun Wang Fu-an Wu A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers Royal Society Open Science dissolution behaviour evolutionary computation particle dynamics computational model |
| title | A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers |
| title_full | A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers |
| title_fullStr | A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers |
| title_full_unstemmed | A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers |
| title_short | A double-population chaotic self-adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers |
| title_sort | double population chaotic self adaptive evolutionary dynamics model for the prediction of supercritical carbon dioxide solubility in polymers |
| topic | dissolution behaviour evolutionary computation particle dynamics computational model |
| url | https://royalsocietypublishing.org/doi/10.1098/rsos.211419 |
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