Owing to bio-polymer's low-cost, environmental friendliness and mechanically stable nature, calcium alginate microcapsules have attracted much interest for their applications in numerous fields. Among the common production methods, the Electrospraying technique has shown a great potential due to smaller shape capsule production and ease of control of independent affecting parameters. Although one factor at a time (OFAT) can predict the trends of parameter effect on size and sphericity, it is inefficient in explaining the complex parameter interaction of the electrospray process. In the current study, the effects of the main parameters affecting on size and sphericity of the microcapsules using OFAT were optimized to attain calcium alginate microcapsules with an average diameter below 100 µm. Furthermore, we propose a statistical model employing the Surface Responses Methodology (RSM) and Central Composite Design (CDD) to generate a quadratic order linear regression model for the microcapsule diameter and sphericity coefficient. Experimentally, microcapsules with a size of 92.586 µm and sphericity coefficient of 0.771 were predicted and obtained from an alginate concentration of 2.013 /, with a flowrate of 0.560 mL/h, a needle size of 27 G and a 2.024 / calcium chloride concentration as optimum parameters. The optimization processes were successfully aligned towards formation of the spherical microcapsules with smaller average diameter of less than 100 µm, owing to the applied high voltage that reached up to 21 kV.
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http://dx.doi.org/10.3390/polym14040709 | DOI Listing |
Alzheimers Dement
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Department of Textile Engineering, Istanbul Technical University, Istanbul, Turkey. Electronic address:
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December 2024
Laboratório de Entomologia e Fitopatologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Campos dos Goytacazes, Rio de Janeiro, 28013-602, Brazil.
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Department of Biology, Faculty of Science, Farhangian University, Tehran, Iran.
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Molecular Nutrition Branch, National Engineering Research Center of Rice and By-product Deep Processing/College of Food Science and Engineering, Central South University of Forestry and Technology, Changsha, Hunan 410004, China. Electronic address:
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