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Selection of optimum ionic liquid solvents for flavonoid and phenolic acids extraction

机译:精选黄酮和酚酸萃取的最佳离子液体溶剂

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Phytochemicals are important in improving human health with their functions as antioxidants, antimicrobials and anticancer agents. However, the quality of phytochemicals extract relies on the efficiency of extraction process. Ionic liquids (ILs) have become a research phenomenal as extraction solvent due to their unique properties such as unlimited range of ILs, non-volatile, strongly solvating and may become either polarity. In phytochemical extraction, the determination of the best solvent that can extract highest yield of solute (phytochemical) is very important. Therefore, this study is conducted to determine the best IL solvent to extract flavonoids and phenolic acids through a property prediction modeling approach. ILs were selected from the imidazolium-based anion for alkyl chains ranging from ethyl >octyl and cations consisting of Br, Cl, [PF6], BF4], [H2PO4], [SO4], [CF3SO3], [TF2N] and [HSO4]. This work are divided into several stages. In Stage 1, a Microsoft Excel-based database containing available solubility parameter values of phytochemicals and ILs including its prediction models and their parameters has been established. The database also includes available solubility data of phytochemicals in IL, and activity coefficient models, for solid-liquid phase equilibrium (SLE) calculations. In Stage 2, the solubility parameter values of the flavonoids (e.g. kaempferol, quercetin and myricetin) and phenolic acids (e.g. gallic acid and caffeic acid) are determined either directly from database or predicted using Stefanis and Marrero-Gani group contribution model for the phytochemicals. A cation-anion contribution model is used for IL. In Stage 3, the amount of phytochemicals extracted can be determined by using SLE relationship involving UNIFAC-IL model. For missing parameters (UNIFAC-IL), they are regressed using available solubility data. Finally, in Stage 4, the solvent candidates are ranked and five ILs, ([OMIM] [TF2N], [HeMIM] [TF2N], [HMIM] [TF2N], [HeMIM] [CF3SO3] and [HMIM] [CF3SO3]) were identified and selected.
机译:植物化学物质在改善人类健康方面对其作为抗氧化剂,抗微生物和抗癌剂的功能很重要。然而,植物化学品提取物的质量依赖于提取过程的效率。离子液体(ILS)由于其独特的性质如无限范围的IL,非挥发性,强烈溶解并且可能成为极性而导致的离子液体(ILS)成为萃取溶剂的研究现象。在植物化学萃取中,确定可以提取最高产率的溶质(植物化学)的最佳溶剂非常重要。因此,进行该研究以确定通过性质预测建模方法提取黄酮类化合物和酚酸的最佳溶剂。从基于咪唑鎓的阴离子中选择ILS,用于由乙基链条的烷基链和由Br,Cl,[PF6],BF4],[H2PO4],[SO4],[CF 3 SO 3],[TF2N]和[HSO4的阳离子]。这项工作分为几个阶段。在第1阶段,已经建立了包含基于Microsoft Excel的数据库,其包含植物化学和ILS的可用溶解度参数值,包括其预测模型及其参数。该数据库还包括IL的植物化学物质的可用溶解性数据和活性系数模型,用于固液相平衡(SLE)计算。在第2阶段,类黄酮(例如Kaempferol,槲皮素和霉菌素)和酚醛酸(例如,无碱酸和咖啡酸)的溶解度参数值直接从数据库中确定,或使用氏植物和植物化学的乳酸和摩尔加甘氏群贡献模型来预测。阳离子阴离子贡献模型用于IL。在第3阶段,提取的植物化学物质的量可以通过使用涉及Unifac-IL模型的SLE关系来确定。对于缺少参数(UNIFAC-IL),它们使用可用的溶解度数据回归。最后,在第4阶段,溶剂候选物被排序,5个ILS,([OMIM] [TF2N],[HMIM] [TF2N],[HMIM] [CF3SO3]和[HMIM] [CF3SO3] )被鉴定并选择。

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