Data from: Membrane-assisted extraction of monoterpenes: From in-silico solvent screening towards biotechnological process application

This work focuses on the process development of membrane-assisted solvent extraction of hydrophobic compounds such as monoterpenes. Beginning with the choice of suitable solvents, quantum chemical calculations with the simulation tool COSMO-RS were carried out to predict the partition coefficient (logP) of (S)-(+)-carvone and terpinen-4-ol in various solvent-water systems and validated afterwards with experimental data. COSMO-RS results show good prediction accuracy for nonpolar solvents like n-hexane, ethyl acetate and n-heptane even in the presence of salts and glycerol in aqueous medium. Based on the high logP value, n-heptane was chosen for the extraction of (S)-(+)-carvone in a lab-scale hollow-fiber membrane contactor. Two operation modes are investigated where experimental and theoretical mass transfer values, based on their related partition coefficients were compared. In addition, the process is evaluated in terms of extraction efficiency and overall product recovery, and its biotechnological application potential discussed. Our work demonstrates that the combination of in-silico prediction by COSMO-RS with membrane-assisted extraction is a promising approach for the recovery of hydrophobic compounds from aqueous solutions.本研究聚焦于单萜类等疏水性化合物的膜辅助溶剂萃取工艺开发。首先通过筛选适配溶剂，借助模拟工具COSMO-RS开展量子化学计算，预测(S)-(+)-香芹酮与萜品烯-4-醇在多种溶剂-水体系中的分配系数（partition coefficient，logP），并通过实验数据对预测结果进行验证。COSMO-RS的预测结果显示，即便水介质中存在盐类与甘油，其对正己烷、乙酸乙酯、正庚烷等非极性溶剂的分配系数预测精度仍较为优异。基于较高的logP值，正庚烷被选为实验室规模中空纤维膜接触器中萃取(S)-(+)-香芹酮的溶剂。本研究考察了两种操作模式，并基于对应的分配系数对比了实验与理论传质数值。此外，本研究从萃取效率与总产品回收率维度对该工艺进行了评估，并探讨了其在生物技术领域的应用潜力。本研究表明，将COSMO-RS的虚拟预测与膜辅助萃取相结合，是从水溶液中回收疏水性化合物的极具前景的技术路径。