Mechanism-Informed Computational Entrainer Selection and Process Design for Biomolecule Extraction from Primary-Concentrated Microalgae in Subcritical Dimethyl Ether Systems

Efficient extraction of biomolecules from high-moisture microalgae is constrained by the polarity mismatch between solvents and water. This study introduces a COSMO-RS-assisted computational–experimental framework for entrainer screening and mechanistic elucidation in subcritical dimethyl ether (DME)–water systems. A database of 1982 solvents was sequentially filtered by melting/boiling points, environmental, health, and safety (EHS) criteria, and COSMO-RS-predicted solubilities, followed by ternary-miscibility evaluation and targeted experiments. The integrated results reveal that extraction efficiency is primarily governed by ternary miscibility, with class-specific entrainers optimizing recovery across lipids, proteins, carbohydrates, and pigments. Excess-enthalpy (HE) decomposition identifies hydrogen bonding as the principal favorable contribution, opposed by electrostatic misfit. Electrostatic potential (ESP), independent gradient model based on Hirshfeld partition (IGMH), and interaction region indicator (IRI) analyses clarify how selected entrainers increase DME–water miscibility and enhance solvation of representative biomolecules. The framework offers predictive guidance for designing efficient, selective, and environmentally sustainable extraction processes for wet biomass valorization.从高水分微藻中高效提取生物分子的过程，常受限于溶剂与水之间的极性失配。本研究提出了一种基于COSMO-RS（Conductor-like Screening Model for Real Solvents）的计算-实验一体化框架，用于亚临界二甲醚(DME)-水体系中夹带剂的筛选与作用机制阐释。研究团队首先通过熔点/沸点、环境-健康-安全(EHS)准则以及COSMO-RS预测的溶解度，对包含1982种溶剂的数据库进行逐级筛选，随后开展三元混溶性评估与靶向实验。整合分析结果表明，提取效率主要受三元混溶性调控，类别特异性夹带剂可优化脂质、蛋白质、碳水化合物与色素的回收效果。过量焓(HE)分解分析显示，氢键是主要的有利贡献因素，而静电失配则起到相反的不利作用。静电势(ESP)、基于Hirshfeld划分的独立梯度模型(IGMH)以及相互作用区域指示器(IRI)分析，阐明了所选夹带剂提升二甲醚-水混溶性并增强代表性生物分子溶剂化作用的具体机制。该框架可为设计高效、高选择性且环境友好的湿生物质资源化提取工艺提供预测性指导。