Mixtures of water and organic cosolvents (mixed solvent systems) play an important role in mediating acid-catalyzed biomass conversion reactions. A minimum amount of water is typically required to dissolve biomass-derived materials, while adding an organic cosolvent can enhance the rates and selectivities of the desirable, catalytic reaction steps. Understanding the molecular-level bases underlying these solvent effects would provide a powerful measure of control over the reaction environment for biomass conversion processes, whereby the rates of desired reaction steps could be preferentially enhanced over the undesirable ones by modulating the composition of the solvent system. However, a quantitative basis to anticipate these solvent effects is currently lacking, and optimizing the composition of the liquid phase for new biomass conversion reactions typically requires laborious screening of the continuous space of possible mixed solvent systems. Herein, we summarize our efforts to estimate solvent effects on the rates and selectivities of liquid-phase, acid-catalyzed biomass conversions reactions using experiments, classical molecular dynamics simulations, and machine learning tools. We then synthesize these insights into a workflow that allows for the rational design of mixed solvent systems for acid-catalyzed biomass conversion processes using computationally efficient methods and minimal experiments. We demonstrate this design framework by analyzing two case studies: the acid-catalyzed dehydration of cyclohexanol to cyclohexene, and the partial dehydration of fructose to 5-hydroxymethylfurfural.

水和有机助溶剂（混合溶剂系统）的混合物在介导酸催化的生物质转化反应中起重要作用。通常需要最小量的水来溶解生物质衍生的材料，而添加有机助溶剂可以提高所需的催化反应步骤的速率和选择性。了解这些溶剂作用背后的分子水平基础将为控制生物质转化过程的反应环境提供有力的措施，通过调节溶剂系统的组成，可以比不希望的反应步骤优先提高所需反应步骤的速率。但是，目前尚缺乏用于预测这些溶剂作用的定量依据，为新的生物质转化反应优化液相的组成通常需要费力地筛选可能的混合溶剂系统的连续空间。在这里，我们总结了我们的工作，以使用实验，经典分子动力学模拟和机器学习工具来估算溶剂对液相，酸催化的生物质转化反应的速率和选择性的影响。然后，我们将这些见解综合到一个工作流程中，该工作流程允许使用计算有效的方法和最少的实验为酸催化的生物质转化过程合理设计混合溶剂系统。我们通过分析两个案例研究来证明此设计框架：酸催化的环己醇脱水成环己烯，以及果糖部分脱水成5-羟甲基糠醛。