氢键重构及协同溶剂化作用下的生物质定向拆解调控机制

The cellulose material with high purity is usually obtained by degrading hemicellulose and lignin in the existing biomass fractionation process for nanocellulose preparation, and nanocellulose can be prepared with the subsequent nano-fibrillation. Functionalized ionic liquids with the hydrogen bonding-reconstitution effect are used as catalysts in polyhydric alcohol, water and other solvents. Directional biomass fractionation and nano-fibrillation of cellulose are conducted in functionalized ionic liquids and solvent system with the hydrogen bonding-reconstitution effect of ionic liquids and the synergistic salvation of both of them. The effects of reactive conditions, removal rates of hemicellulose and lignin, and cellulose hydrolysis rate on cellulose dimension are investigated. Prediction model is built with artificial neural network to optimize and control directional biomass fractionation to realize nano-fibrillation of cellulose. Facile nanocellulose preparation is hopefully achieved with nanofibrillated cellulose material obtained in the process, and the resulting hemicellulose and lignin are potentially used for biorefinery, which can decrease the energy consumption and improve the biomass component utilization. Biomass fractionation and nanocellulose preparation are combined in this project to provide high-quality raw materials for biorefinery while preparing high-performance materials with biomass, and it can be a theoretical reference to the efficient and comprehensive utilization of biomass.

为制备纳米纤维素而分离生物质组分时，多以降解半纤维素和木质素的方式来获得高纯度的纤维素，经纳米纤丝化后制得纳米纤维素。针对该过程中生物质组分利用率低、纳米纤丝化能耗高等问题，本项目以氢键重构型功能化离子液体为催化剂，以多元醇、水等为溶剂，在氢键重构作用以及离子液体/溶剂体系的协同溶剂化作用下定向拆解纤维素组分实现其纳米纤丝化并有效分离半纤维素和木质素。研究反应条件、半纤维素及木质素脱除率、纤维素水解率等因素对纤维素尺度变化的影响机制，建立人工神经网络预测模型优化调控生物质定向拆解过程以实现纤维素纳米纤丝化，简化纳米纤维素制备工艺并降低制备能耗；同时通过与预处理相结合有效分离各组分，获得可用于生物精炼的半纤维素和木质素，实现生物质原料的全组分利用。本项目将生物质分离过程和纳米纤维素制备过程相结合，在以生物质制备高性能材料的同时为生物精炼提供优质原料，将为生物质综合高效利用提供理论参考。

针对纳米纤维素制备工艺复杂、能耗较高等问题，本项目通过将生物质组分分离与纤维素纳米化相结合的方式，定向拆解纤维素氢键网络制备纳米纤维素，并解析其定向拆解调控机制。优选了有机溶剂和功能化离子液体作为溶剂和催化剂对生物质原料进行组分分离处理，考察了溶剂体系、催化剂、助剂、处理条件、预处理等因素对生物质组分分离效率的影响，研究了生物质组分分离过程中组分去向与降解产物特征，利用人工神经网络模型预测并优化了生物质组分分离过程；基于功能化离子液体部分溶解/溶胀作用定向拆解纤维素原料，通过优化功能化离子液体浓度、处理条件等因素，调控纤维素定向拆解程度，实现了高木质素含量的纤维素原料的有效拆解和纳米纤维素的高得率制备。同时，综合分析各因素对生物质组分分离与纤维素纳米化的影响规律，解析了生物质定向拆解调控机制。相关研究有利于降低纳米纤维素制备的复杂性，拓展纳米纤维素的应用，提高生物质原料的全组分利用效率，并将为进一步优化生物质组分分离和纳米纤维素制备提供理论指导。