CAREER: Understanding of Biomass-derived Deep Eutectic Solvents for Sustainable Biorefinery Strategies

对清洁能源和有机化学品原料的可持续供应的需要，加上目前的制造方法对地球气候的负面影响，构成了世界人口面临的一些最紧迫的问题。生物质是交通燃料、化工产品和可生物降解材料等化石资源的一种很有前途的可再生替代/补充。为了从化学复杂的生物质流中最大限度地提取有用的生化成分，有效地分离(分馏)主要的生物质成分，包括纤维素、半纤维素和木质素，是必不可少的。不幸的是，目前能够进行这种分馏过程的生物精炼技术消耗了大量的不可再生化学品、能源和资本，限制了生物质利用的经济可行性和可持续性。在这个项目中，研究小组将寻求一种全新的方法来生产绿色生物质分馏过程，该过程基于从生物质本身提取的深度共熔溶剂(从否则为固体的成分中产生的非挥发性液体混合物)。这种独特的方法将使用一种不引入非生物衍生加工剂的工艺来生产生物质衍生化学产品。教育和推广计划将整合这项研究产生的技术知识，目标是增加未来可持续化学制造方法的技术领导者的数量和多样性。生物质衍生溶剂有可能在发展可持续生物精炼作业中发挥关键作用。生物质衍生的深共晶溶剂(DES)的性质已经用一系列的实验和计算方法进行了研究；然而，这些研究只考察了有限数量的DES组合，而没有研究控制生物质转化为DES的反应过程的机理和动力学。DES中氢键供体(HBD)和氢键受体(HBA)物种之间的分子间氢键在溶剂的形成和决定其物理化学性质和热性质中起着主要作用。拟议的研究计划将(A)通过实验和计算方法从机理上理解一系列HBD和HBA结构上DES的形成，(B)通过一套综合的实验表征和基于机器学习的建模程序来确定DES组成与溶剂的溶剂化、热传递和流变性之间的关系，以及(C)阐明生物质衍生的DES与生物质模型组分和天然生物量的反应机理和动力学。DES的形成机理将通过不同的HBA和HBD对从生物质衍生成分中进行研究，并通过核磁共振(NMR)加以阐明。通过差示扫描量热法、流变仪和离子电导率测量对合成的DES的特性进行了分析。这些实验结果将被用来通过训练人工神经网络(ANN)模型并验证其预测来开发DES性能的预测模型。在合成的模型化合物和实际生物质的反应动力学研究中，还将利用密度泛函理论(DFT)计算DES与生物质的化学相互作用。这些发现不仅将促进对生物质衍生DES分馏性质的科学知识，而且还可以扩展到更广泛的可持续、生态友好和可调的工业溶剂，用于生物精炼过程。根据拟议的研究，将创建生物精炼的跨学科课程，以培训下一代生物精炼技术的工程师和科学家。研究团队计划通过一年一度的夏季研讨会接触高中生，该研讨会由混合讲座和动手实验组成，以增强参与者对可持续生物精炼操作的理解。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The need for sustainable supplies of clean energy and organic chemical feedstocks, together with the negative impact on the Earth’s climate by current manufacturing methods, constitute some of the most pressing problems faced by the world’s population. Biomass is a promising renewable alternative / supplement to fossil-based resources for transportation fuels, chemical products, and biodegradable materials. To extract the maximum fraction of useful biochemical components from chemically complicated biomass streams, effective separation (fractionation) of the major biomass components, including cellulose, hemicelluloses, and lignin, is essential. Unfortunately, current biorefinery technologies capable of carrying out this fractionation process consume significant amounts of non-renewable chemicals, energy, and capital, limiting the economic feasibility and sustainability of biomass utilization. In this program, the research team will pursue a completely new approach to producing a green biomass fractionation process based on deep eutectic solvents (non-volatile liquid mixtures produced from components that are otherwise solid) derived from the biomass itself. This unique approach will produce biomass-derived chemical products using a process that does not introduce non-bioderived processing agents. Education and outreach programs will integrate technical knowledge generated by this research with the goal of increasing the number and diversity of future technical leaders in sustainable chemical manufacturing methods.Biomass-derived solvents have the potential to play a key role in developing sustainable biorefining operations. The properties of biomass-derived deep eutectic solvents (DES) have been investigated using a range of experimental and computational methods; these studies, however, have examined a limited number of DES combinations and have not studied the mechanisms and kinetics of the reaction processes governing the conversion of biomass to DES. Intermolecular hydrogen bonding between the hydrogen bond donor (HBD) and hydrogen bond acceptor (HBA) species in a DES plays a primary role in the formation of the solvent and determining its physicochemical and thermal properties. The proposed research program will (a) pursue a mechanistic understanding of DES formation over a range of HBD and HBA structures by experimental and computational methods, (b) determine correlations between DES composition and the solvation, thermal transport, and rheological properties of the solvent by a comprehensive program of experimental characterization and machine learning-based modeling, and (c) elucidate the reaction mechanisms and kinetics of biomass-derived DES with biomass model components and natural biomass. The formation mechanism of DES will be investigated with diverse HBA and HBD pairs from biomass-derivable components and elucidated by nuclear magnetic resonance (NMR). The characteristics of the synthesized DES will be analyzed by differential scanning calorimetry, rheometry, and ion conductivity measurements. These experimental results will be used to develop a prediction model for the properties of DES by training an artificial neural network (ANN) model and validating its predictions. The chemical interactions of DES with biomass also will be investigated in reaction kinetic studies of the synthesized model compounds and real biomass using density functional theory (DFT) calculations. These findings will not only advance scientific knowledge in the fractionation properties of biomass-derived DES but also can be expanded to a wider range of sustainable, eco-friendly, and tunable industrial solvents for biorefining processes. Informed by the proposed research, an interdisciplinary curriculum for biorefining will be created to train the next generation of engineers and scientists in biorefining technologies. The research team plans to reach out to high school students through an annual summer workshop consisting of hybrid lectures and hands-on experiments to enhance participants’ understanding of sustainable biorefinery operations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.