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

需要可持续地供应清洁能源和有机化学原料，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。生物质是一种很有前途的可再生替代/补充化石资源的运输燃料，化学产品和可生物降解材料。为了从化学上复杂的生物质流中提取最大比例的有用生物化学组分，主要生物质组分（包括纤维素、半纤维素和木质素）的有效分离（分级）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大量的不可再生化学品、能量和资本，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一种基于深共熔溶剂（由固体成分产生的非挥发性液体混合物）的绿色生物质分馏过程。这种独特的方法将使用不引入非生物衍生加工剂的工艺生产生物质衍生化学产品。教育和推广计划将整合本研究产生的技术知识，以增加未来可持续化学制造方法技术领导者的数量和多样性为目标。生物质衍生溶剂有可能在开发可持续生物精炼操作中发挥关键作用。生物质衍生的深共熔溶剂（DES）的性能进行了研究，使用一系列的实验和计算方法，但是，这些研究，已经检查了有限数量的DES组合，并没有研究的机制和动力学的反应过程中，生物质的DES的转换。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确定其物理化学和热性质中起主要作用。拟议的研究计划将（a）通过实验和计算方法对一系列HBD和HBA结构上DES形成的机理进行理解，（B）通过实验表征和基于机器学习的建模的综合计划确定DES组合物与溶剂化、热传递和溶剂的流变性质之间的相关性，以及（c）阐明生物质衍生DES与生物质模型组分和天然生物质的反应机理和动力学。DES的形成机制将与不同的HBA和HBD对生物质衍生的成分进行研究，并通过核磁共振（NMR）来阐明。合成DES的特性将通过差示扫描量热法、流变仪和离子电导率测量进行分析。这些实验结果将被用来开发一个预测模型的DES的属性，通过训练人工神经网络（ANN）模型和验证其预测。DES与生物质的化学相互作用也将在合成的模型化合物和真实的生物质的反应动力学研究中使用密度泛函理论（DFT）计算进行研究。这些发现不仅将推进生物质衍生DES分馏特性的科学知识，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，将创建一个生物精炼的跨学科课程，以培养下一代生物精炼技术的工程师和科学家。该研究团队计划通过每年的夏季研讨会，包括混合讲座和动手实验，以提高参与者对可持续生物炼制操作的理解，从而与高中生建立联系。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值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.