FMSG: Eco: Electrocatalytic Production of Valuable Polymer Feedstocks from Biomass-derived Furanics and CO2

FMSG：Eco：利用生物质衍生的呋喃和二氧化碳电催化生产有价值的聚合物原料

• 批准号: 2328176
• 负责人: Yujie Sun
• 金额: $ 50万
• 依托单位: University of Cincinnati Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2328176&HistoricalAwards=false
• 关键词: FMSG; Eco; Electrocatalytic; Production; Valuable

Among biomass-derived intermediate compounds, furanics stand out as particularly appealing targets in that they exhibit great promise for chemical transformation to a variety of value-added end products including the important biopolymer precursor 2,5-furandicarboxylic acid (FDCA). Although several thermochemical synthetic strategies of FDCA from furfural or 2-furoic acid have been reported, the requirements of stoichiometric oxidants, expensive catalysts, toxic solvents/reagents, and/or potentially harsh conditions render these synthetic strategies non-optimal for the large-scale manufacturing of FDCA. This project, led by Yujie Sun (University of Cincinnati) in collaboration with Arun Mannodi Kanakkithodi (Purdue University), aims to develop an innovative electrochemical process, namely electrocatalytic bromine-mediated carboxylation (EBrC), to produce FDCA from 2-furoic acid and carbon dioxide under ambient conditions. Since carbon dioxide is directly utilized in this process as a C1 feedstock for the final carboxylation step, the proposed EBrC strategy for FDCA production is essentially carbon-negative with potential environmental and societal benefits. Data-driven screening of reaction conditions using computation and machine learning will help guide the design and development of competent electrocatalytic systems.The overall objective of this seed grant is to develop an electrocatalytic approach for the synthesis of an important biopolymer precursor, namely 2,5-furandicarboxylic acid (FDCA), using biomass-derived and industrially produced furfural and carbon dioxide, and also build the talent pool of future research scientists in the emerging field of organic electrocatalysis. The generated data, simulation frameworks, and tools for training models and predicting properties will be publicly released in a Findable, Accessible, Interoperable, Reusable (FAIR) format for the benefit of the materials community, via the Materials Data Facility and nanoHUB, an online repository housed at Purdue University which provides free and open access to this information for educators and students. The PI’s (Sun) group at the University of Cincinnati (UC) will build on its active involvement in outreach programs including the UC Community Day Open House, the UC-Chem Summer Camp, and Science Day at the UC Center for Field Studies. The co-PI’s (Mannodi Kanakkithodi) group at Purdue University will develop new nanoHUB resources based on the density functional theory calculations and machine learning results from the project. These resources will be used for education and outreach, including incorporation into graduate courses at Purdue University and as content for hands-on workshops on materials informatics organized on behalf of nanoHUB, which is typically attended by 100 to 300 students and researchers from across the world.This Future Manufacturing award was supported by funding from the Division of Chemistry in the Directorate for Mathematical and Physical Sciences.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.

在生物质衍生的中级化合物中，Furanics脱颖而出，特别有吸引力的靶标，因为它们对化学转化向各种增值最终产物（包括重要的生物聚合物前体2,5-富甲基苯甲酸（FDCA））揭示了巨大的希望。尽管已经报道了FDCA的几种热化学合成策略，但已经报道了化学计量氧化物，昂贵的催化剂，有毒溶液/试剂/试剂和/或潜在的危害条件的要求，使这些合成策略对FDCA大型生产变得不太优惠。该项目由辛辛那提大学Yujie Sun（Purdue University）与Arun Mannodi Kanakkithodi（Purdue University）合作，旨在开发创新的电化学过程，即电催化性溴介导的羧基化（EBRC）（EBRC），从2-FUROIC酸和Carobon Acid carbon diox产生FDCA。由于在此过程中直接利用二氧化碳作为最终羧化步骤的C1原料，因此拟议的FDCA生产的EBRC策略本质上是碳阴性的，具有潜在的环境和社会益处。使用计算和机器学习对反应条件进行筛查将有助于指导胜任电催化系统的设计和开发。该种子授予的总体目标是开发一种用于合成重要生物聚合物前体的电催化方法，即使用2,5-富含型的研究以及使用生物质量的生物质量和最终的生产型生物源和凯旋的生物群体，并构建了2,5-富含的碳纤维酸（FDCA）。有机电催化新兴领域的科学家。生成的数据，仿真框架和用于培训模型和预测属性的工具将以可发现的，可访问的，可互操作的，可重复使用的（公平）格式通过材料数据设施和NanoHub（在Purdue University所容纳的在线存储库，可为教育服务提供此信息，可为您提供教育工作的信息和开放式访问材料。辛辛那提大学（UC）的PI（Sun）小组将基于其积极参与外展计划，包括UC社区日开放日，UC Chem夏季营地，加州大学UC野外研究中心的科学日。普渡大学（Purdue University）的Co-Pi（Mannodi Kanakkithodi）小组将根据项目的密度功能理论计算和机器学习结果开发新的纳米ub资源。 These resources will be used for education and outreach, including incorporated coverage into graduate courses at Purdue University and as content for hands-on workshops on materials informatives organized on behalf of nanoHUB, which is typically attended by 100 to 300 students and researchers from across the world.This Future Manufacturing award was supported by funding from the Division of Chemistry in the Directorate for Mathematical and Physical Sciences.This award reflects NSF's statutory mission并被认为是使用基金会的知识分子优点和更广泛的审查标准的评估，被认为是宝贵的支持。