CAREER: Solution Catalysis Containing Seemingly Incompatible Steps

职业：含有看似不相容步骤的溶液催化

• 批准号: 2143952
• 负责人: Chong Liu
• 金额: $ 60万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2143952&HistoricalAwards=false
• 关键词: CAREER; Solution; Catalysis; Containing; Seemingly

With the support of the Chemical Catalysis (CAT)program in the Division of Chemistry, Chong Liu of the University of California, Los Angeles (UCLA) is developing new catalytic transformations in contain normally incompatible steps within the reaction cycles. With the use of electrochemistry, nanomaterials, and machine learning, the Liu team seeks to establish general design principles and develop new catalysts for important chemical reactions including the conversion of carbon dioxide and methane into commodity chemicals. Dr. Liu also strives to facilitate inclusive, interdisciplinary training of graduate and undergraduate students from different backgrounds. Dr. Liu is applying machine learning and natural language processing to aid the curriculum development of general chemistry courses at the University of California, Los Angeles. If successful, such efforts have the potential to improve learning experiences and outcomes for tens of thousands of undergraduates. Successful completion of such a project will boost society’s appreciation of STEM (science, technology, engineering and mathematics) education and help train the next-generation workforce. In this research project, Chong Liu and his team at UCLA are developing design principles for solution catalysis containing competing/incompatible reaction steps and applying such principles to a variety of applications. In these endeavors, nanomaterials-based electrochemistry serves as a platform to control the spatial distribution of reactant species at the microscopic level. Aided by machine-learning-based inverse design, the research will focus on the mechanistic study and practical application of such concepts to the activation of light alkanes, reductive dechlorination of organic pollutants, and the catalytic cascade that couples the electrochemical reduction of CO2 with the hydroformylation reaction. In the long run, such research will answer two important questions in the field of catalysis: (1) Can one develop a general platform applicable to a variety of spatially controlled solution catalysis with translatable know-how? (2) How can one quantitatively tailor the spatial control of chemical reactions based on the intrinsic reactivity of a targeted reaction step? Mimicking biology by controlling the spatial distribution of solution catalysis at the microscopic level offers to potential for the development of new chemical transformations that would be difficult, if not impossible, to develop in homogenous solution.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.

在化学系化学催化 (CAT) 项目的支持下，加州大学洛杉矶分校 (UCLA) 的 Chong Liu 正在利用电化学开发新的催化转化，以包含反应循环中通常不相容的步骤。 、纳米材料和机器学习，刘博士团队致力于建立通用设计原则并开发重要化学反应的新催化剂，包括将二氧化碳和甲烷转化为商品化学品。刘博士还努力促进包容性、跨学科的发展。刘博士正在对来自不同背景的研究生和本科生进行培训，以帮助加州大学洛杉矶分校的普通化学课程开发。如果成功，这些努力有可能改善学习。刘冲和他的研究项目成功完成了这个项目，将提高社会对 STEM（科学、技术、工程和数学）教育的认识，并帮助培养下一代劳动力。加州大学洛杉矶分校的团队正在制定解决方案的设计原则包含竞争/不相容反应步骤的催化并将这些原理应用于各种应用中，基于纳米材料的电化学可以作为在微观水平上控制反应物物种空间分布的平台。设计中，该研究将重点关注这些概念在轻烷烃活化、有机污染物还原脱氯以及耦合电化学还原的催化级联中的机理研究和实际应用。从长远来看，此类研究将回答催化领域的两个重要问题：（1）能否开发出一种适用于各种空间控制溶液催化并具有可转化技术的通用平台（2？ ）如何根据目标反应步骤的内在反应性来定量地调整化学反应的空间控制？通过在微观水平上控制溶液催化的空间分布来模拟生物学，为开发新的化学转化提供了潜力。即使不是不可能，也很难以同质解决方案进行开发。该奖项反映了 NSF 的法定使命，并且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。