基于量子化学DFT计算的镍催化CO2高效转化反应机理与立体选择性研究

About 40 billion tons of CO2 are discharged into the atmosphere every year, which will lead to global warming and other environmental problems. Using catalytic transformation to directly and efficiently convert CO2 into high value-added chemicals can not only reduce the emissions of CO2, but also realize the green resources utilization of CO2. As CO2 is difficult to be transformed due to its chemical inertness, the recently developed Nickel-catalyzed reductive cross-coupling between an electrophile and CO2 gives full play to the roles of the transformation of CO2 in this respect, which provides new insight into the highly efficient catalytic transformation of CO2 in atmosphere. However, the in-depth theoretical study on these reactions is lacking. There are only proposed mechanisms and the origins of stereoselectivities still remain unclear, which make it difficult to rationally design new efficient and selective catalysts. In this project, density functional theory (DFT) is proposed to use for the theoretical study on the detailed mechanisms and the origins of stereoselectivities for several novel reactions involving reductive carboxylation of CO2 in atmosphere by Ni catalysts. Through exploring the lowest-energy reaction pathways and studying the transition states and reactive intermediates involved in these reactions, the detailed reaction mechanisms and the origins of stereoselectivities will be established to enable the verification and prediction of experimental results, and an effective theoretical basis and scientific support will be provided for discovering new reactions and designing new efficient catalysts in the future, so that improving the experimental efficiency and reducing experimental cost as required by green chemistry. The project is expected to promote the development of new processes for catalytic transformation of CO2.

全球每年约400亿吨CO2被排放到大气中，导致气候变暖等环境问题。利用催化将CO2直接并高效转化为高附加值的化学品，既可减少CO2排放量，又可实现CO2绿色资源化利用。由于CO2的结构决定其难以被转化，镍催化CO2还原羧化则能很好的解决这一难题，为大气中CO2高效转化提供新思路。但这类反应缺乏理论上的深入研究，反应机理仅停留在推测阶段，立体选择性的根源尚未明确，导致设计新型高效、高选择性CO2催化转化催化剂及开发更有针对性的新反应存在较大的障碍。故本项目拟采用DFT计算方法对镍催化CO2还原羧化反应机理与立体选择性进行理论研究，通过全面、直观解析过渡态和中间体的结构与能量，阐明优势反应途径，揭示立体选择性的根源，指导并预测实验结果，为设计新型高效催化剂及开发新反应提供有效的理论依据和科学支撑，同时提高反应效率，降低成本，减少环境污染，实现绿色化学。本项目有望推动CO2催化转化新工艺的发展。

全球每年约400亿吨CO2被排放到大气中，导致气候变暖等环境问题。利用催化将CO2直接高效转化为高附加值化学品，既减少CO2排放量，又实现CO2绿色资源化利用。但CO2的结构决定其难以被转化，镍催化CO2还原羧化则能很好的解决这一难题，为CO2高效转化提供新思路。而这类反应缺乏理论上的深入研究，反应机理仅停留在推测阶段，立体选择性的根源尚未明确，导致设计新型高效、高选择性催化剂及开发更有针对性的新反应存在较大障碍。本项目通过DFT理论计算，系统深入的研究镍催化CO2还原羧化反应机理与立体选择性，定性与定量地分析结构的成键特征及其变化，直观、全面解释其实验现象，确立优势反应途径，揭示立体选择性的起源，阐明控制反应活性的关键因素，从本质上认识反应过程及其微观机理，得到所研究反应的普遍规律。为设计新型催化剂及开发新反应提供有效的理论依据和科学支撑，同时可提高反应效率，降低实验成本，减少环境污染，实现绿色化学，从理论上推动了CO2催化转化新工艺的发展。项目资助期间已发表SCI论文15篇，其中第一或通讯作者论文7篇，国际顶级期刊Chemical Society Reviews综述论文1篇（IF: 60.615），IF>10.0论文6篇，已申请国家发明专利2项。

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