二维材料电催化还原二氧化碳的构效关系与高效电催化剂的理性设计

It is strategically significant to solve the issues of increasingly energy shortage and environmental pollution by converting CO2 into high-value fuels and chemicals via electroreduction of CO2 with the electricity from clean and renewable energy. However, there is still no an efficient catalyst that could catalyze this reaction with high activity, selectivity and stability. Exploiting catalysts with high efficiency is an important task in this field. In this proposal we aim to quickly search reaction paths, clarify reaction mechanisms, and determine activation sites of electroreduction of CO2 on 2D materials. We would then construct a high-throughput database, relate the structure and performance of catalysts, propose a simple and reliable descriptor controlling CO2 electroreduction, so as to evaluate the activity and selectivity of catalysts quickly and ultimately screen high-performance catalysts for CO2 electroreduction. Next, under the guidance of theoretical computations, we would design and prepare 2D electrocatalysts via feasible chemical routes, and explore their applications to CO2 electroreduction. By repetitively testing and verifying between computations and experiments, we could demonstrate a clear direction for future design and exploration of efficient catalysts.

电催化还原CO2技术可以利用清洁可再生能源产生的电能，在催化剂的作用下将CO2直接转化为高附加值的燃料和化学品，对于缓解日益严峻的能源短缺和环境污染问题具有重大的战略意义。然而，目前仍然没有一种有效的催化剂能够高活性、高选择性、高稳定性地催化该反应的进行。因此，新型高效催化剂的研究开发是该领域亟需攻克的重要课题。本申请通过理论计算实现快速搜索二维材料上电催化还原CO2的反应路径，揭示反应机理，明确反应活性位点；进而构建高通量数据库，建立催化剂结构和催化性能之间的构效关系，提出控制CO2还原反应的简单可靠的描述因子，以快速评估催化剂的催化活性和选择性，最终筛选出高性能的电化学还原CO2催化剂。在理论计算结果的指导下，通过可行的化学方法设计制备二维电催化剂，并探索它们在电催化还原CO2方面的应用。通过计算模拟与实验紧密结合反复验证，为未来高效催化材料的设计和研发指明方向。

电催化还原CO2利用可再生能源产生的电能，在催化剂的作用下将CO2直接转化为清洁燃料和高附加值的化学品，是实现“碳达峰、碳中和”目标的重要途径，其核心为高性能电催化剂。项目组通过计算模拟与实验相结合深入研究CO2电催化机理及二维电催化剂设计，为未来高效电催化材料的研发指明方向。通过模拟接近真实电化学环境下CO2还原过程，发现轴向氧原子可以显著促进NiN4单原子催化剂催化CO2活化和吸附态COOH的形成过程。基于粒子群优化算法和第一性原理计算发现，具有平面超配位结构的二维单层Cu2B2可以将CO转化为乙醇。运用XGBR等机器学习算法和特征工程，提出了适用于快速筛选CO2还原的单原子催化剂的机器学习模型。采用快速热解的新方法制备了Ni单原子催化剂，其电化学还原CO2产生CO的法拉第效率最高可达95%。以上工作对理解CO2电催化还原过程及高效筛选设计电催化剂具有指导意义。相关研究已在高水平期刊发表论文7篇，在相关领域产生了较大学术影响。