Huang Mengxue, Zhu Xuya, Shi Wenwen, Qin Qianqian, Yang Jie, Liu Shanshan, Chen Lifang, Ding Ruimin, Gan Lin, Yin Xi
State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan, Shanxi 030001, China.
School of Chemical Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.
Sci Adv. 2025 Feb 28;11(9):eads6658. doi: 10.1126/sciadv.ads6658. Epub 2025 Feb 26.
Nitrogen-coordinated metal sites (MN) in metal- and nitrogen-codoped carbon (M-N-C) catalysts offer promising electrocatalytic activity, but selective synthetic design of MN sites with specific coordination environments remains challenging. Here, we manipulate the formation statistics of MN sites by using sacrifice alkali metals (AM = Li, Na, and K) to form metal vacancy-N carbon (AM-MVN-C) templates, which are used to direct the solution-phase formation of CoN sites in Co-N-C catalysts. We build a probability weight function based on the embedding energy of M in MN sites as the descriptor for MN formation statistics, and we predict that the alkali metals are prone to induce the formation of MVN sites. By coordinating Co ions with AM-MVN-C templates, we synthesize Co-N-C with CoN sites, demonstrating remarkable oxygen reduction activity in anion exchange membrane fuel cells. These results highlight the statistical thermodynamics of MN formation and open up the possibility for the rational design of complex M-N-C electrocatalysts with well-defined MN sites.
金属与氮共掺杂碳(M-N-C)催化剂中的氮配位金属位点(MN)具有良好的电催化活性,但具有特定配位环境的MN位点的选择性合成设计仍然具有挑战性。在这里,我们通过使用牺牲碱金属(AM = Li、Na和K)来形成金属空位-N碳(AM-MVN-C)模板,从而操纵MN位点的形成统计,该模板用于指导Co-N-C催化剂中CoN位点的溶液相形成。我们基于M在MN位点中的嵌入能量构建了一个概率权重函数,作为MN形成统计的描述符,并预测碱金属易于诱导MVN位点的形成。通过将Co离子与AM-MVN-C模板配位,我们合成了具有CoN位点的Co-N-C,在阴离子交换膜燃料电池中表现出显著的氧还原活性。这些结果突出了MN形成的统计热力学,并为合理设计具有明确MN位点的复杂M-N-C电催化剂开辟了可能性。