Developing cost-effective and high-performance catalysts for energy storage and conversion is a fundamental issue in fuel cells and metal-air batteries. [1-6] To this aim, non-precious metal based or metal free catalysts are extensively investigated to replace noble metal based catalysts. Yet, the active sites and mechanisms of catalytic reactions are always complicated, which makes it difficult to design high performance catalysts in experiments. For example, the lifetime of catalytic reaction intermediates is always too short to be detected in experiments. Fortunately, first-principles simulations are capable to obtain the information about the intermediates and reaction mechanisms in atomic scale. Therefore, we investigated the carbon based (such as nitrogen doped graphene) [2-6] and non-precious based (such as Fe based catalysts) [1] catalysts by density functional theory simulations and Car-Parrinello dynamic simulations for a series of catalytic reactions including oxygen reduction reaction in fuels and CO2 reduction reaction in order to clarify the corresponding active sites, selectivity and dynamic mechanisms.[3,5] The calculated electronic properties of catalysts is related to the activity qualitatively. The calculated binding energies indicate that it observes the so-called linear scale relationship which is used to predict new catalysts. At last, the calculated reaction barriers and dynamics are useful to clarify the reaction mechanism. All of these are very important for improving the performance of new catalysts in experiments.
References:
[1] J. Guo†, X. Yan†, Q. Liu, Q. Li, X. Xu, L. Kang*, Z. Cao*, G. Chai*, J. Chen, Y. Wang, J. Yao, Nano Energy 2018, 46, 347.
[2] G. Chai*†, K. Qiu†, M. Qiao, M. Titirici, C. Shang, Z. Guo*, Energy Environ. Sci. 2017, 10, 1186.
[3] G. Chai*, Z. Hou, D. J. Shu, T. Ikeda, K. Terakura, J. Am. Chem. Soc. 2014, 136, 13629.
[4] G. Chai*, M. Boero, Z. Hou, K. Terakura, and W. D. Cheng, ACS Catal. 2017, 7, 7908.
[5] G. Chai, Z. Guo*, Chem. Sci. 2016, 7, 1268.
[6] L. Ye, G. Chai*, Z. Wen*, Adv. Funct. Mater. 2017, 1606190.