Zong Jingshan, He Cheng, Zhang Wenxue, Bai Min
School of Materials Science and Engineering, Chang'an University, Xi'an 710064, China.
State Key Laboratory for Mechanical Behavior of Materials, School of Materials Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China.
J Colloid Interface Sci. 2023 Dec 15;652(Pt A):878-889. doi: 10.1016/j.jcis.2023.08.114. Epub 2023 Aug 20.
Solar energy has the potential to revolutionize the production of ammonia, as it could provide a reliable and uninterrupted source of energy for the chemical reaction involved. However, improving the catalytic performance of catalysts often leads to a reduction in their band gaps, which results in insufficient photogenerated electron potential to realize the nitrogen reduction reaction (NRR), and thus the development of NRR efficient photocatalysts remains a great challenge. Herein, based on the density functional theory (DFT), a series of single-atom photocatalysts with transition metals (TMs) doped on porous boron nitride (p-BN) nanosheet are proposed for NRR. Among them, Re-B3@p-BN could effectively catalyze gas-phase N through the corresponding pathways with limiting potentials of 0.31 V. Meanwhile, it exhibits excellent light absorption efficiency under illumination and could spontaneously catalyse nitrogen fixation reactions due to the suitable forbidden band and high photogenerated electron potential. Moreover, a linear relationship descriptor based on the intrinsic properties has been established, using a machine learning approach by considering the combined effects of the central metal atom and the coordination atoms. This descriptor could help accelerate the development of rational and improved 2D NRR photocatalysts with high catalytic activity and high selectivity.
太阳能有潜力彻底改变氨的生产,因为它可为相关化学反应提供可靠且不间断的能源。然而,提高催化剂的催化性能往往会导致其带隙减小,从而使光生电子电位不足以实现氮还原反应(NRR),因此开发高效的NRR光催化剂仍然是一个巨大的挑战。在此,基于密度泛函理论(DFT),提出了一系列过渡金属(TMs)掺杂在多孔氮化硼(p-BN)纳米片上的单原子光催化剂用于NRR。其中,Re-B3@p-BN可以通过相应途径有效地催化气相氮,极限电位为0.31V。同时,它在光照下表现出优异的光吸收效率,并且由于合适的禁带和高光生电子电位,可以自发催化固氮反应。此外,通过考虑中心金属原子和配位原子的综合作用,利用机器学习方法建立了基于本征性质的线性关系描述符。该描述符有助于加速开发具有高催化活性和高选择性的合理且改进的二维NRR光催化剂。