2026-10-14T16:48:04Z https://www.scidb.cn/oai

10.57760/sciencedb.35642 2026-05-07T11:05:09Z

2026-05-07 Effect of t-ZrO2/m-ZrO2 Phase Interfaces on the Stability of Ni/Ca-ZrO2 Catalysts for CO2 Methanation doi:10.57760/sciencedb.35642 en Nickel-based catalysts are considered among the most promising candidates for CO2 methanation; however, their tendency toward high-temperature sintering-induced deactivation remains a critical bottleneck for practical application. In this work, a series of Ni-based catalysts supported on mixed-phase t-ZrO2/m-ZrO2 nanocrystalline supports were firstly constructed via Ca doping and thermal treatment regulation. The catalyst calcined at 700 °C exhibited the best stability and low-temperature activity for CO2 methanation. Comprehensive characterizations, including XRD, BET, XPS, TEM, H2-TPR/TPD, and CO2-TPD, revealed that increasing calcination temperature enhanced the Ca-promoted phase transformation from m-ZrO2 to t-ZrO2 and facilitated grain growth of both zirconia phases. At a calcination temperature of 700 °C, t-ZrO2 and m-ZrO2 crystallites in the support were both small and comparable in size, favoring the formation of mixed-phase interfaces. The m/t-ZrO2 interphase boundaries provided anchoring sites for Ni nanoparticles, which is identified as the primary reason for the superior high-temperature anti-sintering performance of the catalyst calcined at 700 °C. In addition, these mixed-phase interfaces optimized the local electronic structure and enriched oxygen vacancy defects, thereby lowering the apparent activation energy for CO2 activation and endowing the 700 °C calcined catalyst with the highest low-temperature CO2 methanation activity. These findings demonstrate that constructing m/t-ZrO2 interphase boundaries through promoter engineering and thermal-treatment control is an effective strategy to stabilize Ni nanoparticles and enhance catalytic performance. methanation; Ni/Ca-ZrO2 catalyst; sintering resistance; CO2 Fu Yitian Li Jia Jiang Yanan Bai Yang Liu Yuan RESTRICTED dataset Science Data Bank