Corona Benjamin, Howard Marco, Zhang Liang, Henkelman Graeme
Department of Chemistry and the Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas 78712-0165, USA.
J Chem Phys. 2016 Dec 28;145(24):244708. doi: 10.1063/1.4972579.
Using density functional theory calculations, a set of candidate nanoparticle catalysts are identified based on reactivity descriptors and segregation energies for the oxygen reduction and hydrogen evolution reactions. Trends in the data were identified by screening over 700 core@shell 2 nm transition metal nanoparticles for each reaction. High activity was found for nanoparticles with noble metal shells and a variety of core metals for both reactions. By screening for activity and stability, we obtain a set of interesting bimetallic catalysts, including cases that have reduced noble metal loadings and a higher predicted activity as compared to monometallic Pt nanoparticles.
利用密度泛函理论计算，基于氧还原反应和析氢反应的反应性描述符和偏析能，确定了一组候选纳米颗粒催化剂。通过对每种反应的700多个核壳2纳米过渡金属纳米颗粒进行筛选，确定了数据中的趋势。发现对于两种反应，具有贵金属壳和多种核金属的纳米颗粒具有高活性。通过筛选活性和稳定性，我们获得了一组有趣的双金属催化剂，包括与单金属铂纳米颗粒相比具有降低的贵金属负载量和更高预测活性的情况。
