Zhao Qing, Kulik Heather J
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.
J Phys Chem Lett. 2019 Sep 5;10(17):5090-5098. doi: 10.1021/acs.jpclett.9b01650. Epub 2019 Aug 21.
Approximate, semilocal density functional theory (DFT) suffers from delocalization error that can lead to a paradoxical model of catalytic surfaces that both overbind adsorbates yet are also too stable. We investigate the effect of two widely applied approaches for delocalization error correction, (i) affordable DFT+U (i.e., semilocal DFT augmented with a Hubbard U) and (ii) hybrid functionals with an admixture of Hartree-Fock (HF) exchange, on surface and adsorbate energies across a range of rutile transition metal oxides widely studied for their promise as water-splitting catalysts. We observe strongly row- and period-dependent trends with DFT+U, which increases surface formation energies only in early transition metals (e.g., Ti and V) and decreases adsorbate energies only in later transition metals (e.g., Ir and Pt). Both global and local hybrids destabilize surfaces and reduce adsorbate binding across the periodic table, in agreement with higher-level reference calculations. Density analysis reveals why hybrid functionals correct both quantities, whereas DFT+U does not. We recommend local, range-separated hybrids for the accurate modeling of catalysis in transition metal oxides at only a modest increase in computational cost over semilocal DFT.
近似的半局域密度泛函理论(DFT)存在离域误差,这可能导致催化表面的矛盾模型,即对吸附质过度结合但又过于稳定。我们研究了两种广泛应用的离域误差校正方法的效果,(i)经济实惠的DFT+U(即通过哈伯德U增强的半局域DFT)和(ii)混合了哈特ree - 福克(HF)交换的混合泛函,研究对象是一系列因其作为水分解催化剂的潜力而被广泛研究的金红石型过渡金属氧化物的表面和吸附质能量。我们观察到DFT+U呈现出强烈的行和周期依赖性趋势,它仅在早期过渡金属(如Ti和V)中增加表面形成能,仅在后期过渡金属(如Ir和Pt)中降低吸附质能量。与更高水平的参考计算结果一致,全局和局部混合泛函都会使表面不稳定,并降低整个周期表中吸附质的结合能。密度分析揭示了混合泛函为何能同时校正这两个量,而DFT+U却不能。我们建议使用局部、范围分离的混合泛函,以便在仅比半局域DFT计算成本适度增加的情况下,对过渡金属氧化物中的催化作用进行精确建模。