Vikramaditya Talapunur, Lin Shiang-Tai
Computational Molecular Engineering Laboratory, Department of Chemical Engineering, National Taiwan University, Taipei, 10617, Taiwan.
J Comput Chem. 2017 Jun 5;38(21):1844-1852. doi: 10.1002/jcc.24828. Epub 2017 May 11.
Accurate determination of ionization potentials (IPs), electron affinities (EAs), fundamental gaps (FGs), and HOMO, LUMO energy levels of organic molecules play an important role in modeling and predicting the efficiencies of organic photovoltaics, OLEDs etc. In this work, we investigate the effects of Hartree Fock (HF) Exchange, correlation energy, and long range corrections in predicting IP and EA in Hybrid Functionals. We observe increase in percentage of HF exchange results in increase of IPs and decrease in EAs. Contrary to the general expectations inclusion of both HF exchange and correlation energy (from the second order perturbation theory MP2) leads to poor prediction. Range separated Hybrid Functionals are found to be more reliable among various DFT Functionals investigated. DFT Functionals predict accurate IPs whereas post HF methods predict accurate EAs. © 2017 Wiley Periodicals, Inc.
准确测定有机分子的电离能(IPs)、电子亲和能(EAs)、基本能隙(FGs)以及最高占据分子轨道(HOMO)、最低未占据分子轨道(LUMO)能级,在有机光伏、有机发光二极管等器件效率的建模和预测中起着重要作用。在这项工作中,我们研究了哈特里 - 福克(HF)交换、相关能以及长程校正对混合泛函中IP和EA预测的影响。我们观察到HF交换百分比的增加会导致IPs增加和EAs降低。与一般预期相反,同时包含HF交换和相关能(来自二阶微扰理论MP2)会导致预测效果不佳。在所研究的各种密度泛函理论(DFT)泛函中,范围分离的混合泛函被发现更可靠。DFT泛函能准确预测IPs,而后HF方法能准确预测EAs。© 2017威利期刊公司