Charge Separation in Donor–C60 Complexes with Real-Time Green Functions: The Importance of Nonlocal Correlations,Nano Letters

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Charge Separation in Donor–C60 Complexes with Real-Time Green Functions: The Importance of Nonlocal Correlations
Nano Letters ( IF 9.6 ) Pub Date : 2018-01-04 00:00:00 , DOI: 10.1021/acs.nanolett.7b03995
Emil Viñas Boström ₁ , Anders Mikkelsen ₂ , Claudio Verdozzi ₁ , Enrico Perfetto _{3,

4} , Gianluca Stefanucci _{4,

5}

Affiliation

We use the nonequilibrium Green function (NEGF) method to perform real-time simulations of the ultrafast electron dynamics of photoexcited donor–C₆₀ complexes modeled by a Pariser–Parr–Pople Hamiltonian. The NEGF results are compared to mean-field Hartree–Fock (HF) calculations to disentangle the role of correlations. Initial benchmarking against numerically highly accurate time-dependent density matrix renormalization group calculations verifies the accuracy of NEGF. We then find that charge-transfer (CT) excitons partially decay into charge separated (CS) states if dynamical nonlocal correlation corrections are included. This CS process occurs in ∼10 fs after photoexcitation. In contrast, the probability of exciton recombination is almost 100% in HF simulations. These results are largely unaffected by nuclear vibrations; the latter become however essential whenever level misalignment hinders the CT process. The robust nature of our findings indicates that ultrafast CS driven by correlation-induced decoherence may occur in many organic nanoscale systems, but it will only be correctly predicted by theoretical treatments that include time-nonlocal correlations.

中文翻译：

具有实时绿色功能的供体– C ₆₀配合物中的电荷分离：非局部相关性的重要性

我们使用非平衡格林函数（NEGF）方法对以Pariser-Parr-Pople哈密顿量为模型的光激发供体-C ₆₀配合物的超快电子动力学进行实时模拟。将NEGF结果与平均场Hartree-Fock（HF）计算进行比较，以弄清相关性的作用。针对数值高度精确的随时间变化的密度矩阵重新归一化组计算的初始基准测试验证了NEGF的准确性。然后，我们发现如果动态，电荷转移（CT）激子会部分衰减为电荷分离（CS）状态包括非局部相关校正。该CS过程在光激发后约10 fs内发生。相反，在HF模拟中，激子复合的可能性几乎为100％。这些结果在很大程度上不受核振动的影响。但是，只要水平未对准阻碍CT过程，后者就变得必不可少。我们发现的稳健性表明，由相关诱导的退相干驱动的超快CS可能发生在许多有机纳米级系统中，但只有通过包括时间-非局部相关性在内的理论处理才能正确预测。

更新日期：2018-01-04

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