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首页> 外文期刊>The Journal of Chemical Physics >Automated property optimization via ab initio O(N) elongation method: Application to (hyper-)polarizability in DNA
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Automated property optimization via ab initio O(N) elongation method: Application to (hyper-)polarizability in DNA

机译:通过从头算O(N)延伸方法自动进行性能优化:在DNA的(超)极化率中的应用

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An automated property optimization method was developed based on the ab initio O(N) elongation (ELG) method and applied to the optimization of nonlinear optical (NLO) properties in DNA as a first test. The ELG method mimics a polymerization reaction on a computer, and the reaction terminal of a starting cluster is attacked by monomers sequentially to elongate the electronic structure of the system by solving in each step a limited space including the terminal (localized molecular orbitals at the terminal) and monomer. The ELG-finite field (ELG-FF) method for calculating (hyper-)polarizabilities was used as the engine program of the optimization method, and it was found to show linear scaling efficiency while maintaining high computational accuracy for a random sequenced DNA model. Furthermore, the self-consistent field convergence was significantly improved by using the ELG-FF method compared with a conventional method, and it can lead to more feasible NLO property values in the FF treatment. The automated optimization method successfully chose an appropriate base pair from four base pairs (A, T, G, and C) for each elongation step according to an evaluation function. From test optimizations for the first order hyper-polarizability (beta) in DNA, a substantial difference was observed depending on optimization conditions between "choose-maximum" (choose a base pair giving the maximum beta for each step) and "choose-minimum" (choose a base pair giving the minimum beta). In contrast, there was an ambiguous difference between these conditions for optimizing the second order hyper-polarizability (gamma) because of the small absolute value of. and the limitation of numerical differential calculations in the FF method. It can be concluded that the ab initio level property optimization method introduced here can be an effective step towards an advanced computer aided material design method as long as the numerical limitation of the FF method is taken into account. Published by AIP Publishing.
机译:基于从头算O(N)伸长(ELG)方法开发了一种自动属性优化方法,并将其应用于DNA中非线性光学(NLO)属性的优化作为第一个测试。 ELG方法模拟计算机上的聚合反应,起始簇的反应末端依次受到单体的攻击,从而通过在每个步骤中求解包括末端在内的有限空间(末端的局部分子轨道)来延长系统的电子结构)和单体。用于计算(超)极化率的ELG有限域(ELG-FF)方法被用作优化方法的引擎程序,并且发现它在显示线性缩放效率的同时,还为随机序列DNA模型提供了高计算精度。此外,与常规方法相比,使用ELG-FF方法可显着改善自洽场收敛,并且可以在FF处理中获得更可行的NLO属性值。自动化优化方法根据评估函数从每个延伸步骤的四个碱基对(A,T,G和C)中成功选择了一个合适的碱基对。从DNA中的一阶超极化率(beta)的测试优化中,根据“选择最大”(选择每个步骤给出最大beta的碱基对)和“选择最小”之间的优化条件,观察到了很大的差异。 (选择一个给出最小beta的碱基对)。相比之下,由于的绝对值较小,因此在用于优化二阶超极化率(γ)的这些条件之间存在歧义差异。以及FF方法中数值微分计算的局限性。可以得出结论,只要考虑到FF方法的数值限制,此处介绍的从头开始的级性能优化方法就可以成为迈向先进的计算机辅助材料设计方法的有效步骤。由AIP Publishing发布。

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