TD-DFT based fine-tuning of molecular excitation energies using evolutionary algorithms

TD-DFT based fine-tuning of molecular excitation energies using evolutionary algorithms
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使用进化算法基于 TD-DFT 的分子激发能微调

DOI:
10.1039/c5ra22800j
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发表时间:
2016
期刊:
影响因子:
3.9
通讯作者:
B. Alsberg
B. Alsberg
中科院分区:
化学3区
文献类型:
--
作者:
Sailesh Abburu;Vishwesh Venkatraman;B. Alsberg

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提出了一种进化从头设计方法,对基于时间依赖密度泛函理论(TD-DFT)计算的分子激发能进行微调。该方法应用于偶氮苯的π共轭分子体系。在多个超级计算集群上,在TD-DFT水平上计算了进化设计方案产生的所有分子的激发能。利用自主开发的软件自动建立TD-DFT计算,利用并行化的优势,加快了进化从头开始程序的结果获取过程。我们提出的优化方案能够在激发能显著降低的情况下提出新的偶氮苯结构。
An evolutionary de novo design method is presented to fine-tune the excitation energies of molecules calculated using time-dependent density functional theory (TD-DFT). The approach is applied to a π-conjugated molecular system, azobenzene. The excitation energies for all the molecules generated by the evolutionary design scheme were computed at TD-DFT level on multiple supercomputing clusters. A software developed in-house was used to automatically set up the TD-DFT calculations and exploit the advantages of parallelization and thereby speed up the process of obtaining results for the evolutionary de novo program. Our proposed optimisation scheme is able to propose new azobenzene structures with significant decrease in excitation energies.
DOI: 10.1021/ja408104w
发表时间: 2013-11-27
影响因子: 15
作者:
Kienzler MA;Reiner A;Trautman E;Yoo S;Trauner D;Isacoff EY
通讯作者: Isacoff EY
DOI: 10.1039/c5nr03774c
发表时间: 2015-01-01
期刊: NANOSCALE
影响因子: 6.7
作者:
Davis, Jack B. A.;Shayeghi, Armin;Johnston, Roy L.
通讯作者: Johnston, Roy L.