Improving the accuracy of density-functional theory calculation: the genetic algorithm and neural network approach |
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Authors: | Li Hui Shi LiLi Zhang Min Su Zhongmin Wang XiuJun Hu LiHong Chen GuanHua |
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Affiliation: | Institute of Functional Material Chemistry, Faculty of Chemistry, Northeast Normal University, Changchun 130024, People's Republic of China. |
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Abstract: | The combination of genetic algorithm and neural network approach (GANN) has been developed to improve the calculation accuracy of density functional theory. As a demonstration, this combined quantum mechanical calculation and GANN correction approach has been applied to evaluate the optical absorption energies of 150 organic molecules. The neural network approach reduces the root-mean-square (rms) deviation of the calculated absorption energies of 150 organic molecules from 0.47 to 0.22 eV for the TDDFTB3LYP6-31G(d) calculation, and the newly developed GANN correction approach reduces the rms deviation to 0.16 eV. |
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