Accurate prediction of heats of formation by a combined method of B3LYP and neural network correction |
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| Authors: | Jianming Wu Xin Xu |
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| Affiliation: | 1. State Key Laboratory of Physical Chemistry of Solid Surfaces;2. Center for Theoretical Chemistry;3. Department of Chemistry, College for Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China |
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| Abstract: | Recently, we proposed the X1 method which combines the B3LYP/6‐311+G(3df,2p)//B3LYP/6‐311+G(d,p) method with a neural network correction for an accurate yet efficient prediction of heats of formation (Wu and Xu, J Chem Phys 2007, 127, 214105). In this contribution, we discuss in detail how to set up the X1 neural network. We give examples, showing how to apply the X1 method and how the applicability of X1 can be extended. The overall mean absolute deviation of the X1 method from experiment for the 488 heats of formation is 1.52 kcal/mol compared with 9.44 kcal/mol for the original B3LYP results. © 2008 Wiley Periodicals, Inc. J Comput Chem 2009 |
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| Keywords: | DFT B3LYP heats of formation neural network |
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