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A machine learning correction for DFT non-covalent interactions based on the S22, S66 and X40 benchmark databases

Crossref DOI link: https://doi.org/10.1186/s13321-016-0133-7

Published Online: 2016-05-03

Published Print: 2016-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Gao, Ting

Li, Hongzhi

Li, Wenze

Li, Lin

Fang, Chao

Li, Hui

Hu, LiHong

Lu, Yinghua

Su, Zhong-Min
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (21473025)

National Natural Science Foundation of China (21131001)

The Science and Technology Development Planning of Jilin Province (CN) (20150204041GX)

The Science and Technology Development Planning of Jilin Province (CN) (20130522109JH)

The Education Department of Jilin Province (2015556)

The Education Department of Jilin Province (2014B045)
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Article History

Received: 10 November 2015

Accepted: 11 April 2016

First Online: 3 May 2016