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Article: A generalized exchange-correlation functional: The Neural-Networks approach

TitleA generalized exchange-correlation functional: The Neural-Networks approach
Authors
Issue Date2004
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/cplett
Citation
Chemical Physics Letters, 2004, v. 390 n. 1-3, p. 186-192 How to Cite?
AbstractA Neural-Networks approach is employed to improve B3LYP exchange-correlation functional by taking into account of high-order contributions. The new B3LYP functional is based on a Neural-Network whose structure and synaptic weights are determined from 116 known experimental energy data [J. Chem. Phys. 98 (1993) 5648]. It leads to better agreement between the first-principles calculations and the experimental results. The new functional is further tested by applying it to calculate 40 ionization potentials and 40 enthalpies of formation in G2-2 test set [J. Chem. Phys. 109 (1998) 42] using 6-311+G(3df,2p) basis set. The root-mean-square errors are reduced from those of conventional B3LYP calculations. © 2004 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/69105
ISSN
2015 Impact Factor: 1.86
2015 SCImago Journal Rankings: 0.757
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZheng, Xen_HK
dc.contributor.authorHu, Len_HK
dc.contributor.authorWang, Xen_HK
dc.contributor.authorChen, Gen_HK
dc.date.accessioned2010-09-06T06:10:37Z-
dc.date.available2010-09-06T06:10:37Z-
dc.date.issued2004en_HK
dc.identifier.citationChemical Physics Letters, 2004, v. 390 n. 1-3, p. 186-192en_HK
dc.identifier.issn0009-2614en_HK
dc.identifier.urihttp://hdl.handle.net/10722/69105-
dc.description.abstractA Neural-Networks approach is employed to improve B3LYP exchange-correlation functional by taking into account of high-order contributions. The new B3LYP functional is based on a Neural-Network whose structure and synaptic weights are determined from 116 known experimental energy data [J. Chem. Phys. 98 (1993) 5648]. It leads to better agreement between the first-principles calculations and the experimental results. The new functional is further tested by applying it to calculate 40 ionization potentials and 40 enthalpies of formation in G2-2 test set [J. Chem. Phys. 109 (1998) 42] using 6-311+G(3df,2p) basis set. The root-mean-square errors are reduced from those of conventional B3LYP calculations. © 2004 Elsevier B.V. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/cpletten_HK
dc.relation.ispartofChemical Physics Lettersen_HK
dc.rightsChemical Physics Letters. Copyright © Elsevier BV.en_HK
dc.titleA generalized exchange-correlation functional: The Neural-Networks approachen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0009-2614&volume=390&spage=186&epage=192&date=2004&atitle=A+generalized+exchange-correlation+functional:+The+neural-networks+approach+en_HK
dc.identifier.emailChen, G:ghc@yangtze.hku.hken_HK
dc.identifier.authorityChen, G=rp00671en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.cplett.2004.04.020en_HK
dc.identifier.scopuseid_2-s2.0-2342576829en_HK
dc.identifier.hkuros92466en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-2342576829&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume390en_HK
dc.identifier.issue1-3en_HK
dc.identifier.spage186en_HK
dc.identifier.epage192en_HK
dc.identifier.isiWOS:000221628400035-
dc.publisher.placeNetherlandsen_HK
dc.identifier.scopusauthoridZheng, X=7404090981en_HK
dc.identifier.scopusauthoridHu, L=7401557295en_HK
dc.identifier.scopusauthoridWang, X=10341267000en_HK
dc.identifier.scopusauthoridChen, G=35253368600en_HK

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