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Long-range parameter optimization for a better description of potential energy surfaces using Density Functional Theory
The advance of computing and the development of modern quantum chemistry models such as Density Functional Theory (DFT) have allowed scientists to perform fast in silico studies with accurate results. It also allowed for the achievement of empirically unattainable quantities such as Potential Energy...
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Published in: | Journal of molecular modeling 2022-05, Vol.28 (5), p.121-121, Article 121 |
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creator | Bispo, Matheus de Oliveira Filho, Demétrio Antônio da Silva |
description | The advance of computing and the development of modern quantum chemistry models such as Density Functional Theory (DFT) have allowed scientists to perform fast in silico studies with accurate results. It also allowed for the achievement of empirically unattainable quantities such as Potential Energy Surfaces (PES), a fundamental construct in various applications, such as the study of weakly bound systems. One of DFT’s current weaknesses is a reliable description of PESs, due to a lack of suitable exchange-correlation functionals. In general, other post-Hartree-Fock methods are employed, such as
n
th-order Møller-Plesset’s Perturbation Theory (MPn) or Coupled Cluster Theory (CCSD(T)) with large basis sets. Despite producing good results, these methods demand much computational power when applied to large systems. This work presents a novel approach of PES description of the
H
2
O
2
–Kr system using DFT by optimizing a long-range parameter present in some DFT functionals, obtaining results similar to those of the MPn methods with somewhat less computational time necessary.
Graphical Abstract
By optimizing the omega value of certain functionals, DFT can describe PESs with accuracy comparable to MP4 methods |
doi_str_mv | 10.1007/s00894-022-05083-1 |
format | article |
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n
th-order Møller-Plesset’s Perturbation Theory (MPn) or Coupled Cluster Theory (CCSD(T)) with large basis sets. Despite producing good results, these methods demand much computational power when applied to large systems. This work presents a novel approach of PES description of the
H
2
O
2
–Kr system using DFT by optimizing a long-range parameter present in some DFT functionals, obtaining results similar to those of the MPn methods with somewhat less computational time necessary.
Graphical Abstract
By optimizing the omega value of certain functionals, DFT can describe PESs with accuracy comparable to MP4 methods</description><identifier>ISSN: 1610-2940</identifier><identifier>EISSN: 0948-5023</identifier><identifier>DOI: 10.1007/s00894-022-05083-1</identifier><identifier>PMID: 35426616</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Characterization and Evaluation of Materials ; Chemistry ; Chemistry and Materials Science ; Computer Appl. in Life Sciences ; Computer Applications in Chemistry ; Computing time ; Density functional theory ; Hydrogen peroxide ; Molecular Medicine ; Optimization ; Original Paper ; Parameters ; Perturbation theory ; Potential energy ; Production methods ; Quantum chemistry ; Theoretical and Computational Chemistry ; XXI-Brazilian Symposium of Theoretical Chemistry (SBQT2021)</subject><ispartof>Journal of molecular modeling, 2022-05, Vol.28 (5), p.121-121, Article 121</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022</rights><rights>2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-602866bda0fdba800d4fbbec5ecdd5577b7ecdc7701f2d0fe0ce95d5069eeb7c3</citedby><cites>FETCH-LOGICAL-c375t-602866bda0fdba800d4fbbec5ecdd5577b7ecdc7701f2d0fe0ce95d5069eeb7c3</cites><orcidid>0000-0002-7103-4780</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35426616$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Bispo, Matheus de Oliveira</creatorcontrib><creatorcontrib>Filho, Demétrio Antônio da Silva</creatorcontrib><title>Long-range parameter optimization for a better description of potential energy surfaces using Density Functional Theory</title><title>Journal of molecular modeling</title><addtitle>J Mol Model</addtitle><addtitle>J Mol Model</addtitle><description>The advance of computing and the development of modern quantum chemistry models such as Density Functional Theory (DFT) have allowed scientists to perform fast in silico studies with accurate results. It also allowed for the achievement of empirically unattainable quantities such as Potential Energy Surfaces (PES), a fundamental construct in various applications, such as the study of weakly bound systems. One of DFT’s current weaknesses is a reliable description of PESs, due to a lack of suitable exchange-correlation functionals. In general, other post-Hartree-Fock methods are employed, such as
n
th-order Møller-Plesset’s Perturbation Theory (MPn) or Coupled Cluster Theory (CCSD(T)) with large basis sets. Despite producing good results, these methods demand much computational power when applied to large systems. This work presents a novel approach of PES description of the
H
2
O
2
–Kr system using DFT by optimizing a long-range parameter present in some DFT functionals, obtaining results similar to those of the MPn methods with somewhat less computational time necessary.
Graphical Abstract
By optimizing the omega value of certain functionals, DFT can describe PESs with accuracy comparable to MP4 methods</description><subject>Characterization and Evaluation of Materials</subject><subject>Chemistry</subject><subject>Chemistry and Materials Science</subject><subject>Computer Appl. in Life Sciences</subject><subject>Computer Applications in Chemistry</subject><subject>Computing time</subject><subject>Density functional theory</subject><subject>Hydrogen peroxide</subject><subject>Molecular Medicine</subject><subject>Optimization</subject><subject>Original Paper</subject><subject>Parameters</subject><subject>Perturbation theory</subject><subject>Potential energy</subject><subject>Production methods</subject><subject>Quantum chemistry</subject><subject>Theoretical and Computational Chemistry</subject><subject>XXI-Brazilian Symposium of Theoretical Chemistry (SBQT2021)</subject><issn>1610-2940</issn><issn>0948-5023</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9kUFvFCEYhonR2E3tH_BgSLx4oX4wA8wcTbVqsomXeiYM87HS7AwjMDHbX192t2riwRMk7_O-kDyEvOZwzQH0-wzQ9S0DIRhI6BrGn5EN9G3HJIjmOdlwxYGJvoULcpXzPQBwIZUU4iW5aGQrlOJqQ35t47xjyc47pItNdsKCicalhCk82BLiTH1M1NIByzEZMbsUllMQPV1iwbkEu6c4Y9odaF6Ttw4zXXOYd_QjzjmUA71dZ3fsVPDuB8Z0eEVeeLvPePV0XpLvt5_ubr6w7bfPX28-bJlrtCxMgeiUGkYLfhxsBzC2fhjQSXTjKKXWg643pzVwL0bwCA57OUpQPeKgXXNJ3p13lxR_rpiLmUJ2uN_bGeOajVCSq55rDhV9-w96H9dUv3yioNU9b1WlxJlyKeac0Jslhcmmg-FgjmbM2YypZszJjOG19OZpeh0mHP9UfnuoQHMGco2qi_T37f_MPgKTHpvp</recordid><startdate>20220501</startdate><enddate>20220501</enddate><creator>Bispo, Matheus de Oliveira</creator><creator>Filho, Demétrio Antônio da Silva</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-7103-4780</orcidid></search><sort><creationdate>20220501</creationdate><title>Long-range parameter optimization for a better description of potential energy surfaces using Density Functional Theory</title><author>Bispo, Matheus de Oliveira ; Filho, Demétrio Antônio da Silva</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-602866bda0fdba800d4fbbec5ecdd5577b7ecdc7701f2d0fe0ce95d5069eeb7c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Characterization and Evaluation of Materials</topic><topic>Chemistry</topic><topic>Chemistry and Materials Science</topic><topic>Computer Appl. in Life Sciences</topic><topic>Computer Applications in Chemistry</topic><topic>Computing time</topic><topic>Density functional theory</topic><topic>Hydrogen peroxide</topic><topic>Molecular Medicine</topic><topic>Optimization</topic><topic>Original Paper</topic><topic>Parameters</topic><topic>Perturbation theory</topic><topic>Potential energy</topic><topic>Production methods</topic><topic>Quantum chemistry</topic><topic>Theoretical and Computational Chemistry</topic><topic>XXI-Brazilian Symposium of Theoretical Chemistry (SBQT2021)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bispo, Matheus de Oliveira</creatorcontrib><creatorcontrib>Filho, Demétrio Antônio da Silva</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of molecular modeling</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bispo, Matheus de Oliveira</au><au>Filho, Demétrio Antônio da Silva</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Long-range parameter optimization for a better description of potential energy surfaces using Density Functional Theory</atitle><jtitle>Journal of molecular modeling</jtitle><stitle>J Mol Model</stitle><addtitle>J Mol Model</addtitle><date>2022-05-01</date><risdate>2022</risdate><volume>28</volume><issue>5</issue><spage>121</spage><epage>121</epage><pages>121-121</pages><artnum>121</artnum><issn>1610-2940</issn><eissn>0948-5023</eissn><abstract>The advance of computing and the development of modern quantum chemistry models such as Density Functional Theory (DFT) have allowed scientists to perform fast in silico studies with accurate results. It also allowed for the achievement of empirically unattainable quantities such as Potential Energy Surfaces (PES), a fundamental construct in various applications, such as the study of weakly bound systems. One of DFT’s current weaknesses is a reliable description of PESs, due to a lack of suitable exchange-correlation functionals. In general, other post-Hartree-Fock methods are employed, such as
n
th-order Møller-Plesset’s Perturbation Theory (MPn) or Coupled Cluster Theory (CCSD(T)) with large basis sets. Despite producing good results, these methods demand much computational power when applied to large systems. This work presents a novel approach of PES description of the
H
2
O
2
–Kr system using DFT by optimizing a long-range parameter present in some DFT functionals, obtaining results similar to those of the MPn methods with somewhat less computational time necessary.
Graphical Abstract
By optimizing the omega value of certain functionals, DFT can describe PESs with accuracy comparable to MP4 methods</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>35426616</pmid><doi>10.1007/s00894-022-05083-1</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-7103-4780</orcidid></addata></record> |
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subjects | Characterization and Evaluation of Materials Chemistry Chemistry and Materials Science Computer Appl. in Life Sciences Computer Applications in Chemistry Computing time Density functional theory Hydrogen peroxide Molecular Medicine Optimization Original Paper Parameters Perturbation theory Potential energy Production methods Quantum chemistry Theoretical and Computational Chemistry XXI-Brazilian Symposium of Theoretical Chemistry (SBQT2021) |
title | Long-range parameter optimization for a better description of potential energy surfaces using Density Functional Theory |
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