Please use this identifier to cite or link to this item:
https://hdl.handle.net/1959.11/56022
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DC Field | Value | Language |
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dc.contributor.author | Santra, Golokesh | en |
dc.contributor.author | Semidalas, Emmanouil | en |
dc.contributor.author | Mehta, Nisha | en |
dc.contributor.author | Karton, Amir | en |
dc.contributor.author | Martin, Jan M L | en |
dc.date.accessioned | 2023-09-12T04:25:09Z | - |
dc.date.available | 2023-09-12T04:25:09Z | - |
dc.date.issued | 2022-11-07 | - |
dc.identifier.citation | Physical Chemistry Chemical Physics, 24(41), p. 25555-25570 | en |
dc.identifier.issn | 1463-9084 | en |
dc.identifier.issn | 1463-9076 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/56022 | - |
dc.description.abstract | <p>The S66x8 noncovalent interactions benchmark has been re-evaluated at the "sterling silver" level, using explicitly correlated MP2-F12 near the complete basis set limit, CCSD(F12*)/aug-cc-pVTZ-F12, and a (T) correction from conventional CCSD(T)/sano-V{D,T}Z+ calculations. The revised reference values differ by 0.1 kcal mol<sup>-1</sup> RMS from the original Hobza benchmark and its revision by Brauer et al., but by only 0.04 kcal mol<sup>-1</sup> RMS from the "bronze" level data in Kesharwani <i>et al., Aust. J. Chem.,</i> 2018, <b>71</b>, 238– 248. We then used these to assess the performance of localized-orbital coupled cluster approaches with and without counterpoise corrections, such as PNO-LCCSD(T) as implemented in MOLPRO, DLPNO-CCSD(T<sub>1</sub>) as implemented in ORCA, and LNO-CCSD(T) as implemented in MRCC, for their respective "Normal", "Tight", and "very Tight" settings. We also considered composite approaches combining different basis sets and cutoffs. Furthermore, in order to isolate basis set convergence from domain truncation error, for the aug-cc-pVTZ basis set we compared PNO, DLPNO, and LNO approaches with canonical CCSD(T). We conclude that LNO-CCSD(T) with very tight criteria performs very well for "raw" (CP-uncorrected), but struggles to reproduce counterpoise-corrected numbers even for very very criteria: this means that accurate results can be obtained using either extrapolation from basis sets large enough to quench basis set superposition error (BSSE) such as aug-cc-pV{Q,5}Z, or using a composite scheme such as Tight{T,Q} + 1.11[vvTight(T) Tight(T)]. In contrast, PNO-LCCSD(T) works best with counterpoise, while performance with and without counterpoise is comparable for DLPNO-CCSD(T<sub>1</sub>). Among more economical methods, the highest accuracies are seen for dRPA75- D3BJ, ωB97M-V, ωB97M(2), revDSD-PBEP86-D4, and DFT(SAPT) with a TDEXX or ATDEXX kernel.</p> | en |
dc.language | en | en |
dc.publisher | Royal Society of Chemistry | en |
dc.relation.ispartof | Physical Chemistry Chemical Physics | en |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.title | S66x8 noncovalent interactions revisited: new benchmark and performance of composite localized coupled-cluster methods | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1039/D2CP03938A | en |
dcterms.accessRights | UNE Green | en |
local.contributor.firstname | Golokesh | en |
local.contributor.firstname | Emmanouil | en |
local.contributor.firstname | Nisha | en |
local.contributor.firstname | Amir | en |
local.contributor.firstname | Jan M L | en |
local.relation.isfundedby | ARC | en |
local.profile.school | School of Science and Technology | en |
local.profile.email | akarton@une.edu.au | en |
local.output.category | C1 | en |
local.grant.number | FT170100373 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.publisher.place | United Kingdom | en |
local.format.startpage | 25555 | en |
local.format.endpage | 25570 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 24 | en |
local.identifier.issue | 41 | en |
local.title.subtitle | new benchmark and performance of composite localized coupled-cluster methods | en |
local.access.fulltext | Yes | en |
local.contributor.lastname | Santra | en |
local.contributor.lastname | Semidalas | en |
local.contributor.lastname | Mehta | en |
local.contributor.lastname | Karton | en |
local.contributor.lastname | Martin | en |
dc.identifier.staff | une-id:akarton | en |
local.profile.orcid | 0000-0002-7981-508X | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/56022 | en |
local.date.onlineversion | 2022-10-11 | - |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | S66x8 noncovalent interactions revisited | en |
local.relation.fundingsourcenote | This research was funded by the Israel Science Foundation (grant 1969/20), the Minerva Foundation (grant 20/05), as well as by a research grant from the Artificial Intelligence and Smart Materials Research Fund, in Memory of Dr Uriel Arnon, Israel. GS acknowledges a doctoral fellowship from the Feinberg Graduate School (WIS). The work of E. S. on this scientific paper was supported by the Onassis Foundation—Scholarship ID: FZP 052-2/2021-2022. | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.relation.grantdescription | ARC/FT170100373 | en |
local.search.author | Santra, Golokesh | en |
local.search.author | Semidalas, Emmanouil | en |
local.search.author | Mehta, Nisha | en |
local.search.author | Karton, Amir | en |
local.search.author | Martin, Jan M L | en |
local.open.fileurl | https://rune.une.edu.au/web/retrieve/2e2ca4b6-39ee-4238-967a-9c87d3d41d9c | en |
local.uneassociation | Yes | en |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.year.available | 2022 | en |
local.year.published | 2022 | en |
local.fileurl.open | https://rune.une.edu.au/web/retrieve/2e2ca4b6-39ee-4238-967a-9c87d3d41d9c | en |
local.fileurl.openpublished | https://rune.une.edu.au/web/retrieve/2e2ca4b6-39ee-4238-967a-9c87d3d41d9c | en |
local.subject.for2020 | 340701 Computational chemistry | en |
local.subject.seo2020 | 280120 Expanding knowledge in the physical sciences | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
local.profile.affiliationtype | UNE Affiliation | en |
local.profile.affiliationtype | External Affiliation | en |
Appears in Collections: | Journal Article School of Science and Technology |
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openpublished/S66x8NoncovalentKarton2022JournalArticle.pdf | Published Version | 3.45 MB | Adobe PDF Download Adobe | View/Open |
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