Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ Clusters

We present a computational investigation on the structural arrangements and energetic stabilities of small-size protonated argon clusters, Ar H + . Using high-level ab initio electronic structure computations, we determined that the linear symmetric triatomic ArH + Ar ion serves as the molecular cor...

Descripción completa

Detalles Bibliográficos
Autores: Montes de Oca, Judit, Prosmiti, Rita
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/367055
Acceso en línea:http://hdl.handle.net/10261/367055
Access Level:acceso abierto
Palabra clave:ab initio electronic structure calculations
Molecular interactions
Machine learning potentials
Noble gas proton-bound clusters
Microsolvation structures
id ES_ab09d0ebdfcf2e959bed65b6e2a6ff01
oai_identifier_str oai:digital.csic.es:10261/367055
network_acronym_str ES
network_name_str España
repository_id_str
spelling Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ ClustersMontes de Oca, JuditProsmiti, Ritaab initio electronic structure calculationsMolecular interactionsMachine learning potentialsNoble gas proton-bound clustersMicrosolvation structuresWe present a computational investigation on the structural arrangements and energetic stabilities of small-size protonated argon clusters, Ar H + . Using high-level ab initio electronic structure computations, we determined that the linear symmetric triatomic ArH + Ar ion serves as the molecular core for all larger clusters studied. Through harmonic normal-mode analysis for clusters containing up to seven argon atoms, we observed that the proton-shared vibration shifts to lower frequencies, consistent with measurements in gas-phase IRPD and solid Ar-matrix isolation experiments. We explored the sum-of-potentials approach by employing kernel-based machine-learning potential models trained on CCSD(T)-F12 data. These models included expansions of up to two-body, three-body, and four-body terms to represent the underlying interactions as the number of Ar atoms increases. Our results indicate that the four-body contributions are crucial for accurately describing the potential surfaces in clusters with > 3. Using these potential models and an evolutionary programming method, we analyzed the structural stability of clusters with up to 24 Ar atoms. The most energetically favored Ar H + structures were identified for magic size clusters at n = 7, 13, and 19, corresponding to the formation of Ar-pentagon rings perpendicular to the ArH + Ar core ion axis. The sequential formation of such regular shell structures is compared to ion yield data from high-resolution mass spectrometry measurements. Our results demonstrate the effectiveness of the developed sum-of-potentials model in describing trends in the nature of bonding during the single proton microsolvation by Ar atoms, encouraging further quantum nuclear studies.This research was funded by MCIN grant No. PID2020-114654GB-I00, Comunidad de Madrid grant No. IND2018/TIC-9467, CSIC-PEICT Ref: 2024AEP119, and COST Actions CA18212(MD-GAS), CA21101(COSY) and CA21126(NanoSpace)Peer reviewedMultidisciplinary Digital Publishing InstituteMinisterio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)Comunidad de MadridConsejo Superior de Investigaciones Científicas (España)European Cooperation in Science and TechnologyConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]2024202420242024info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/367055reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114654GB-I00IND2018/TIC-9467https://doi.org/10.3390/molecules29174084Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3670552026-05-22T06:33:51Z
dc.title.none.fl_str_mv Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ Clusters
title Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ Clusters
spellingShingle Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ Clusters
Montes de Oca, Judit
ab initio electronic structure calculations
Molecular interactions
Machine learning potentials
Noble gas proton-bound clusters
Microsolvation structures
title_short Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ Clusters
title_full Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ Clusters
title_fullStr Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ Clusters
title_full_unstemmed Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ Clusters
title_sort Microsolvation of a Proton by Ar Atoms: Structures and Energetics of ArnH+ Clusters
dc.creator.none.fl_str_mv Montes de Oca, Judit
Prosmiti, Rita
author Montes de Oca, Judit
author_facet Montes de Oca, Judit
Prosmiti, Rita
author_role author
author2 Prosmiti, Rita
author2_role author
dc.contributor.none.fl_str_mv Ministerio de Ciencia, Innovación y Universidades (España)
Agencia Estatal de Investigación (España)
Comunidad de Madrid
Consejo Superior de Investigaciones Científicas (España)
European Cooperation in Science and Technology
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv ab initio electronic structure calculations
Molecular interactions
Machine learning potentials
Noble gas proton-bound clusters
Microsolvation structures
topic ab initio electronic structure calculations
Molecular interactions
Machine learning potentials
Noble gas proton-bound clusters
Microsolvation structures
description We present a computational investigation on the structural arrangements and energetic stabilities of small-size protonated argon clusters, Ar H + . Using high-level ab initio electronic structure computations, we determined that the linear symmetric triatomic ArH + Ar ion serves as the molecular core for all larger clusters studied. Through harmonic normal-mode analysis for clusters containing up to seven argon atoms, we observed that the proton-shared vibration shifts to lower frequencies, consistent with measurements in gas-phase IRPD and solid Ar-matrix isolation experiments. We explored the sum-of-potentials approach by employing kernel-based machine-learning potential models trained on CCSD(T)-F12 data. These models included expansions of up to two-body, three-body, and four-body terms to represent the underlying interactions as the number of Ar atoms increases. Our results indicate that the four-body contributions are crucial for accurately describing the potential surfaces in clusters with > 3. Using these potential models and an evolutionary programming method, we analyzed the structural stability of clusters with up to 24 Ar atoms. The most energetically favored Ar H + structures were identified for magic size clusters at n = 7, 13, and 19, corresponding to the formation of Ar-pentagon rings perpendicular to the ArH + Ar core ion axis. The sequential formation of such regular shell structures is compared to ion yield data from high-resolution mass spectrometry measurements. Our results demonstrate the effectiveness of the developed sum-of-potentials model in describing trends in the nature of bonding during the single proton microsolvation by Ar atoms, encouraging further quantum nuclear studies.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Publisher's version
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/367055
url http://hdl.handle.net/10261/367055
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
#PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114654GB-I00
IND2018/TIC-9467
https://doi.org/10.3390/molecules29174084
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869416233817866240
score 15,811543

Similares en LA Referencia