Aqueous solution chemistry in silico and the role of data-driven approaches

Autores
Banerjee, Debarshi; Azizi, Khatereh; Egan, Colin K.; Donkor, Edward Danquah; Malosso, Cesare; Di Pino, Solana Magalí; Díaz Mirón, Gonzalo; Stella, Martina; Sormani, Giulia; Neza Hozana, Germaine; Monti, Marta; Morzan, Uriel; Rodriguez, Alex; Cassone, Giuseppe; Jelic, Asja; Scherlis Perel, Damian Ariel; Hassanali, Ali
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The use of computer simulations to study the properties of aqueous systems is, today more than ever, an active area of research. In this context, during the last decade there has been a tremendous growth in the use of data-driven approaches to develop more accurate potentials for water as well as to characterize its complexity in chemical and biological contexts. We highlight the progress, giving a historical context, on the path to the development of many-body and reactive potentials to model aqueous chemistry, including the role of machine learning strategies. We focus specifically on conceptual and methodological challenges along the way in performing simulations that seek to tackle problems in modeling the chemistry of aqueous solutions. In conclusion, we summarize our perspectives on the use and integration of advanced data-science techniques to provide chemical insights into physical chemistry and how this will influence computer simulations of aqueous systems in the future.
Fil: Banerjee, Debarshi. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Azizi, Khatereh. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Egan, Colin K.. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Donkor, Edward Danquah. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Malosso, Cesare. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Di Pino, Solana Magalí. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Díaz Mirón, Gonzalo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Stella, Martina. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Sormani, Giulia. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Neza Hozana, Germaine. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Monti, Marta. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Morzan, Uriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Rodriguez, Alex. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Cassone, Giuseppe. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Jelic, Asja. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Scherlis Perel, Damian Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Hassanali, Ali. The Abdus Salam. International Centre for Theoretical Physics; Italia
Materia
DFT
Molecular dyamics
water
machine learning
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/266159
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/266159
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Aqueous solution chemistry in silico and the role of data-driven approachesBanerjee, DebarshiAzizi, KhaterehEgan, Colin K.Donkor, Edward DanquahMalosso, CesareDi Pino, Solana MagalíDíaz Mirón, GonzaloStella, MartinaSormani, GiuliaNeza Hozana, GermaineMonti, MartaMorzan, UrielRodriguez, AlexCassone, GiuseppeJelic, AsjaScherlis Perel, Damian ArielHassanali, AliDFTMolecular dyamicswatermachine learninghttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1The use of computer simulations to study the properties of aqueous systems is, today more than ever, an active area of research. In this context, during the last decade there has been a tremendous growth in the use of data-driven approaches to develop more accurate potentials for water as well as to characterize its complexity in chemical and biological contexts. We highlight the progress, giving a historical context, on the path to the development of many-body and reactive potentials to model aqueous chemistry, including the role of machine learning strategies. We focus specifically on conceptual and methodological challenges along the way in performing simulations that seek to tackle problems in modeling the chemistry of aqueous solutions. In conclusion, we summarize our perspectives on the use and integration of advanced data-science techniques to provide chemical insights into physical chemistry and how this will influence computer simulations of aqueous systems in the future.Fil: Banerjee, Debarshi. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Azizi, Khatereh. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Egan, Colin K.. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Donkor, Edward Danquah. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Malosso, Cesare. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Di Pino, Solana Magalí. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; ArgentinaFil: Díaz Mirón, Gonzalo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; ArgentinaFil: Stella, Martina. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Sormani, Giulia. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Neza Hozana, Germaine. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Monti, Marta. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Morzan, Uriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Rodriguez, Alex. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Cassone, Giuseppe. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Jelic, Asja. The Abdus Salam. International Centre for Theoretical Physics; ItaliaFil: Scherlis Perel, Damian Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; ArgentinaFil: Hassanali, Ali. The Abdus Salam. International Centre for Theoretical Physics; ItaliaAmerican Institute of Physics2024-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/266159Banerjee, Debarshi; Azizi, Khatereh; Egan, Colin K.; Donkor, Edward Danquah; Malosso, Cesare; et al.; Aqueous solution chemistry in silico and the role of data-driven approaches; American Institute of Physics; Chemical Physics Reviews; 5; 2; 6-2024; 1-232688-4070CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://pubs.aip.org/cpr/article/5/2/021308/3300328/Aqueous-solution-chemistry-in-silico-and-the-roleinfo:eu-repo/semantics/altIdentifier/doi/10.1063/5.0207567info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:14:35Zoai:ri.conicet.gov.ar:11336/266159instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:14:35.741CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Aqueous solution chemistry in silico and the role of data-driven approaches
title Aqueous solution chemistry in silico and the role of data-driven approaches
spellingShingle Aqueous solution chemistry in silico and the role of data-driven approaches
Banerjee, Debarshi
DFT
Molecular dyamics
water
machine learning
title_short Aqueous solution chemistry in silico and the role of data-driven approaches
title_full Aqueous solution chemistry in silico and the role of data-driven approaches
title_fullStr Aqueous solution chemistry in silico and the role of data-driven approaches
title_full_unstemmed Aqueous solution chemistry in silico and the role of data-driven approaches
title_sort Aqueous solution chemistry in silico and the role of data-driven approaches
dc.creator.none.fl_str_mv Banerjee, Debarshi
Azizi, Khatereh
Egan, Colin K.
Donkor, Edward Danquah
Malosso, Cesare
Di Pino, Solana Magalí
Díaz Mirón, Gonzalo
Stella, Martina
Sormani, Giulia
Neza Hozana, Germaine
Monti, Marta
Morzan, Uriel
Rodriguez, Alex
Cassone, Giuseppe
Jelic, Asja
Scherlis Perel, Damian Ariel
Hassanali, Ali
author Banerjee, Debarshi
author_facet Banerjee, Debarshi
Azizi, Khatereh
Egan, Colin K.
Donkor, Edward Danquah
Malosso, Cesare
Di Pino, Solana Magalí
Díaz Mirón, Gonzalo
Stella, Martina
Sormani, Giulia
Neza Hozana, Germaine
Monti, Marta
Morzan, Uriel
Rodriguez, Alex
Cassone, Giuseppe
Jelic, Asja
Scherlis Perel, Damian Ariel
Hassanali, Ali
author_role author
author2 Azizi, Khatereh
Egan, Colin K.
Donkor, Edward Danquah
Malosso, Cesare
Di Pino, Solana Magalí
Díaz Mirón, Gonzalo
Stella, Martina
Sormani, Giulia
Neza Hozana, Germaine
Monti, Marta
Morzan, Uriel
Rodriguez, Alex
Cassone, Giuseppe
Jelic, Asja
Scherlis Perel, Damian Ariel
Hassanali, Ali
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv DFT
Molecular dyamics
water
machine learning
topic DFT
Molecular dyamics
water
machine learning
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The use of computer simulations to study the properties of aqueous systems is, today more than ever, an active area of research. In this context, during the last decade there has been a tremendous growth in the use of data-driven approaches to develop more accurate potentials for water as well as to characterize its complexity in chemical and biological contexts. We highlight the progress, giving a historical context, on the path to the development of many-body and reactive potentials to model aqueous chemistry, including the role of machine learning strategies. We focus specifically on conceptual and methodological challenges along the way in performing simulations that seek to tackle problems in modeling the chemistry of aqueous solutions. In conclusion, we summarize our perspectives on the use and integration of advanced data-science techniques to provide chemical insights into physical chemistry and how this will influence computer simulations of aqueous systems in the future.
Fil: Banerjee, Debarshi. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Azizi, Khatereh. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Egan, Colin K.. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Donkor, Edward Danquah. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Malosso, Cesare. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Di Pino, Solana Magalí. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Díaz Mirón, Gonzalo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Stella, Martina. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Sormani, Giulia. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Neza Hozana, Germaine. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Monti, Marta. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Morzan, Uriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; Argentina
Fil: Rodriguez, Alex. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Cassone, Giuseppe. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Jelic, Asja. The Abdus Salam. International Centre for Theoretical Physics; Italia
Fil: Scherlis Perel, Damian Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química, Física de los Materiales, Medioambiente y Energía. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Química, Física de los Materiales, Medioambiente y Energía; Argentina
Fil: Hassanali, Ali. The Abdus Salam. International Centre for Theoretical Physics; Italia
description The use of computer simulations to study the properties of aqueous systems is, today more than ever, an active area of research. In this context, during the last decade there has been a tremendous growth in the use of data-driven approaches to develop more accurate potentials for water as well as to characterize its complexity in chemical and biological contexts. We highlight the progress, giving a historical context, on the path to the development of many-body and reactive potentials to model aqueous chemistry, including the role of machine learning strategies. We focus specifically on conceptual and methodological challenges along the way in performing simulations that seek to tackle problems in modeling the chemistry of aqueous solutions. In conclusion, we summarize our perspectives on the use and integration of advanced data-science techniques to provide chemical insights into physical chemistry and how this will influence computer simulations of aqueous systems in the future.
publishDate 2024
dc.date.none.fl_str_mv 2024-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/266159
Banerjee, Debarshi; Azizi, Khatereh; Egan, Colin K.; Donkor, Edward Danquah; Malosso, Cesare; et al.; Aqueous solution chemistry in silico and the role of data-driven approaches; American Institute of Physics; Chemical Physics Reviews; 5; 2; 6-2024; 1-23
2688-4070
CONICET Digital
CONICET
url http://hdl.handle.net/11336/266159
identifier_str_mv Banerjee, Debarshi; Azizi, Khatereh; Egan, Colin K.; Donkor, Edward Danquah; Malosso, Cesare; et al.; Aqueous solution chemistry in silico and the role of data-driven approaches; American Institute of Physics; Chemical Physics Reviews; 5; 2; 6-2024; 1-23
2688-4070
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://pubs.aip.org/cpr/article/5/2/021308/3300328/Aqueous-solution-chemistry-in-silico-and-the-role
info:eu-repo/semantics/altIdentifier/doi/10.1063/5.0207567
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Institute of Physics
publisher.none.fl_str_mv American Institute of Physics
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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