SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Química Nova (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422018000600628 |
Resumo: | Finding the most efficient solvent for a chemical reaction can demand costly experimental procedure and the screening is usually limited to few solvents. The use of theoretical methods could accelerate the search for the best solvent, able to promote most effective kinetics and thermodynamics of a reaction. In this work, it was proposed an automated procedure that calculates the solvent effect for a chemical reaction using all the 179 solvents available in SMD (solvation model density). The reaction of 2-bromoacetophenone with pyridine was used as a test. The SMD model correctly predicts the reactivity trends for five solvents, which experimental data are available. We have found that sulfolane, a less usual solvent, is the best one for this reaction. The present study points out that computational screening of large set of solvents using the SMD model is a viable approach and could be useful for chemical reactions optimization. |
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SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODELsolvent effectnucleophilic substitutionMenshutkin reactioncontinuum solvation modelFinding the most efficient solvent for a chemical reaction can demand costly experimental procedure and the screening is usually limited to few solvents. The use of theoretical methods could accelerate the search for the best solvent, able to promote most effective kinetics and thermodynamics of a reaction. In this work, it was proposed an automated procedure that calculates the solvent effect for a chemical reaction using all the 179 solvents available in SMD (solvation model density). The reaction of 2-bromoacetophenone with pyridine was used as a test. The SMD model correctly predicts the reactivity trends for five solvents, which experimental data are available. We have found that sulfolane, a less usual solvent, is the best one for this reaction. The present study points out that computational screening of large set of solvents using the SMD model is a viable approach and could be useful for chemical reactions optimization.Sociedade Brasileira de Química2018-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422018000600628Química Nova v.41 n.6 2018reponame:Química Nova (Online)instname:Sociedade Brasileira de Química (SBQ)instacron:SBQ10.21577/0100-4042.20170224info:eu-repo/semantics/openAccessDalessandro,Ellen V.Pliego Jr.,Josefredo R.eng2018-07-05T00:00:00Zoai:scielo:S0100-40422018000600628Revistahttps://www.scielo.br/j/qn/ONGhttps://old.scielo.br/oai/scielo-oai.phpquimicanova@sbq.org.br1678-70640100-4042opendoar:2018-07-05T00:00Química Nova (Online) - Sociedade Brasileira de Química (SBQ)false |
dc.title.none.fl_str_mv |
SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL |
title |
SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL |
spellingShingle |
SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL Dalessandro,Ellen V. solvent effect nucleophilic substitution Menshutkin reaction continuum solvation model |
title_short |
SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL |
title_full |
SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL |
title_fullStr |
SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL |
title_full_unstemmed |
SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL |
title_sort |
SOLVENT SELECTION FOR CHEMICAL REACTIONS: AUTOMATED COMPUTATIONAL SCREENING OF SOLVENTS USING THE SMD MODEL |
author |
Dalessandro,Ellen V. |
author_facet |
Dalessandro,Ellen V. Pliego Jr.,Josefredo R. |
author_role |
author |
author2 |
Pliego Jr.,Josefredo R. |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Dalessandro,Ellen V. Pliego Jr.,Josefredo R. |
dc.subject.por.fl_str_mv |
solvent effect nucleophilic substitution Menshutkin reaction continuum solvation model |
topic |
solvent effect nucleophilic substitution Menshutkin reaction continuum solvation model |
description |
Finding the most efficient solvent for a chemical reaction can demand costly experimental procedure and the screening is usually limited to few solvents. The use of theoretical methods could accelerate the search for the best solvent, able to promote most effective kinetics and thermodynamics of a reaction. In this work, it was proposed an automated procedure that calculates the solvent effect for a chemical reaction using all the 179 solvents available in SMD (solvation model density). The reaction of 2-bromoacetophenone with pyridine was used as a test. The SMD model correctly predicts the reactivity trends for five solvents, which experimental data are available. We have found that sulfolane, a less usual solvent, is the best one for this reaction. The present study points out that computational screening of large set of solvents using the SMD model is a viable approach and could be useful for chemical reactions optimization. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422018000600628 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422018000600628 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.21577/0100-4042.20170224 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
publisher.none.fl_str_mv |
Sociedade Brasileira de Química |
dc.source.none.fl_str_mv |
Química Nova v.41 n.6 2018 reponame:Química Nova (Online) instname:Sociedade Brasileira de Química (SBQ) instacron:SBQ |
instname_str |
Sociedade Brasileira de Química (SBQ) |
instacron_str |
SBQ |
institution |
SBQ |
reponame_str |
Química Nova (Online) |
collection |
Química Nova (Online) |
repository.name.fl_str_mv |
Química Nova (Online) - Sociedade Brasileira de Química (SBQ) |
repository.mail.fl_str_mv |
quimicanova@sbq.org.br |
_version_ |
1750318119163789312 |