Hopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversion

Detalhes bibliográficos
Autor(a) principal: Bárbara Caroline Rodrigues de Araujo
Data de Publicação: 2020
Outros Autores: Felipe Silva Carvalho, Maria Betânia de Freitas Marques, João Pedro Braga, Rita de Cássia de Oliveira Sebastião
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFMG
Texto Completo: http://hdl.handle.net/1843/40951
Resumo: CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
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spelling 2022-04-09T00:24:06Z2022-04-09T00:24:06Z2020-073171392140010.21577/0103-5053.202000240103-5053http://hdl.handle.net/1843/40951CNPq - Conselho Nacional de Desenvolvimento Científico e TecnológicoFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas GeraisCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorA general kinetic equation to simulate differential scanning calorimetry (DSC) data was employed along this work. Random noises are used to generate a thousand data, which are considered to evaluate the performance of Levenberg-Marquardt (LM) and a Hopfield neural network (HNN) based algorithm in the fitting process. The HNN-based algorithm showed better results for two different initial conditions: exact and approximated values. After this statistical analysis, DSC experimental data at three heating rates for losartan potassium, an antihypertensive drug, was adjusted by the HNN method using different initial conditions to obtain the activation energy and frequency factor. Additionally, it was possible to recover the parameters for the kinetic model with accuracy, showing that the conversion is described by a complex process, once these values do not correspond to any ideal models described in the literature.engUniversidade Federal de Minas GeraisUFMGBrasilFAR - DEPARTAMENTO DE ALIMENTOSICX - DEPARTAMENTO DE QUÍMICAJournal of the Brazilian Chemical SocietyAlgoritmoRede Neural HopfieldRedes neurais artificiaisCalorimetriaKinetic studyNeural networkThermal analysisDSCHopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversioninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttps://www.scielo.br/j/jbchs/a/Q4CmPZ9dzDc3CGKJGjk9kJx/?lang=enBárbara Caroline Rodrigues de AraujoFelipe Silva CarvalhoMaria Betânia de Freitas MarquesJoão Pedro BragaRita de Cássia de Oliveira Sebastiãoapplication/pdfinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/40951/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALHopfield Neural Network-Based Algorithm Applied to Differential Scanning Calorimetry Data for Kinetic Studies in Polymorphic Conversion.pdfHopfield Neural Network-Based Algorithm Applied to Differential Scanning Calorimetry Data for Kinetic Studies in Polymorphic Conversion.pdfapplication/pdf2454354https://repositorio.ufmg.br/bitstream/1843/40951/2/Hopfield%20Neural%20Network-Based%20Algorithm%20Applied%20to%20Differential%20Scanning%20Calorimetry%20Data%20for%20Kinetic%20Studies%20in%20Polymorphic%20Conversion.pdfacaf4c3aace1fefc028889c25d97f1b1MD521843/409512022-04-08 21:24:07.409oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2022-04-09T00:24:07Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.pt_BR.fl_str_mv Hopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversion
title Hopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversion
spellingShingle Hopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversion
Bárbara Caroline Rodrigues de Araujo
Kinetic study
Neural network
Thermal analysis
DSC
Algoritmo
Rede Neural Hopfield
Redes neurais artificiais
Calorimetria
title_short Hopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversion
title_full Hopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversion
title_fullStr Hopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversion
title_full_unstemmed Hopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversion
title_sort Hopfield neural network-based algorithm applied to differential scanning calorimetry data for kinetic studies in polymorphic conversion
author Bárbara Caroline Rodrigues de Araujo
author_facet Bárbara Caroline Rodrigues de Araujo
Felipe Silva Carvalho
Maria Betânia de Freitas Marques
João Pedro Braga
Rita de Cássia de Oliveira Sebastião
author_role author
author2 Felipe Silva Carvalho
Maria Betânia de Freitas Marques
João Pedro Braga
Rita de Cássia de Oliveira Sebastião
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Bárbara Caroline Rodrigues de Araujo
Felipe Silva Carvalho
Maria Betânia de Freitas Marques
João Pedro Braga
Rita de Cássia de Oliveira Sebastião
dc.subject.por.fl_str_mv Kinetic study
Neural network
Thermal analysis
DSC
topic Kinetic study
Neural network
Thermal analysis
DSC
Algoritmo
Rede Neural Hopfield
Redes neurais artificiais
Calorimetria
dc.subject.other.pt_BR.fl_str_mv Algoritmo
Rede Neural Hopfield
Redes neurais artificiais
Calorimetria
description CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
publishDate 2020
dc.date.issued.fl_str_mv 2020-07
dc.date.accessioned.fl_str_mv 2022-04-09T00:24:06Z
dc.date.available.fl_str_mv 2022-04-09T00:24:06Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1843/40951
dc.identifier.doi.pt_BR.fl_str_mv 10.21577/0103-5053.20200024
dc.identifier.issn.pt_BR.fl_str_mv 0103-5053
identifier_str_mv 10.21577/0103-5053.20200024
0103-5053
url http://hdl.handle.net/1843/40951
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.pt_BR.fl_str_mv Journal of the Brazilian Chemical Society
dc.rights.driver.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 Universidade Federal de Minas Gerais
dc.publisher.initials.fl_str_mv UFMG
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv FAR - DEPARTAMENTO DE ALIMENTOS
ICX - DEPARTAMENTO DE QUÍMICA
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Repositório Institucional da UFMG
collection Repositório Institucional da UFMG
bitstream.url.fl_str_mv https://repositorio.ufmg.br/bitstream/1843/40951/1/License.txt
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repository.name.fl_str_mv Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)
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