A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling

[EN]Levan nanoparticles formation is a complicated phenomenon involving simultaneously polymeric reaction kinetics and nanoparticles self-assembly theory. These phenomena are studied in this work with experimental and computationalmethodologies. Specifically, the effect of different parameters on le...

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Detalles Bibliográficos
Autores: González Garcinuño, Álvaro, Tabernero de Paz, Antonio, Marcelo, Gema, Martín del Valle, Eva María
Tipo de recurso: artículo
Estado:Versión borrador
Fecha de publicación:2020
País:España
Institución:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/168901
Acceso en línea:http://hdl.handle.net/10366/168901
Access Level:acceso abierto
Palabra clave:Levan
Kinetic modeling
Self-assembly
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spelling A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modelingGonzález Garcinuño, ÁlvaroTabernero de Paz, AntonioMarcelo, GemaMartín del Valle, Eva MaríaLevanKinetic modelingSelf-assembly[EN]Levan nanoparticles formation is a complicated phenomenon involving simultaneously polymeric reaction kinetics and nanoparticles self-assembly theory. These phenomena are studied in this work with experimental and computationalmethodologies. Specifically, the effect of different parameters on levan kinetics and nanoparticles production in a cell-free system environment have been studied. Results point out that 37 °C is the best temperature for synthesizing levan as well as the existence of a substrate inhibition effect for polymeric reaction. This work also highlights that raffinose can be used for producing and that an increase on the ratio enzymesubstrate increases the velocity of conversion. However, the previous experimental conditions did not produce an important effect on self-assembly formed levan nanoparticles (always 110 nm) as long as the required levan concentration (CAC) for nanoparticles reorganization is achieved. To have a better understanding of these results, a model was developed to explain numerically levan kinetics and nanoparticle self-assembly. This model was built by taking into account enzyme poisoning effect (also demonstrated experimentally) and a diffusion limited cluster model for the aggregation phenomenon. Simulation results fit properly experimental data and catalytic parameters as well as predicting accurately the value of CAC for producing its reorganization into nanoparticles by self-assembly.Elsevier202620262020info:eu-repo/semantics/articleinfo:eu-repo/semantics/drafthttp://hdl.handle.net/10366/168901reponame:GREDOS. Repositorio Institucional de la Universidad de Salamancainstname:Universidad de Salamanca (USAL)Inglésinfo:eu-repo/semantics/openAccessoai:gredos.usal.es:10366/1689012026-06-07T06:28:51Z
dc.title.none.fl_str_mv A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling
title A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling
spellingShingle A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling
González Garcinuño, Álvaro
Levan
Kinetic modeling
Self-assembly
title_short A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling
title_full A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling
title_fullStr A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling
title_full_unstemmed A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling
title_sort A comprehensive study on levan nanoparticles formation: Kinetics and self-assembly modeling
dc.creator.none.fl_str_mv González Garcinuño, Álvaro
Tabernero de Paz, Antonio
Marcelo, Gema
Martín del Valle, Eva María
author González Garcinuño, Álvaro
author_facet González Garcinuño, Álvaro
Tabernero de Paz, Antonio
Marcelo, Gema
Martín del Valle, Eva María
author_role author
author2 Tabernero de Paz, Antonio
Marcelo, Gema
Martín del Valle, Eva María
author2_role author
author
author
dc.subject.none.fl_str_mv Levan
Kinetic modeling
Self-assembly
topic Levan
Kinetic modeling
Self-assembly
description [EN]Levan nanoparticles formation is a complicated phenomenon involving simultaneously polymeric reaction kinetics and nanoparticles self-assembly theory. These phenomena are studied in this work with experimental and computationalmethodologies. Specifically, the effect of different parameters on levan kinetics and nanoparticles production in a cell-free system environment have been studied. Results point out that 37 °C is the best temperature for synthesizing levan as well as the existence of a substrate inhibition effect for polymeric reaction. This work also highlights that raffinose can be used for producing and that an increase on the ratio enzymesubstrate increases the velocity of conversion. However, the previous experimental conditions did not produce an important effect on self-assembly formed levan nanoparticles (always 110 nm) as long as the required levan concentration (CAC) for nanoparticles reorganization is achieved. To have a better understanding of these results, a model was developed to explain numerically levan kinetics and nanoparticle self-assembly. This model was built by taking into account enzyme poisoning effect (also demonstrated experimentally) and a diffusion limited cluster model for the aggregation phenomenon. Simulation results fit properly experimental data and catalytic parameters as well as predicting accurately the value of CAC for producing its reorganization into nanoparticles by self-assembly.
publishDate 2020
dc.date.none.fl_str_mv 2020
2026
2026
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/draft
format article
status_str draft
dc.identifier.none.fl_str_mv http://hdl.handle.net/10366/168901
url http://hdl.handle.net/10366/168901
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:GREDOS. Repositorio Institucional de la Universidad de Salamanca
instname:Universidad de Salamanca (USAL)
instname_str Universidad de Salamanca (USAL)
reponame_str GREDOS. Repositorio Institucional de la Universidad de Salamanca
collection GREDOS. Repositorio Institucional de la Universidad de Salamanca
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,812429

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