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Artículo

Computational modelling of mechanical properties for new polymeric materials with high molecular weight

Cravero, FiorellaIcon ; Martínez, María JimenaIcon ; Ponzoni, IgnacioIcon ; Diaz, Monica FatimaIcon
Fecha de publicación: 15/10/2019
Editorial: Elsevier Science
Revista: Chemometrics and Intelligent Laboratory Systems
ISSN: 0169-7439
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:
Otras Ciencias de la Computación e Información; Otras Ingeniería de los Materiales

Resumen

The field of polymeric materials is one of the most complex that exists. These materials have very high molecular weights and also a molecular weight distribution, which give them singular properties. The demand for new materials that suit specific applications is increasing. However, the development time of new materials from new molecular structures can take 10–20 years. For this reason, both the knowledge about the structure-property relationship and the creation of reliable databases are increasingly crucial, as they serve to generate predictive models with the aim of reducing development times. This challenge is attempted by polymer informatics. In the present work, we show results of in silico experimentation, using in-house databases, with the aim of generating Quantitative Structure-Property Relationship (QSPR) models to predict a property derived from the tensile test Tensile Modulus. Two models were reported, after several development stages: feature selection, QSPR modelling training and validation. Additionally, complete physicochemical discussions and interpretations were presented. The QSPR model could be used as a “virtual testing” that provides a property profile estimation for a new molecule before synthesis. Consequently, our model is expected to contribute in the design stage of new polymeric materials, drastically reducing costs and development times.
Palabras clave: MACHINE LEARNING , POLYDISPERSITY INDEX , POLYMER INFORMATICS , QSPR , TENSILE MODULUS
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info:eu-repo/semantics/restrictedAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/118250
URL: https://www.sciencedirect.com/science/article/abs/pii/S0169743919304186
DOI: https://doi.org/10.1016/j.chemolab.2019.103851
Colecciones
Articulos (ICIC)
Articulos de INSTITUTO DE CS. E INGENIERIA DE LA COMPUTACION
Articulos(PLAPIQUI)
Articulos de PLANTA PILOTO DE INGENIERIA QUIMICA (I)
Citación
Cravero, Fiorella; Martínez, María Jimena; Ponzoni, Ignacio; Diaz, Monica Fatima; Computational modelling of mechanical properties for new polymeric materials with high molecular weight; Elsevier Science; Chemometrics and Intelligent Laboratory Systems; 193; 15-10-2019; 1-12
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