ICIC   25583
INSTITUTO DE CIENCIAS E INGENIERIA DE LA COMPUTACION
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
A Database Curation for Prediction of the Refractive Index in the Virtual Testing of Polymeric Materials by using Machine Learning.
Autor/es:
PONZONI, IGNACIO; SCHUSTIK, SANTIAGO A.; DIAZ, MONICA F.; CRAVERO, FIORELLA
Lugar:
Bahía Blanca
Reunión:
Congreso; Xth International Conference of Production Research - Americas 2020; 2020
Resumen:
The aim of industry 4.0 is to promote productivity and innovation by incorporating emerging IT technologies, where machine learning is playing a central role in this industrial revolution. In this sense, the production of new materials could take advantage of novel virtual testing approaches based on data science for supporting the design of new polymers. Nevertheless, the lack of data for learning virtual testing models constitutes a hard challenge for progressing in these innovative techniques. Therefore, it is especially important to create reliable databases for polymer study and make them available to the scientific community. In this work, we have focused on the generation of a trustworthy database of Refractive Index (RI) of synthetic polymers. This paper details the different types of errors found in the data source and the corrections made during the curation and cleaning of this database. Additionally, some Quantitative Structure-Property Relationship models for predicting RI, inferred without domain expert intervention, are presented and discussed for illustrating how virtual testing can be applied using this database.