期刊
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
卷 191, 期 -, 页码 65-72出版社
ELSEVIER
DOI: 10.1016/j.chemolab.2019.06.006
关键词
Computer-aided design; Polymeric informatics; QSPR; Feature selection; Artificial intelligence; Material databases
类别
资金
- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Argentina [PIP 112-2012-0100471]
- Universidad Nacional del Sur (UNS), Bahia Blanca, Argentina [PGI 24/N042, PGI 24/ZM17]
- Spanish Ministry of Economy and Competitiveness
- European Regional Development Fund [TIN2015-64776-C3-2-R]
In Polymer Informatics, quantitative structure-property relationship (QSPR) modeling is an emerging approach for predicting relevant properties of polymers in the context of computer-aided design of industrial materials. Nevertheless, most QSPR models available in the literature use simplistic computational representations of polymers based on their structural repetitive unit. The aim of this work is to evaluate the effect of this simplification and to analyze new strategies to achieve alternative characterizations that capture the phenomenon of polydispersity. In particular, the experiments reported in this work are focused on three mechanical properties derived from the tensile test. The reported results revealed the disadvantages of using these simplified representations. Besides, we contributed with alternative representations for the databases of polymer molecular descriptors that achieved more realistic and accurate QSPR models.
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