$polymer refractive index database$

$polymer refractive index database$

In addition, we contrast the best models obtained by both approaches against two other predictive models for RI estimation reported in the literature, achieving promising performances in terms of cardinality and accuracy when the expert interacts during modeling. In this regard, visual analytics strategies were used to capture the expert’s knowledge, facilitating an effective and rapid interaction between the outputs provided by ML and the chemical analyst. In this article, we present the design of QSPR models for RI modeling following two different approaches, a black-box ML methodology and an Interactive Machine Learning (IML) methodology with expert-in-the-loop, from a database whose curation is also described in the present work.

$polymer refractive index database$ $polymer refractive index database$

For this reason, interactive ML methodologies that combine computational outputs with experts’ knowledge, usually known as expert-in-the-loop strategies, are becoming more frequent. However, in many cases, it has been observed that using ML algorithms in a fully automatic way, without human intervention in the QSPR model design process, tend to generate black-box models that have a difficult interpretation and can lose sight about relevant aspects that require both criteria and an expert’s knowledge in the chemical domain. In particular, the development of Quantitative Structure-Property Relationship (QSPR) models has benefited from these emerging technologies, providing the possibility of generating in silico testing strategies applicable to the early stages of the design of new materials. Over the last decades, the use of Machine Learning (ML) algorithms in the modeling of properties for the design of new materials has been consolidated thanks to the gradual increase in the available databases. Therefore, the modeling and prediction of this property play a key role when characterizing and designing materials for these important industries. A particular case is that of plastic optical fibers, in which the information is transmitted by photons and then RI takes center stage. Refractive index (RI) is a highly relevant property for the design of new polymeric materials for very specific applications in the telecommunications industry, medicine, and analytical chemistry, among many others.

$polymer refractive index database$

Polymer refractive index database