Insights into modeling refractive index of ionic liquids using chemical structure-based machine learning methods

Insights into modeling refractive index of ionic liquids using chemical structure-based machine learning methods

Abstract Ionic liquids (ILs) have drawn much attention due to their extensive applications and environment-friendly nature. Refractive index prediction is valuable for ILs quality control and property characterization. This paper aims to predict refractive indices of pure ILs and identify factors in...

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Bibliographic Details
Main Authors: Ali Esmaeili, Hesamedin Hekmatmehr, Saeid Atashrouz, Seyed Ali Madani, Maryam Pourmahdi, Dragutin Nedeljkovic, Abdolhossein Hemmati-Sarapardeh, Ahmad Mohaddespour
Format: Article
Language:English
Published: Nature Portfolio 2023-07-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-39079-5

Internet

https://doi.org/10.1038/s41598-023-39079-5

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