New QSPRs for Liquid Heat Capacity

Quantitative Structure-Property Relationships (QSPRs) have found applications in many areas of chemistry and engineering as effective prediction methods. QSPRs use molecular descriptors to simplify complex molecular properties to a single value and have been used extensively for constant value properties. Liquid heat capacity (cpl ) is another property where QSPRs can be helpful prediction tools. Researchers have shown strong correlation between the cpl and various molecular descriptors, but these predictions are limited to a single temperature, usually 298.15 K. Additionally, other QSPRs have had problems with oxygen-containing functional groups. In this work, QSPRs for cpl at various temperatures were developed using data selected from the DIPPR database using a novel search method. This method improves on existing QSPRs for cpl by using unique descriptors but does not overcome the issue of oxygen-containing species.

Automated summary

Quantitative Structure-Property Relationships (QSPRs) are widely used in chemistry and engineering for predicting complex molecular properties. However, existing QSPRs for liquid heat capacity (cpl) are limited to single temperatures and have issues with oxygen-containing functional groups.