New QSPRs for Liquid Heat Capacity

Abstract

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 ( $c_p^l$ ) is another property where QSPRs can be helpful prediction tools. Researchers have shown strong correlation between the $c_p^l$ 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 $c_p^l$ at various temperatures were developed using data selected from the DIPPR database using a novel search method. This method improves on existing QSPRs for $c_p^l$ by using unique descriptors but does not overcome the issue of oxygen-containing species.

Keywords: QSAR; QSPR; database; liquid heat capacity.