The accurate prediction of standard vaporization enthalpy (Δ vap H m°) for volatile organic
compounds (VOCs) is of paramount importance in environmental chemistry, industrial …

Gas-particle partitioning of secondary organic aerosols is impacted by particle phase state
and viscosity, which can be inferred from the glass transition temperature (Tg) of the …

Abstract Machine learning (ML) is an emerging approach for predicting molecular
properties. The prediction of the properties of energetic molecules by ML is still in its infancy …

Thermodynamic properites of molecules are used widely in the study of reactive processes.
Such properties are typically measured via experiments or calculated by a variety of …

The objective of this study is to provide a simple yet accurate theoretical strategy for the
prediction of the sublimation enthalpy of wide range organic contaminants only from their 3D …

Enthalpy of vaporization (ΔH vap) is a thermodynamic property associated with the dispersal
of Persistent Organic Pollutants (POPs) in the environment. Common problem in the …

This study proposes easy-to-apply machine learning-developed models, which predict four
flammability properties of pure organic compounds: the flash point, heat of combustion …

In spite of increasing importance of cyclic hydrocarbons in various chemical systems, studies
on the fundamental properties of these compounds, such as enthalpy of formation, are still …

Environmental properties of compounds provide significant information in treating organic
pollutants, which drives the chemical process and environmental science toward eco …

Chemical substances are essential in all aspects of human life, and understanding their
properties is essential for developing chemical systems. The properties of chemical species …