The influence of solid state information and descriptor selection on statistical models of temperature dependent aqueous solubility.

ABSTRACT: Predicting the equilibrium solubility of organic, crystalline materials at all relevant temperatures is crucial to the digital design of manufacturing unit operations in the chemical industries. The work reported in our current publication builds upon the limited number of recently published quantitative structure-property relationship studies which modelled the temperature dependence of aqueous solubility. One set of models was built to directly predict temperature dependent solubility, including for materials with no solubility data at any temperature. We propose that a modified cross-validation protocol is required to evaluate these models. Another set of models was built to predict the related enthalpy of solution term, which can be used to estimate solubility at one temperature based

SUBMITTER: Marchese Robinson RL 

PROVIDER: S-EPMC6115327 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature