Electron configuration-based neural network model to predict physicochemical properties of inorganic compounds.

ABSTRACT: Registration, evaluation, and authorization of chemicals (REACH), the regulation of chemicals in use, imposes the characterization and report of the physicochemical properties of compounds. To cope with the financial burden of the experiments, the use of computational models is permitted for prediction of properties. Although a number of physicochemical property prediction models have been developed, their applicability domain is limited to organic molecules since most available data are concerned with organic molecules, and most of the molecular descriptors are restricted to organic molecule calculations. Prediction models developed for inorganic compounds were intended to predict endpoints relevant to novel material design. Therefore, no models were available for predicting endpoints of

SUBMITTER: Shin HK 

PROVIDER: S-EPMC9056678 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature