With the growth of computational resources, the scope of electronic structure simulations has
increased greatly. Artificial intelligence and robust data analysis hold the promise to …

The discovery paradigm of drugs is rapidly growing due to advances in machine learning
(ML) and artificial intelligence (AI). This review covers myriad faces of AI and ML in drug …

Machine learning (ML) in the representation of molecular-orbital-based (MOB) features has
been shown to be an accurate and transferable approach to the prediction of post-Hartree …

Instant machine learning predictions of molecular properties are desirable for materials
design, but the predictive power of the methodology is mainly tested on well-known …

The degradation behaviour of magnesium and its alloys can be tuned by small organic
molecules. However, an automatic identification of effective organic additives within the vast …

Abstract Machine learning (ML) algorithms were explored for the classification of the UV–Vis
absorption spectrum of organic molecules based on molecular descriptors and fingerprints …

The ability to predict transport properties of liquids quickly and accurately will greatly
improve our understanding of fluid properties both in bulk and complex mixtures, as well as …

We introduce an unsupervised clustering algorithm to improve training efficiency and
accuracy in predicting energies using molecular-orbital-based machine learning (MOB-ML) …

Organic chemical structures encode information about a molecule's atom and bond
arrangement. The most established way to encode a molecular structure is through line …

A large amount of hybrid metal oxides can be proposed for detecting various gases from
rapidly developing of 2D materials and elemental doping technologies, and the key issue is …