The screening of novel materials with good performance and the modelling of quantitative
structure-activity relationships (QSARs), among other issues, are hot topics in the field of …

Owing to the rapid developments to improve the accuracy and efficiency of both
experimental and computational investigative methodologies, the massive amounts of data …

Machine learning algorithms are generally developed in computer science or adjacent
disciplines and find their way into chemical modeling by a process of diffusion. Though …

Selecting proper descriptors or features is one of the central problems in exploring structure–
activity relationships of materials using machine learning models. The current feature …

For a chemist who is concerned with the synthesis of new energetic compounds, it is
essential to be able to assess physical and thermodynamic properties, as well as the …

The sublimation enthalpy of energetic compounds is often predicted using quantum
chemistry (QC) based quantitative structure–property relationship (QC-QSPR), which is …

Cocrystallizing a given molecule with another can be useful for adjusting the physical
properties of molecules in the solid state. However, most combinations of molecules do not …

We present a large-scale study of the temperature-dependence of structures, free energy
differences and properties of polymorphic molecular organic crystals. Lattice-vibrational …

The aim of the present study was to develop a novel solubilization technique consisting of a
nano-cocrystal suspension by integrating cocrystal and nanocrystal formulation …

Kinetics can play an important role in the crystallization of molecules and can give rise to
polymorphism, the tendency of molecules to form more than one crystal structure. Current …