T.E. de Vries (Tom) MSc
Promovendus - Solid State Chemistry
6525 AJ NIJMEGEN
Interne postcode: 23
6500 GL NIJMEGEN
Many useful crystals like active pharmaceutical ingredients (APIs), agrochemicals and pigments possess certain properties that make them unsuitable for their intended purpose. These properties include things like solubility, bioavailability and taste. These properties can be modified by using multi-component crystals, which are crystals composed of a combination of the target chemical and another compound. Experimentally finding compounds that will form multi-component crystals with a target chemical is time-consuming and labor intensive. In this project, we develop computational tools to predict possible multi-component crystals using network science and machine learning techniques. These tools can help shorten the time needed to find useful multi-component crystals.