Our society heavily depends on technology, which itself depends on materials with the right properties: a steel with the proper ductility and hardness to make a good knife, or a Li-compound with the proper lithium conductivity to make a good rechargeable battery. Industry constantly searches for materials with properties that are ever better suited for a particular application. Next to experimental search programs to improve properties, computational searching has become a mature member of the toolbox too. It can be faster and cheaper than lab work. We apply computational tools within quantum physics to predict the properties of inorganic crystalline materials, aiming either for improving fundamental understanding or for optimizing properties for industrial applications.