News
Predicting Templating Effects in Solid-Synthesis with Machine Learning
In collaborative work with the group of Bettina Lotsch (MPI Stuttgart), we just reported on the use of machine learning based classifiers to predict the templating effects of organic molecules in hybrid Antimony and Bismuth halides (out now in Chemistry of Materials). These kinds of tools allow chemists to rationally design solid state architectures, without the need of expensive trial-and-error experiments.