In week three of the academic year at the chemistry and materiomics programs of UHasselt, the students started to put their freshly gained new knowledge of weeks 1 and 2 into practice with a number of exercise classes.

For the second bachelor chemistry students, this meant performing their first calculations within the context of the course ** introduction to quantum chemistry**. At this point this is still very mathematical (

*e.g.*, calculating commutators) and abstract (

*e.g.*, normalizing a wave function or calculating the probability of finding a particle, given a simple wave function), but this will change, and chemical/physical meaning will slowly be introduced into the mathematical formalism. For the third bachelor chemistry, the course

**continued with perturbation theory, and we started with the variational method as well. The latter was introduced through the example of the H atom, for which the exact variational ground state was recovered starting from a well chosen trial wave function.**

*quantum and computational chemistry*In the master materiomics, the first master course ** fundamentals of materials modelling**, dove into the details underpinning DFT introducing concepts like pseudo-potentials, the frozen-core approximation, periodic boundary conditions etc. This knowledge was then put into practice during a second exercise session working on the supercomputer, as a last preparation for the practical lab exercise the following day. During this lab, the students used the supercomputer to calculate the Young modulus of two infinite linear polymers. An intense practical session which they all executed with great courage (remember 2 weeks ago they never heard of DFT, nor had they accessed a supercomputer). Their report for this practical will be part of their grade.

For the second master materiomics, the course focused on * Density Functional Theory* consisted of a discussion lecture, covering the topics the students studied during their self study assignments. In addition, I recorded two video lectures for the blended learning part of the course. For the course

*self study topics were covered in such a discussion lecture as well. In addition, the QM9 data set was investigated during an exercise session, as preparation for further detailed study.*

**Machine learning and artificial intelligence in modern materials science**At the end of this week, we have added another 16h of live lectures and ~1h of video lectures, putting our semester **total at 35h of live lectures**. Upwards and onward to week 4.