An international team of researchers has developed a new method for parameterizing machine-learning interatomic potentials (MLIP) to simulate magnetic materials, making the prediction of their properties much more reliable and accurate. A key feature of the new approach is that the models of interatomic interactions are trained on so-called “magnetic forces.”