The local environment of an atom describes the region of the crystal inside which the interactions of an atom with neighboring atoms are non-negligible. In our HydraGNN model, the size of the local environment can be adjusted through the radius cut-off, which is a tunable hyperparameter. On the one hand, increasing the radius cut-off allows to retain more information about the local structure of the crystal, with potential benefits in the predictive performance of the model. On the other hand, larger values of the radius cut-off we report the performance of the HydraGNN models using CGConv and PNAConv with values of the radius cut-off set to 3.0 Å, 5.0 Å, 6.9 Å, and 8.0 Å. The value 6.9 Å is considered because it corresponds to the value of the radius cut-off used by the EAM model that generated the training data. Although slight changes in the radius cut-off do not necessarily result in immediate changes of the predictive performance of the HydraGNN models, we can clearly see a change in performance comparing the results when the radius cut-off is equal to 3.0 Å and 8.0 Å, respectively. A very short cutoff radius of only 3.0 Å performs very poorly and has even problem predicting formation energies correctly with an MAE of 1.933 eV for the PNAConv architecture, whereas the improvement in extending the cutoff radius from 5.0 Å (MAE of 0.474 eV for PNAConv) to 8.0 Å (0.293 eV for PNAConv) with our computationally most expensive GCNN is less dramatic. The MAEs of the bulk modulus, on the other hand, are not varying smoothly as a function of the cutoff radius. This finding will be further discussed below.