Graph neural network force fields (GNNFFs). For many tasks in chemistry, molecular geometry and 3D structure is essential and string-based representations are not sufficient. Neural force fields (NFFs) are graph neural networks (GNNs) that take molecular geometries as inputs, described by a set of atomic numbers (Z 1 , ..., Z n |Z i ∈ N) and Cartesian coordinates ( r 1 , ..., r n | r i ∈ R 3 ). The NFF with parameters θ, f θ , predicts a real-valued energy Ê = f θ (X) for an atomistic configuration X. The NFF produces energyconserving atomic forces by differentiating the energies with respect to the atomic coordinates,