fig9

Figure 9. Workflow of TensorAlloy. Atomic positions and cell tensors are transformed to universal tensor descriptors (UTDs) and various interaction potentials can be used to model the total energy. Atomic forces, stress tensors and Hessian matrices can be derived automatically. Physical constraints, like the equation of state or elastic constants, may be utilized in the training stage. Optimized potentials can be called either by C++ codes (LAMMPS for MD and TensorKMC for AKMC) or Python. EAM: Embedded atom method; ADP: angular-dependent potential; NNPs: neural network potentials.