Efficient Large-Scale STEM-EELS Simulations With Torched-TACAW
This work introduces a method called torched-TACAW to efficiently simulate electron energy loss spectra (EELS) from vibrational and magnon excitations in large material systems. By combining machine-learned interatomic potentials with supercell partitioning and on-the-fly data processing, the approach achieves near ab initio quality simulations for realistic, large structures containing defects or interfaces.