Fig. 1: Schematic overview of the process for constructing the MLFF.
From: DPmoire: a tool for constructing accurate machine learning force fields in moiré systems
Initially, an MLFF is generated for monolayer structures to stabilize subsequent molecular dynamics (MD) simulations for bilayer systems. We then create non-twisted bilayer structures with various stacking configurations, relax these structures, and run MD simulations using the VASP MLFF module to construct the training dataset. The coordinates (x and y) of a selected atom from each layer are maintained constant during relaxation to preserve the integrity of the stacking order. Subsequently, the twisted structures are relaxed using density functional theory (DFT) to generate the test dataset. The MLFF is ultimately trained on these collected datasets, ensuring it can accurately predict the physical behaviors of moiré systems.
