Correlating atomic structure with carrier transport in defective MoS2 with grain boundary via machine-learned potentials
Accurate modelling of defects in materials requires quantum-level fidelity, computational efficiency, and validation against application-relevant physical observables. Density functional theory (DFT) is reliable but prohibitively expensive for large defective systems. To address this, we use a machine-learned inter...