Machine Learning Assisted Reconstruction of Local Electronic Structure of Non-Uniformly Strained MoS2
This study combines density functional theory with a recurrent neural network to demonstrate that biaxial bending-induced strain in wrinkled and nanobubbled MoS2 significantly outperforms uniaxial or in-plane strain in modifying electronic properties, offering a validated, computationally efficient framework for predicting local electronic structures in strained 2D semiconductors.