First-Principles and Machine Learning Study of ML- P 4/ mmm -LaBr2: A Promising Flexible Electronic Material

Abstract

Flexible electronic materials are essential for the development of next-generation devices that maintain reliable performance under mechanical deformation such as bending and stretching. In this work, we propose a novel monolayer compound, P4/mmm LaBr2 (denoted as “ML-P4/mmm-LaBr2”), discovered via high-pressure crystal structure prediction and characterized by first-principles and machine learning study, as a promising candidate for flexible electronics. The I4/mmm LaBr2 parent phase is thermodynamically stable at ambient pressure, and its monolayer can be exfoliated with a cleavage energy comparable to established 2D materials such as graphene, MoS2, and black phosphorus. The average Young’s modulus E and shear modulus G of ML-P4/mmm-LaBr2 are calculated to be 55.8 and 23.0 N/m, respectively, indicating moderate mechanical flexibility. Electron–phonon coupling calculations reveal an exceptional electrical conductivity of 4.9 × 106 S/m (sheet conductance 3.1 mS) at 300 K, and a qualitative strain analysis indicates that this high conductivity is retained under small biaxial strains. Machine-learning molecular dynamics yields a low lattice thermal conductivity of 7.0 ± 0.2 W/(m·K). We further show that the monolayer tolerates moisture and intrinsic point defects, though oxygen sensitivity necessitates inert-atmosphere handling. These results suggest that ML-P4/mmm-LaBr2 is a promising candidate for flexible electronic applications, provided that appropriate encapsulation strategies are employed to mitigate its oxygen sensitivity.