Twisted two-dimensional van der Waals heterostructures provide a fertile ground for tailoring electronic and structural properties.However,their vast configurational space poses challenges for systematic study.Here,we...Twisted two-dimensional van der Waals heterostructures provide a fertile ground for tailoring electronic and structural properties.However,their vast configurational space poses challenges for systematic study.Here,weintroduce SAMBA,an open-source,high-throughput Python workflowthat automates the generation,simulation,and analysis of twisted bilayers.Using the coincidence lattice method,we generate a comprehensive set of over 18,000 quasi-commensurable homo-and heterobilayer structures based on 63 experimentally reported monolayers,and perform DFT simulations on a growing subset.The resulting database includes symmetry,interlayer energetics,band alignment,and charge transfer.A detailed case study on graphene-jacutingaite illustrates the framework’s capabilities.This platform offers a robust foundation for data-driven discovery and the rational design of 2D materials with tunable properties.展开更多
基金support from the Brazilian agencies FAPESP (grants 23/12336-5, 23/09820-2 and FAPESP-CEPID 24/00989-7)CNPq (INCT - Materials Informatics) grant 157793/2025-7, and LNCC (Laboratório Nacional de Computação Científica) for computer time (Project didmat).
文摘Twisted two-dimensional van der Waals heterostructures provide a fertile ground for tailoring electronic and structural properties.However,their vast configurational space poses challenges for systematic study.Here,weintroduce SAMBA,an open-source,high-throughput Python workflowthat automates the generation,simulation,and analysis of twisted bilayers.Using the coincidence lattice method,we generate a comprehensive set of over 18,000 quasi-commensurable homo-and heterobilayer structures based on 63 experimentally reported monolayers,and perform DFT simulations on a growing subset.The resulting database includes symmetry,interlayer energetics,band alignment,and charge transfer.A detailed case study on graphene-jacutingaite illustrates the framework’s capabilities.This platform offers a robust foundation for data-driven discovery and the rational design of 2D materials with tunable properties.
