A high-throughput framework and database for twisted 2D van der Waals bilayers

Abstract 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 introduce SAMBA, an open-source, high-throughput Python workflow that 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.