Two-dimensional (2D) materials have already revolutionized science, and have the potential to revolutionize technology due to their unique properties [1–7]. Their electronic properties range from metallic to insulating.
2D semiconducting materials play a particularly important role, as they often combine high carrier mobility with presence of direct band gap and atomic-like thickness [2,8,9], thus offering the potential to replace the current semiconducting materials in high-mobility high-speed fast switching semiconductor devices requiring low-dimensions.
Despite their unique properties, 2D materials in their most natural form, may still not possess the desired properties. Such properties may be induced by tuning tools, such as layer engineering, or dielectric embedding. These tools interfere with both the quantum confinement and the screening via vacuum and, hence, have a pronounced effect on electronic properties. Both tools can be studied by computational methods, the most widely used being the Density Functional Theory (DFT).
DFT, while being computationally relatively cheap, heavily bias the electronic properties (band gaps [10]) as well as the structural properties (van der Waals (vdW) interactions in the vdW multilayers). To fix these biases, we propose to use the most accurate and numerically efficient, albeit also the most computationally demanding, stochastic quantum Monte Carlo (QMC) techniques.