This thesis investigates the structural, energetic, and electronic properties of two-dimensional (2D) materials, focusing on graphene, hexagonal boron nitride (hBN), transition metal dichalcogenides (TMDCs), and arsenic phosphide (AsP) bilayers, using dispersion-corrected density functional theory (DFT) and random Phase Approximation (RPA). Central to our analysis is the use of dispersion-corrected DFT methods, particularly the SCAN-rVV10 and PBE-rVV10L functionals, to accurately predict interlayer distances, interaction energies, and electronic properties. We assess these properties across a wide range of 2D materials in both homogeneous and heterostructured forms. This thesis demonstrates the effectiveness of standard DFT methods in predicting intralayer properties like bond lengths and lattice constants. However, it is the advanced London dispersion-corrected functionals, such as SCAN-rVV10, that are particularly effective in detailing interlayer distances and interactions. These interlayer phenomena are crucial for accurate material characterization and application. For instance, in homogeneous and heterostructured layered systems, SCAN-rVV10 accurately predicts interlayer distances and interaction energetics, aligning closely with experimental and higher-level theoretical RPA results. Moreover, in studying binding behavior, particularly for {Mo,Ti}S2 nanostructures interacting with organic molecules, we illustrate how molecular orientation and surface structure influence binding characteristics. This research emphasizes that molecule interactions at edge and basal plane sites are crucial for controlling the shape and growth of these nanostructures. Molecules often bind more strongly to edge sites, promoting edge passivation and vertical stacking, while basal plane interactions, especially with thiophene, favor lateral growth. In conclusion, this thesis not only advances our understanding of the fundamental properties of 2D materials but also provides crucial insights into the accuracy of DFT methods in predicting these properties. By identifying the strengths and limitations of different dispersion-corrected DFT methods, we open the way for more accurate computational research and practical applications of these materials. This comprehensive analysis bridges theoretical predictions with potential industrial applications, underscoring the transformative impact of 2D materials in science and technology.