## 4 Discussion  
The Raman enhancement is highest for substrate A and B, and the Raman spectral maxima of Rhodamine B can be identified down to concentrations of \(10^{-12}\) M. The structure of these two substrates is largely more chaotic, and although the feature sizes are around 100 nm, the distances between them at multiple locations are less than that. Substrate C, on the other hand, features a highly periodic arrangement of feature sizes around 20 nm; however, the minimal interstructural distances between them appear to be on average larger than for substrates A and B, which leads to a lower enhancement. These two substrates also have a layered structure with considerable depth between the nanostructures. This also leads to an overall higher chance of the analyte molecule falling in-between them and experiencing a larger Raman enhancement. Substrate C is more or less single-layered. The surface maps show that substrate B is the most uniform one in terms of enhancement. Our hypothesis seems to be substantiated, that is, a more bottom-up and controlled approach where the nanostructures are more periodic is great for obtaining small feature sizes; however, the artificial nature of such structures means that any kind of fractality and added detail needs to be manually engineered--something that takes more time and effort. In contrast, nanostructures which are more chaotic, often obtained from somewhat stochastic chemical processes, feature more complexity and small-scale detail without much added time and energy required. As such, it appears that substrates obtained by methods employing stochastic physical processes could yield a higher SERS enhancement factor. It must be mentioned, however, that a method such as electron-beam lithography could potentially allow for such small-scale structuring (with interstructural distances on the order of 10 nm) that would surpass the benefit of the more chaotic substrates. This direction could potentially be pursued in future research. This fact about chaotic arrangements generally leading to higher enhancement is also hinted at by FEM models. The substrate model featuring a larger variation in distances and containing more detail shows a larger enhancement than the substrate model containing more periodic arrangements. All of the substrates presented in this work showed respectable performance and the large amount of work, presented both here and in many research papers in the past 50 years, repeatedly proves the powerfulness of the SERS method. There are, however, nuances regarding SERS, some of which are an impediment to its successful implementation in analysis, especially quantitative. The first, and most obvious one, is the fact that any molecule which happens to be adsorbed on the surface adds its own Raman spectrum, as well as possible fluorescence. The most common is the aforementioned amorphous carbon. Although conditions can be controlled in the lab to minimise the chance of this happening, real-world applications often involve highly impure samples. Possibly a combination of SERS and resonance Raman spectroscopy (SERRS) helps to more selectively enhance the analyte's spectrum. Secondly, the reusability of substrates is somewhat limited, since any deeper cleaning of the surface easily destroys the nanostructures themselves, reducing the enhancement efficiency of the active area. Thirdly, the use of the Raman peak intensity and the subsequent enhancement factor for quantitative analysis is quite prone to inducing measurement errors. This is because the SERS method is highly sensitive, which in turn means that it is also highly sensitive to any change in location of the analyte molecules in relation to the active surface and the incident laser spot.