## 3 Results and Discussion
### High-Performance Thin-Layer Chromatography  
It is obvious that the four populations obtained with the deconvolution differ from the well-known SARA fractions that derive from a fractionation with solvents of different polarity [29]. Nevertheless, since there is an increase in molecular weight and state of aggregation that parallels the increase in polarity, it is interesting to investigate if the four populations and SARA fractions somehow correlate. For this reason, we can here introduce the only \"not-rheological\" data, which are the results of the HPTLC analysis (Table 5). The evolution of the composition clearly individuates the fractions most affected by aging. Saturates and asphaltenes do not change significantly, at least from a quantitative point of view. In contrast, a consistent number of aromatic molecules move toward the resin family due to oxidation. It is worth nothing that for aromatics and resins, the variation in composition is higher in the presence of clay. This seems to be in contrast with the anti-aging effect of clay observed until now through rheological data. However, if we define an aging index (\(AI_{SARA}\)) similar to \(AI_{P}\), the result is consistent with the previous ones, thus indicating that the aging indexes must take into account the whole composition.  
This is clarified in the last three columns of Table 6 that report the following aging indexes:  
\[AI_{ar}=\frac{(ar^{\%_{6}})_{a}}{(ar^{\%_{6}})_{u}}\;AI_{res}=\frac{(res\%_{6 })_{a}}{(res\%_{6})_{u}}\;AI_{SARA}=\frac{\left[\frac{(res^{\%_{6}+aspl\%_{ 0}})}{(sat^{\%_{6}+aspl\%_{0}})}\right]_{a}}{\left[\frac{(res^{\%_{6}+aspl\%_{ 0}})}{(sat^{\%_{6}+aspl\%_{0}})}\right]_{u}} \tag{22}\]  
where _sat_, _ar_, _res_, and _asph_ indicates saturates, aromatics, resins, and asphaltenes, respectively. The indexes that refer to a single population may give misleading information with regard to the global evolution with aging.  
Finally, in order to better visualize the affinity between the two kinds of populations, Figure 11 gives a picture of the above-supposed correlation by reporting the data of Table 6 without distinction between the B and LS-B binder. The _x_-axis is the relative percentage obtained with HPTLC and the _y_-axis is the percentage calculated with the _8_-method. The image confirms the parallelism between the _8_-method and HPTLC families. Saturates-P1 and asphaltenes-P4 do not change significantly, while the P2-aromatics and P3-resins populations have a higher sensitivity to aging. This is interesting food for thought. The prefix \"A\" in AMWD stands for apparent and is introduced to distinguish between data collected in solution (for example with gel permeation chromatography) and in bulk (rheology). Following the same reasoning, the four populations can be named A-MGD, which stands for apparent molecule groups dynamics and motions, which give an idea of how the composition/aggregation of the molecules' dynamic and motion changes with aging.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & **Saturates** & **Aromatics** & **Resins** & **Asphaltenes** & **AI\({}_{ar}\)** & **AI\({}_{res}\)** & **AI\({}_{SARA}\)** \\  & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **(\%)** & **AI\({}_{ar}\)** & **AI\({}_{res}\)** & **AI\({}_{SARA}\)** \\ \hline B & 10.7 & 50.1 & 25.0 & 14.2 & 1.00 & 1.00 & 1.00 \\ B25 & 9.8 & 46.0 & 31.8 & 12.4 & 0.72 & 1.29 & 1.48 \\ B40 & 10.9 & 43.5 & 33.4 & 12.2 & 0.65 & 1.35 & 1.72 \\ B65 & 10.6 & 39.9 & 37.4 & 12.1 & 0.64 & 1.29 & 1.56 \\ B90 & 9.2 & 40.0 & 38.5 & 12.3 & 0.69 & 1.31 & 1.67 \\ \hline LS-B & 10.1 & 54.2 & 22.1 & 13.6 & 1.00 & 1.00 & 1.00 \\ LS-B25 & 10.1 & 50.4 & 27.6 & 11.9 & 0.83 & 1.22 & 1.31 \\ LS-B40 & 10.3 & 49.4 & 29.1 & 11.2 & 0.70 & 1.26 & 1.45 \\ LS-B65 & 10.5 & 44.3 & 34.3 & 10.8 & 0.70 & 1.38 & 1.59 \\ LS-B90 & 10.4 & 40.9 & 38.1 & 10.6 & 0.77 & 1.36 & 1.53 \\ \hline \hline \end{tabular}
\end{table}
Table 6: SARA fractions from HPTLC.