First, we simulate a 'neat' LJ liquid where all particles are assigned σ = 3.4 Å, sample the RDFs, and calculate the structure factor using eq. 15 at q = 0 Å-1 for gradually increasing truncations of the integral, R, S lm (0; R), towards convergence if the correction is successful. This type of plot is therefore a helpful tool in judging whether the low-q behaviour of the structure factor (and thus the scattering signal) will be influenced by finite-size sampling errors of the RDF. Since l ∈ v, m ∈ v, we label this structure factor S v (0; R). The top plot in fig. shows the LJ-potential (red line) used in sampling the RDF shown in black. The middle plot in the figure shows the structure factor S v (0; R), using the 'raw' RDF in the top plot, before applying any RDF-corrections (black dashed line). The plot also shows structure factors calculated from RDFs corrected with the three main methods described previously (solid lines). The uncorrected S v (0; R)-value starts a smooth increase from around roughly 40 Å, while the structural correlations die out. This indicates that the RDF is converging towards a value slightly above 1 such that the value of the integral truncated at R is increasing proportionally to R 3 , and the low-q structure factor intensity will be entirely dependent on when one chooses to stop sampling the RDF, a choice often governed by the size of the MD simulation cell. For the Perera-correction, k lm is simply set to the first r-value that gives g lm (r) > 0, as suggested in the original paper . Due to the finite bin-size of 0.05 Å in sampling the RDF, as well as the fact that an LJ particle is not completely hard, the value is associated with some inaccuracy. Having this in mind, we set the value to 2.925 Å. For the volume correction, R lm was set to 2.8240 Å using a simple fitting-method to find the excluded volume which we will describe in the next section on solute-solvent LJ systems. The volume-and van der Vegt correction both flatten out S v (0; R) at R-values roughly above 40 Å to slightly oscillate around their average value in this region. The Perera-correction seems to have slightly overcorrected the RDF such that the S v (0; R)-value starts to systematically decrease at long R-values. This small overcorrection can most likely be eliminated by further tuning the involved parameters.