In this section, we evaluate the performance of the D3S scheme. We begin with our initial ill-behaved case of H2-NiKur. The PES curves as well as the dispersion energy curves are shown in Figure . As expected, the PES and dispersion energy curves have smoothed, resulting in the disappearance of the local minimum in the case of the D3S(0) correction. A negligible barrier of 0.3 kJ/mol is still present on the restricted scan plot for the D3S(BJ) case; however, this is a restricted scan, and in relaxed scan plots, this barrier might disappear. To verify this, we reoptimized the H2-NiKur-(2) structure at the BLYP-D3S(BJ)/def2-SVP and B3LYP-D3S(BJ)/def2-SVP levels, and we indeed observed that the optimization now results in the correct H2-NiKur-(1) minimum. Additionally, we reoptimized all incorrect minima found for other systems described in the section above. All four problematic cases optimized to the correct geometries with the D3S approach. Although the disappearance of unphysical minima is indeed significant progress, it will only be useful for large-scale applications if our reparameterization does not affect the accuracy of interaction energies, as measured by performance on large benchmark sets. For the benchmark set we chose the large Main-Group Chemistry Database MGCDB84 database that includes 84 datasets and 4986 data points. The database can be separated into eight subsets that include different datatypes such as: non-covalent easy dimers (NCED), non-covalent easy clusters (NCEC), non-covalent difficult dimers (NCD), easy isomerization energies (IE), difficult isomerization energies (ID), easy thermochemistry (TCE), difficult thermochemistry (TCD), and barrier heights (BH). The separation between difficult and easy datatypes are made based on the involvement of either self-interaction error or strong correlation. Easy interactions are not significantly characterized by either of these effects. The results of benchmark tests are shown in Table and Tables S5-S7. As we can see, the D3S model does not compromise the accuracy of the obtained interaction energies, performing as well as the D3 scheme. Moreover, in some particular cases (e.g., the BH subset), the precision of the D3S model is even slightly better than that of the D3 model, with small decreases in RMSD values of approximately 0.01 kJ/mol. Table . RMS deviations in kJ/mol for the benchmark tests for the 11 D3S(BJ) corrected density functionals. The RMSDs for the standard D3(BJ) dispersion corrected functionals are given in parentheses. The eight subsets of MGCDB84 dataset include non-covalent easy dimers (NCED), non-covalent easy clusters (NCEC), non-covalent difficult dimers (NCD), easy isomerisation energies (IE), difficult isomerisation energies (ID), easy thermochemistry (TCE), difficult thermochemistry (TCD), barrier heights (BH). It is important to note that the common assumption that the accuracy of methods parameterized for small complexes or clusters remains consistent for larger ones is not generally true, since larger molecules have more long-range dispersion terms, leading to a potential accumulation of errors with increasing system size. Thus, it is also potentially important to test the accuracy of the D3S correction on other benchmarks that includes large molecular systems. For that purpose, we chose the L7 dataset that includes complexes of up to 112 atoms. The results of the test are given in Table . As we can observe, the discrepancy between the D3S and D3 methods becomes more pronounced, with the largest difference in RMSD values being 0.66 kJ/mol, with D3S generally exhibiting larger RMSDs. However, this discrepancy is still significantly smaller than the inherent errors associated with artifactual local minima present in the standard D3 dispersion correction method. To compare the accuracy of the D3S and D3 schemes for hydrogen molecule binding, a subset of the H2Bind78×7 dataset was used. The original dataset includes 78 potential energy curves for H2 binding, consisting of the equilibrium geometry, two compressed geometries (0.75*req and 0.9*req), and three elongated geometries (1.1*req, 1.25*req, and 1.5*req). In addition, the original dataset also includes 78 vertical interaction energies that were not included in the current assessment. The resulting subset consists of 467 data points and will be referred to below as the H2Bind78×6 dataset. Within the H2Bind78×6 dataset, it is important to further separate the data into two subsets. One subset includes only cationic species, referred to as H2Bind78×6Ion (287 data points), while the other includes only neutral molecules, referred to as H2Bind78×6Neutral (180 data points). The results of the performance of the D3 and D3S schemes are shown in Table and Table .