Moving on to hybrid meta-GGAs, indications of the performance of SCAN0, the hybridized version of SCAN, has been obtained from simulations based on a deep neural network potential (SCAN0/ML) which indicate that SCAN0 is still overstructured. With the exception of M06-HF with 100% exact exchange, the hybrid Minnesota functionals are generally accurate in predicting the height of the first minimum, but they fail to accurately predict its position (Fig. , right). However, Del Ben et al. discovered that M06-2X, which appears to be the best performing Minnesota functional for water overall, further improves when coupled with the D3 correction . In general, the first minimum r * min is shifted to a smaller intermolecular distance when there is either an excessive amount of exchange (M06-HF) or when the correlation effects overestimate vdW interactions. This highlights the remarkable sensitivity between (exact) exchange and correlation, both of which tend to compress or augment the first coordination peak instead of having compensatory effects. Achieving an accurate description of liquid water with DFT therefore requires finding the correct balance between these two quantum effects. This quest has motivated the refinement of XC functionals, where the occupied and virtual KS orbitals contribute to non-local correlation just as the occupied orbitals contribute to the non-local exact exchange. From Fig. , the RPA, which consists of exact exchange plus the RPA correlation, appears as the most promising rung-5 (post-HF) DFT approach in this direction, e.g., yielding very good structural properties outperforming MP2 .